00:17 We should start,
00:18 right?
00:22 A life.
00:35 Uh,
00:36 good morning.
00:37 Uh,
00:37 good,
00:38 uh,
00:39 Afternoon.
00:40 Good evening to everybody.
00:43 Welcome,
00:44 uh,
00:44 to this,
00:44 uh,
00:45 uh,
00:45 two-day,
00:46 uh,
00:47 conference on vaccinating,
00:48 uh,
00:49 South Asia.
00:50 Uh,
00:50 I will be,
00:51 um,
00:52 uh,
00:52 moderating this,
00:53 uh,
00:53 this 1st,
00:55 1st day,
00:56 and,
00:57 uh,
00:57 uh,
00:58 we are ready to,
00:59 to start.
01:00 My name is Mauriti Bussolo,
01:02 and I give the floor
01:03 to Hans Timmer,
01:04 uh,
01:04 the Chief economist for,
01:06 uh,
01:06 South Asia
01:08 at the World Bank for some opening remarks.
01:10 Uh,
01:11 Hans,
01:11 the floor is yours.
01:15 To,
01:16 uh,
01:16 Maurizio.
01:18 And good evening,
01:20 good afternoon,
01:20 and good morning.
01:22 Uh,
01:23 welcome to the 7th conference of the South Asia Economic Policy Network.
01:29 We are at the start of 2 exciting days.
01:33 Uh,
01:34 it's the 7th conference.
01:36 We organize this conference twice a year.
01:39 So
01:40 the series has actually a short history.
01:42 It started early
01:44 2018.
01:46 Uh,
01:47 but,
01:47 uh,
01:47 these conferences have
01:49 already become very useful.
01:52 They are useful for us and the World Bank because
01:56 it helps us to
01:58 get inputs for the upcoming South Asia economic focus.
02:03 That is a report that we publish twice a year.
02:06 Uh,
02:06 it contains a description and a forecast of
02:08 the economic situation in the South Asia region.
02:12 But it always also contains a chapter on a topical issue.
02:18 And the conference preceding the report
02:21 is always devoted to that topical issue,
02:26 and this time it is South Asia vaccinates.
02:30 Uh,
02:31 I hope also that the conference is useful for researchers and practitioners
02:37 in the region,
02:38 that it stimulates research,
02:41 that it encourages
02:43 evidence-based debates.
02:46 Always,
02:47 there are 4 parts to the conference.
02:50 The first part is presentation of academic papers,
02:54 and this time we have really excellent papers grouped in 2 sessions,
02:59 one on financing of vaccines,
03:02 the other one on
03:03 the distributional impacts.
03:05 The second part is always a keynote lecture,
03:08 and it's really exciting.
03:10 To have the opportunity this time to listen to
03:14 Nobel Prize winner Michael Kramer.
03:17 The 3rd session
03:19 is always devoted to the upcoming report,
03:22 so also this time.
03:24 Uh,
03:24 and then,
03:25 uh,
03:25 last but not least,
03:27 uh,
03:27 we always have a policy panel.
03:29 Uh,
03:30 we,
03:31 we sometimes loosely use the word,
03:33 uh,
03:34 uh,
03:34 expert panel.
03:36 But this time,
03:37 I can't think of of better experts.
03:40 We have found
03:41 key players in the current
03:43 vaccination program in South Asia,
03:47 willing to discuss the challenges and opportunities as they see it.
03:52 So really exciting two days.
03:55 South Asia
03:57 has
03:58 embarked on an ambitious path to
04:01 vaccinate its population.
04:04 Uh,
04:04 policymakers and
04:06 healthcare workers,
04:07 they are working extremely hard
04:10 to achieve this task
04:11 as fast,
04:12 as cost-effective,
04:14 as
04:15 equitable,
04:16 uh,
04:16 as possible.
04:18 Uh,
04:18 it is primarily a medical challenge,
04:21 but
04:22 It's also a challenge for economists
04:24 to see how from our
04:27 profession,
04:28 uh
04:28 we can best advise governments and other key players.
04:32 Uh,
04:33 as,
04:33 as often there,
04:34 there's always the question of the role of governments and the role of the market.
04:39 Uh,
04:40 we have seen an extremely successful cooperation between governments
04:44 and private companies in the development and production of vaccines,
04:49 even if
04:50 it has led to some
04:52 disparities across countries
04:54 in terms of early access to the vaccines.
04:58 But it's always important to get that division
05:00 of labor between the government and the market,
05:03 uh,
05:03 right?
05:05 There is the issue of global economic cooperation.
05:10 Ultimately,
05:11 uh,
05:11 global immunity is a global public good.
05:15 So how does the world best provide this,
05:18 this global public good?
05:20 There is the issue of fiscal challenges.
05:23 Uh,
05:23 that's especially
05:25 uh an important issue for South Asia,
05:28 where debt levels are already high,
05:31 where
05:32 deficits are large.
05:34 Where the revenue base is small and government spending on
05:38 healthcare is small,
05:40 uh,
05:40 both as percentage of total spending of the government
05:44 and also as percentage of total spending of healthcare because
05:49 most of the spending on healthcare in South Asia
05:52 is out of pocket spending.
05:55 There is the issue of distributional impacts of the rollout of the vaccines.
06:01 Uh,
06:02 inequality is already large in uh in South Asia
06:05 and it significantly has increased because of the pandemic.
06:10 There's also the opportunity to improve going forward the healthcare system,
06:16 strengthening preventive care,
06:17 becoming better prepared for the next pandemic.
06:20 And so all these issues where there are strong
06:24 economic insights
06:26 to be gained also
06:27 will be discussed during the conference.
06:31 Uh,
06:31 but one thing we,
06:32 we already know.
06:34 And that is time is of the essence.
06:38 The sooner people are vaccinated,
06:41 the fewer people will die.
06:43 And the greater the opportunity to limit further economic damage.
06:50 So time is of the essence.
06:52 Without further ado and without
06:54 wasting more time,
06:56 let's dive into the program.
06:58 Let me already thank all the presenters and discussant,
07:01 and I'm sure that we will have a productive two days.
07:05 Thank you all so much and back to Maurizio.
07:10 Uh,
07:10 thank,
07:11 thank you very much,
07:12 uh,
07:12 Hansel,
07:12 for
07:13 the introduction.
07:15 Uh,
07:15 so,
07:16 in the interest of time,
07:17 I will,
07:18 uh,
07:18 immediately start the 1st,
07:20 1st session.
07:22 Let me just,
07:22 uh,
07:22 say a quick word about,
07:24 uh,
07:24 housekeeping.
07:25 We,
07:26 uh,
07:26 we run on a fairly tight schedule,
07:29 so,
07:30 uh,
07:30 I beg
07:32 the presenters to limit it to their 10 minutes.
07:35 Um,
07:36 uh,
07:36 Rana
07:37 will send you
07:38 a message in the chat when it's,
07:40 uh,
07:40 5 minutes.
07:41 Uh,
07:42 so you will have to have half of your presentation done by then.
07:46 And,
07:46 uh,
07:47 if needed,
07:48 I'll,
07:48 I'll,
07:48 I'll send a reminder 1 minute before.
07:51 So,
07:51 uh,
07:52 that,
07:52 that's it.
07:53 And we can start the first session,
07:55 which is on vaccine finance and fiscal aspect of vaccination.
07:59 Um,
08:00 Katth Andrews from the World Bank,
08:02 uh,
08:03 will start.
08:04 The,
08:05 the floor is yours,
08:06 Scott.
08:08 Thank you very much.
08:27 Thank you.
08:27 I'm delighted to be here on behalf of my co-authors,
08:31 Chris,
08:31 Jewel and uh Jay as well to discuss health financing
08:35 and health systems considerations as a high-level overview and background
08:39 for the rest of the discussion today as South Asia
08:42 plans to vaccinate its population against COVID-19.
08:54 As you'll know,
08:54 South Asia or SAR as it is in World Bank parlance is
08:58 comprised of 8 countries and of those 8 together,
09:01 it comprises 25% of the world's population.
09:05 It's quite a diverse region,
09:06 some of the world's largest populations such as in India and Pakistan
09:10 and also some of the world's smallest like Maldives and Bhutan.
09:13 It's largely a lower middle income region as you can tell,
09:17 and by the median age,
09:18 it's a young population as well,
09:20 which has important implications for the
09:22 pandemic's trajectory and for vaccination.
09:27 Interestingly,
09:28 while having more than 25% of the globe's population,
09:30 SARS has a lower share of confirmed COVID cases,
09:34 which is demonstrated by the fact that all of the
09:37 blue circles here fall below the line of equivalence between the
09:41 share of the global population and the global COVID-19 cases.
09:46 Likely in part due to a younger population
09:49 as we just described and also constrained testing.
09:52 As we know,
09:53 younger people have less severe COVID-19 cases and are therefore also less
09:58 likely to both be tested and to pass away from the disease.
10:02 The pandemic's trajectory looks different in South Asia from other regions.
10:07 As you can see,
10:07 SARS here is this dark thick blue line.
10:11 The main difference is is that SARS
10:13 had its first spike in confirmed cases,
10:15 a bit on the later side,
10:17 almost in parallel with Sub-Saharan Africa here and
10:19 much later than East Asia and Pacific,
10:21 for example.
10:23 Uh,
10:23 the daily confirmed new cases peaked back in the fall and began to begin to decline,
10:29 and we can all hope that it will continue on this pattern.
10:33 However,
10:33 this regional pattern,
10:35 mainly driven by India,
10:36 which you can see here,
10:37 the uh light blue solid line,
10:40 masks important country-specific variation in the region.
10:43 So this snarl of lines down here includes Afghanistan,
10:47 Bangladesh and Pakistan,
10:48 which were the first to experience a major surge in reported cases,
10:52 followed by India and Nepal that had similar surges,
10:55 but uh the peak was about 2 to 3 months later.
10:58 And impressively,
10:59 Bhutan in particular,
11:00 in addition to Maldives and Sri Lanka have had
11:02 a relatively greater success in containing containing the pandemic.
11:06 But importantly,
11:07 case count is highly dependent on testing,
11:09 as we know,
11:10 and India has had the highest testing rate at about 80 tests per 100,000
11:14 population per day and Afghanistan has had less than 1/10 of that testing rate.
11:18 So,
11:18 the extent to which these confirmed case counts reflect
11:22 true case counts really
11:23 remains a bit unknown.
11:25 So,
11:25 how is this translated into deaths?
11:28 The number of deaths ranges from only 1 in Bhutan to over 150,000 in India,
11:34 and Bhutan is an excellent example of where crucial and timely measures were
11:37 taken to prevent the spread of the virus with a lot of success.
11:40 And like in other areas,
11:42 most deaths have occurred among those aged 60 and above.
11:47 Beyond the massive impact on morbidity and mortality,
11:50 COVID has also obviously had a devastating economic effect.
11:53 There's a strong negative correlation between COVID deaths,
11:57 as you can see here on,
11:59 on the um on the X axis.
12:02 And growth in GDP per capita.
12:04 Um,
12:05 so,
12:05 as countries with more deaths down here,
12:07 you can also see have also had a larger decline in GDP growth.
12:12 So,
12:12 as we all know,
12:13 COVID-19 lockdown policies and social distancing have really resulted in
12:17 steep declines in economic activity globally and as a result,
12:21 the world is experiencing one of the largest declines in GDP in almost a century.
12:25 Countries that implemented more stringent lockdown policies or failed to contain
12:29 the virus appear to have taken the biggest economic hit,
12:32 as did those where as those economies that
12:35 were more dependent on the service sector,
12:37 for example,
12:37 tourism such as in Maldives,
12:39 as you can see here.
12:43 Prior to the pandemic,
12:44 SARS was growing faster than the global average,
12:47 as you can see in this dark blue line above the dotted line of the global average,
12:51 but it's been impacted in a similar way in um
12:55 in 2020 from the the COVID impact.
12:58 Now,
12:59 all countries in SAR except for Bangladesh
13:01 have are expected to have negative growth with the
13:04 largest declines seen in Maldives followed by India.
13:10 This economic shock aggravates an already weak health financing landscape,
13:14 unfortunately.
13:15 Among all regions globally,
13:17 SARS has the lowest level of public spending on health as a share
13:21 of GDP as you can see from this uh this gray line here.
13:26 It also has the highest level of out of pocket payments,
13:29 meaning that the population is relied upon more
13:32 to um financing finance their own healthcare and also
13:35 the the private sector of healthcare within within
13:39 the South Asian region is also very prominent.
13:42 Within are there important differences in financing for health across countries.
13:46 So health uh out of pocket spending rather for
13:49 health is heavily relied upon across all countries,
13:52 of course,
13:52 but particularly in Afghanistan and Bangladesh.
13:55 And the tiny nation of Maldives has the um
13:59 The,
14:00 uh,
14:00 uh,
14:01 leaves the region and public spending on health as a share of GDP.
14:04 We see that Afghanistan relies on external financing
14:08 much more than,
14:09 uh,
14:09 some of the other countries in the region,
14:11 here at 16.4%.
14:13 But overall,
14:14 as you can tell,
14:15 health is not particularly prioritized in SAR from
14:17 a government financing perspective and taken together,
14:21 this suggests a tight fiscal landscape for
14:23 financing the rollout of the COVID-19 vaccine
14:25 and implies that mobilization of substantial additional funds
14:28 may be necessary to cover the cost.
14:32 So,
14:32 even assuming that countries have sufficient fiscal space to finance the
14:36 vaccination and that there is sufficient
14:38 vaccine supply without production constraints,
14:40 for example,
14:41 service delivery challenges may come into play.
14:43 So,
14:44 these service delivery barriers may be on,
14:45 of course,
14:46 both on the supply and the demand sides and on the supply side,
14:49 they may appear in the form of,
14:51 for example,
14:51 limited human resources for health in terms of
14:54 both well trained and well allocated human resources,
14:57 inadequate cold chain and distribution systems,
14:59 etc.
15:00 And on the demand side,
15:01 a vaccine hesitancy may play a role as may the challenge of following up.
15:06 With individual patients for a second dose.
15:09 So,
15:09 while there's no perfect proxy for COVID-19 vaccination delivery,
15:12 DTP 3 vaccination rates among children,
15:15 which is a common childhood vaccine
15:17 with 3 doses,
15:18 may serve as an approximate bellwether for a
15:21 health system's capacity to identify a target population
15:24 in need of vaccination and then to follow them up with multiple doses over time.
15:29 Low rates of DTP-3 coverage in Afghanistan and Pakistan,
15:32 as you can see here.
15:34 Um,
15:35 signal potential challenges in achieving high COVID vaccine
15:38 coverage,
15:39 especially since these childhood vaccination systems have been in
15:42 place for decades and COVID-19 infrastructure is relatively new.
15:46 Similarly,
15:46 the universal health coverage UHC Service Coverage index is a
15:51 metric that combines um various health service coverage indicators on
15:56 on communicable disease care and childhood immunization
15:58 and we can imagine that countries that have a low
16:01 service coverage and a low public financing for health,
16:04 such as those in the quadrant over here,
16:06 including in Afghanistan,
16:08 Bangladesh,
16:08 Nepal,
16:09 Pakistan,
16:09 India,
16:10 could also face some challenges from a demand,
16:13 supply and or financing perspective.
16:17 So,
16:17 we've discussed health financing considerations
16:19 and service delivery considerations,
16:21 but what will it actually take to get
16:23 shots in arms in terms of costs.
16:25 So,
16:25 we've reviewed the latest um publicly available information on
16:29 procurement details and commonly used assumption about distribution costs,
16:33 which yielded that the costs of the vaccine itself
16:36 are highly variable and of course changing every day,
16:39 ranging in SAR from about $3 per dose in India to an
16:42 assumed very rough estimate of perhaps $7 per dose in Pakistan.
16:47 And international working groups estimate that it'll take about 89 cents
16:52 per dose for international transport,
16:54 about $1.66
16:55 per dose for domestic transport,
16:57 and then of course,
16:58 about 10% wastage along the way given utilization
17:01 and efficiencies and breakdowns in the cold chain.
17:04 So,
17:04 this yields a per person vaccinated cost of about 12 to $21 depending on
17:10 whether you're on the high or low level of this per dose cost.
17:13 And also,
17:14 as you're aware,
17:15 COVAX is playing a role.
17:16 It's a pool purchasing mechanism that benefits low income countries and SAR
17:21 countries are among those eligible to receive the 1st 20% of their population
17:25 coverage for free,
17:27 meaning that they'll only have to cover
17:29 the international and domestic transport costs.
17:32 Country governments and SAR will then also be
17:34 responsible for covering or finding the financing to cover
17:38 the cost of vaccinating the remaining say 50% of
17:40 the population required to reach herd immunity levels,
17:43 assuming that
17:44 reaching 70% herd immunity is part of their priorities.
17:49 Taking some of these basic assumptions and
17:51 tweaking them to more accurately reflect free
17:53 vaccine doses from other sources such as
17:56 India and public information on procurement deals,
17:58 we can begin to generate a very rough simplistic cost estimate per country to
18:02 get from the 20% coverage from COVAX to the 70% ideal coverage from um
18:08 from herd immunity.
18:09 So,
18:09 all countries in SAR except for Pakistan thus far
18:12 have received shipments of free vaccines from India,
18:15 uh,
18:15 and some have made initial procurement deals with the Serum Institute in India,
18:18 for example,
18:19 and notably,
18:19 Bhutan is receiving all of its vaccine doses for free from India,
18:22 which will only mean it will need to cover domestic transportation costs.
18:27 One
18:28 minute.
18:29 Perfect.
18:30 So,
18:30 this toy example,
18:32 taking it together is uh allows us to demonstrate that
18:35 even if the 1st 20% of the population is covered by COAX
18:39 and the vaccine itself can be purchased for about $4 per dose,
18:42 it may be prohibitively expensive for some countries and SAR,
18:45 especially Afghanistan and Pakistan,
18:49 where it would comprise the vast majority
18:51 of the available government health budget in 2022,
18:54 for example.
18:56 Mm
18:59 So,
18:59 in conclusion,
19:00 in addition to the direct impact
19:02 of uh the COVID-19
19:05 um
19:05 pandemic on morbidity and mortality,
19:07 the pandemic is also obviously adversely affecting
19:09 economic activity worldwide and in the region.
19:12 Health systems and health financing constraints
19:14 in SARS may pose extra difficulties
19:16 for both funding and distribution of
19:19 the vaccine with perhaps Afghanistan and Pakistan
19:22 likely to face significant financing challenges in addition to other countries.
19:26 So,
19:26 targeted service delivery and financing support in SAR may be able to help
19:30 facilitate uh the realization of health and economic benefits of the vaccine.
19:34 Unfortunately,
19:35 many development banks are coming in with a lot of financial support
19:39 because it's not a matter of whether to vaccinate,
19:41 but how to do so in a way that yields optimal outcomes.
19:44 Thank you.
19:49 Excellent.
19:50 Uh,
19:50 thank you.
19:51 Thank you very much,
19:52 uh,
19:52 Kat,
19:53 for sticking with the,
19:54 with the time,
19:55 and we can,
19:56 uh,
19:57 swiftly move on to
19:59 our second,
20:00 uh,
20:00 presentation,
20:01 which is,
20:02 um,
20:03 from,
20:04 uh,
20:04 Arini
20:06 Vira Sikira,
20:08 uh,
20:08 from the Institute of Public
20:10 Public Policy Studies of Sri Lanka.
20:13 Um,
20:14 the floor is
20:15 yours,
20:16 Irene.
20:17 Thank you.
20:18 Thank you very much.
20:20 Let me just uh share my slides.
20:24 And,
20:25 and just,
20:25 just while this,
20:26 uh,
20:27 this comes online,
20:28 uh,
20:28 you are all invited to send questions via the,
20:31 uh,
20:31 the chat box.
20:32 Uh,
20:33 thank you.
20:33 Go on.
20:37 Uh,
20:38 can my slides be seen?
20:39 Are we good?
20:40 Yeah,
20:41 yes,
20:41 uh,
20:42 we're good.
20:43 I can see them.
20:43 Thanks.
20:44 OK,
20:45 thank you very much.
20:46 Uh,
20:46 so hello everyone.
20:47 Uh,
20:48 today I will be,
20:48 uh,
20:49 presenting some of the key findings from a paper co-authored by,
20:52 uh,
20:53 myself and my colleague Kitmina Hei.
20:55 Uh,
20:55 we are both research economists at the Institute of Policy Studies of Sri Lanka.
21:00 So,
21:00 specifically,
21:01 our paper deals with the issue of vaccine financing as discussed,
21:05 and,
21:05 uh,
21:05 more broadly we look at the fiscal
21:07 implications of vaccinating Sri Lanka against COVID-19.
21:11 Uh,
21:12 so I'll very quickly first,
21:13 um,
21:14 uh,
21:14 give you an update on how the pandemic has sort
21:16 of played out in Sri Lanka over the past year.
21:19 So,
21:19 um,
21:20 we experienced the first wave of infections,
21:23 uh,
21:23 last March,
21:24 uh,
21:24 in March 2020,
21:26 and uh.
21:26 However,
21:27 this,
21:27 uh,
21:27 the spread was largely contained at that stage,
21:30 uh,
21:30 but subsequently in October 2020,
21:33 we experienced a,
21:34 a bigger second wave of infections,
21:36 and the case,
21:37 uh,
21:38 caseload has sort of,
21:39 uh,
21:39 gone up from there,
21:40 as you can see in this graph.
21:43 Uh,
21:44 so,
21:44 uh,
21:44 when it comes to the vaccination,
21:46 uh,
21:47 driver strategy,
21:47 this has somewhat already,
21:49 uh,
21:49 begun as of,
21:50 uh,
21:50 January this year.
21:52 Um,
21:52 and Sri Lanka's National Medicines Regulatory Authority has,
21:56 uh,
21:57 only approved Oxford's,
21:58 uh,
21:58 AstraZeneca vaccine for emergencies in the country at the moment.
22:02 Um,
22:03 and in terms of,
22:04 uh,
22:04 the vaccine doses that we have secured,
22:06 uh,
22:07 that are in the pipeline,
22:08 um,
22:09 we have,
22:10 uh,
22:10 got some donations from India's Neighborhood Friendly,
22:12 uh,
22:13 Policy,
22:13 which came in first.
22:15 Uh,
22:15 we are set to receive another nearly 2 million doses,
22:18 uh,
22:18 for a start
22:19 from WHO's COvax facility donation,
22:22 and we've also made a purchase,
22:24 uh,
22:24 order from the Serum Institute of India.
22:27 Uh,
22:27 so in terms of the official kind of,
22:29 uh,
22:30 the government's,
22:31 um,
22:32 Position on the vaccination plan at the moment,
22:35 a cabinet decision has been taken to,
22:37 uh,
22:38 to aim to,
22:39 uh,
22:41 give access to the vaccination to 14 million people in Sri Lanka,
22:45 which amounts to around 60% of the country.
22:48 Uh,
22:48 then when it comes to,
22:50 uh,
22:50 the priority list,
22:51 there was some,
22:52 uh,
22:52 confusion and back and forth about this because initially it was announced that,
22:56 uh,
22:57 healthcare workers,
22:58 uh,
22:58 the elderly and other frontline workers would,
23:01 uh,
23:01 receive the vaccine first,
23:02 and which is how the drive started.
23:05 But subsequently,
23:06 uh,
23:06 it was announced that those in the age group of 30 to 60,
23:10 uh,
23:11 in vulnerable areas in the country could also receive the vaccine.
23:15 So this is how the vaccine
23:18 rollout is proceeding.
23:20 So moving on to the real focus of the study,
23:24 we aim to kind of assess the fiscal implications of reaching
23:29 a target of vaccinating 80% of Sri Lanka's population against COVID.
23:34 Uh,
23:34 we made an assumption in the paper that around 20% of the population will,
23:38 uh,
23:39 be vaccinated through donations.
23:40 And this was sort of a fair assumption to make,
23:43 um,
23:43 at the time of writing because
23:45 it was announced that Sri Lanka will probably receive enough,
23:48 uh,
23:48 uh,
23:49 doses from WHO's COVAX facility to cover 20% of the population.
23:54 So we then kind of do a,
23:56 Rough cost estimate to see how much it would cost to
24:00 reach the 80% target by vaccinating,
24:03 by,
24:03 by the government having to spend to vaccinate 60% of the country's population,
24:08 and along with this,
24:09 we look at the associated fiscal trade-offs of using
24:12 government budget for this purpose.
24:15 When it comes to,
24:16 um,
24:17 the actual kind of focus of,
24:19 of the components of the study,
24:22 uh,
24:22 we do 3 things.
24:23 We do a costing exercise,
24:25 we then analyze,
24:26 uh,
24:27 uh,
24:27 look at the pros and cons of some financing options that are available,
24:31 and we also do an economic impact analysis.
24:33 Um,
24:34 so firstly,
24:35 when it comes to the costing exercise,
24:37 um,
24:38 this is actually more of an.
24:40 Vaccination that is done with the limited data that we have
24:44 available on um immunization delivery costs in Sri Lanka.
24:48 So as we know,
24:48 the vaccine dosage cost is publicly known and available,
24:53 uh,
24:53 but all these ancillary costs around,
24:56 uh,
24:56 distributing a vaccine,
24:58 um,
24:58 are a little difficult and sort of,
25:00 we're still at a new stage of,
25:01 um,
25:02 the vaccine rollout to have very precise data.
25:05 Um,
25:06 so,
25:06 for this reason,
25:07 we use one of the most recently available vaccine deployment plans,
25:10 which,
25:11 uh,
25:11 in Sri Lanka,
25:12 which was
25:12 used for a previous influenza pandemic,
25:15 of course,
25:15 um,
25:16 it's a totally different scale when it comes to COVID-19.
25:19 But,
25:20 uh,
25:20 what we really are aiming at is to get a sort of a ballpark figure to see
25:25 what,
25:25 uh,
25:26 the vaccination program,
25:27 uh,
25:28 what the scale of it will kind of look like.
25:31 Uh,
25:32 and then
25:33 moving on to the financing options.
25:35 This is basically just a discussion of the pros and cons of different options.
25:39 And,
25:40 uh,
25:40 finally,
25:40 we,
25:41 uh,
25:41 wanted to demonstrate like,
25:43 um,
25:44 how there's an economic benefit over and above the,
25:47 um,
25:48 health benefits of vaccinating the population.
25:50 So we do
25:51 a sort of a quick,
25:52 uh,
25:52 economic impact analysis and to do this,
25:54 we use,
25:55 um,
25:55 a tool,
25:56 an impact analysis tool,
25:57 which implies
25:58 the national,
25:59 um,
25:59 input output tables.
26:03 So,
26:04 uh,
26:04 firstly,
26:04 when it comes to the costing,
26:07 um,
26:08 we have estimated that it
26:10 would take around $101 million US dollars,
26:14 but
26:14 like I said,
26:15 this is,
26:15 um,
26:16 uh,
26:16 we have used a lot of proxy data,
26:18 so this is
26:19 a minimum,
26:20 uh,
26:21 a very sort of,
26:22 uh,
26:22 minimum,
26:22 it should be treated as a minimum cost,
26:24 uh,
26:24 estimate.
26:27 And then moving on to,
26:29 uh,
26:29 the financing options,
26:31 uh,
26:32 so we have identified three of which.
26:34 The first is,
26:35 uh,
26:35 uh,
26:36 like reallocating budgetary uh commitments.
26:39 Um,
26:39 however,
26:40 it should be said that in Sri Lanka's national budget for 2021,
26:45 uh,
26:46 no pro budgetary provisions have been made
26:49 for,
26:49 uh,
26:50 COVID-19 vaccination strategy or anything,
26:52 no specific allocations to the pandemic have been made.
26:56 Uh,
26:56 in addition to this,
26:57 the country's,
26:58 uh,
26:58 health budget has,
26:59 uh,
26:59 reduced compared to the previous year in this year's budget,
27:03 and this is also constrained given the obvious,
27:05 uh,
27:06 stresses,
27:06 uh,
27:06 during,
27:07 for the health sector during a pandemic,
27:09 um.
27:10 In addition to this,
27:11 the country faces,
27:13 um,
27:13 a fiscal,
27:14 a very tight fiscal situation on the macroeconomic front.
27:18 So as a result,
27:19 uh,
27:20 this option is a little tricky and
27:22 the government has to be careful not to pull away from other essential health,
27:25 uh,
27:26 spending.
27:26 Uh,
27:27 as well.
27:28 So which brings us to the second option,
27:30 which we feel is a more prudent,
27:31 uh,
27:32 option
27:33 to look at more targeted tax policy interventions
27:36 to raise revenue specifically to vaccinate the population.
27:42 Um,
27:43 and it should be mentioned that,
27:45 uh,
27:45 the current,
27:46 the government in power,
27:47 when they came into power,
27:48 they,
27:48 uh,
27:48 reduced tax rates across the board,
27:50 and they have also indicated that tax policy
27:53 will largely remain unchanged in the coming years.
27:55 So we're unlikely to see any,
27:58 uh,
27:58 major shifts in,
28:00 um,
28:00 or major upward revisions in taxes,
28:02 but it's important to recognize that given the country's fiscal situation
28:07 and dealing with the pandemic,
28:08 it,
28:09 um,
28:10 These targeted stra uh,
28:12 tax,
28:12 uh,
28:13 strategies are important to implement.
28:16 So,
28:16 specifically,
28:17 we see some scope for,
28:19 uh,
28:19 perhaps a rationalization in,
28:21 uh,
28:21 of uh tax rationalization in,
28:25 uh,
28:25 the area of like luxury goods or scenic goods.
28:27 So when I say scenic goods,
28:28 I mean things like alcohol and cigarettes,
28:30 because
28:31 these products have the,
28:32 because of the inelastic nature,
28:34 they have the potential to generate.
28:35 Generate,
28:36 um,
28:37 a significant amount of,
28:38 uh,
28:38 extra revenue.
28:40 And,
28:40 uh,
28:41 for an example,
28:41 in a recent study that IPS did,
28:43 we found
28:44 that government revenue could increase up to as much as,
28:47 um,
28:48 40 billion Sri Lankan rupees,
28:50 which is about double what we estimated for the
28:53 cost of the vaccine drives.
28:54 So,
28:55 uh,
28:55 these are options that,
28:56 uh,
28:56 the Sri Lankan government can consider and should
28:59 consider as like low hanging fruit options.
29:01 Uh,
29:05 sorry,
29:05 uh,
29:05 I'll wrap up quickly,
29:07 and,
29:07 uh,
29:07 the final option is of course direct assistance,
29:10 but Sri Lanka can't
29:11 depend on this,
29:12 uh,
29:12 too much because we are a middle income country,
29:14 so we don't have as much access,
29:16 uh,
29:17 to direct options other than,
29:18 say,
29:19 the,
29:19 uh,
29:19 WHO's CO vax,
29:21 uh,
29:21 facility.
29:22 Uh,
29:23 very quickly,
29:23 we did an economic,
29:25 uh,
29:25 impact analysis where the,
29:26 where we,
29:27 uh,
29:27 uh,
29:28 inject a positive shock to the economy,
29:30 uh,
29:30 this,
29:31 uh,
29:31 which is the size of the vaccination strategy.
29:33 And as you can see,
29:34 uh,
29:35 there are positive effects all around,
29:36 and these are concentrated mostly in the services sector,
29:39 which also intuitively makes sense
29:41 because sectors like tourism,
29:42 uh,
29:43 which were affected are likely to bounce back.
29:46 And finally,
29:47 um,
29:48 I will wrap up my presentation by just saying that
29:51 we feel the best way forward to Sri Lanka is
29:54 a medium-term self-financing strategy through which
29:58 targeted tax policy interventions are prioritized,
30:02 and these can be complemented with available external financing.
30:06 And
30:08 finally,
30:09 Uh,
30:09 it's also really important to look at the future in the sense
30:12 that we potentially need to finance continuous vaccination cycles because of,
30:17 uh,
30:18 vaccine boosters and potentially new,
30:20 newer vaccines to tackle newer variants of the virus in the coming years.
30:24 So it would be prudent for the government of Sri Lanka to get their
30:26 fiscal house in order and implement these
30:28 revenue generation strategies sooner rather than later.
30:32 Um,
30:33 and with that,
30:33 I'll end my presentation.
30:34 Thank you.
30:38 Thank you.
30:39 Thank you very much,
30:40 uh,
30:40 uh,
30:40 Rey.
30:41 Um,
30:42 so we have seen,
30:43 we have seen the regional,
30:44 uh,
30:45 uh,
30:45 landscape,
30:46 and we have seen,
30:48 uh,
30:48 the
30:49 situation in Sri Lanka,
30:50 and we're moving on,
30:51 uh,
30:52 with the next presentation to Bangladesh.
30:55 Uh,
30:55 Farzana
30:56 Moshi from,
30:57 uh,
30:57 Braque University,
30:59 uh,
30:59 will be next.
31:00 The floor is yours.
31:02 Thank you.
31:04 Thank you very much.
31:06 Good afternoon from Bangladesh.
31:09 Uh,
31:09 let me just share my screen.
31:25 OK.
31:26 Something is not right here.
31:39 Um,
31:40 can we,
31:40 are you there?
31:43 Fsana,
31:43 would you mind,
31:44 uh,
31:44 stop,
31:44 uh,
31:45 let me,
31:45 let me,
31:46 uh,
31:47 help you.
31:47 Can you help me,
31:49 yes.
31:51 OK.
31:52 Let me pass the ball back to you.
31:57 Do you see my PowerPoint?
31:59 Uh,
31:59 no,
31:59 can you please reshare again?
32:01 Thank you.
32:07 Um,
32:08 do you pass the ball,
32:09 please?
32:10 That I can share.
32:12 Uh,
32:13 yes,
32:13 he got the presenter's role.
32:16 No,
32:16 I don't have it.
32:17 It's in Adnan Zawai.
32:19 Oh,
32:19 sorry.
32:20 Apologies.
32:21 Yes.
32:22 It's OK.
32:23 OK,
32:24 you got the presenter's rule.
32:46 Sorry,
32:47 something is not right here.
32:49 Um,
32:49 can you,
32:50 can you please share my presentation?
32:53 OK,
32:54 let me
32:57 So Rana,
32:58 hello Kon Ying.
32:59 Yes,
33:00 I can share for Zana's presentation.
33:02 Can you give me the ball?
33:03 Yes,
33:04 please.
33:05 Let me past the presenter's rule.
33:08 OK,
33:08 you got the presenter's rule.
33:10 Thank you.
33:10 OK.
33:13 Just give me 1 2nd.
34:33 OK,
34:34 can you see my screen now?
34:36 Yes,
34:36 I can see it.
34:37 OK.
34:40 Should I start?
34:42 Yeah,
34:43 please go ahead.
34:44 Um,
34:45 sorry about this,
34:46 um.
34:48 So,
34:48 um,
34:49 my,
34:49 uh,
34:50 I'm presenting macroeconomic policy response to
34:52 coronavirus pandemic in Bangladesh and analysis.
34:55 Next slide,
34:55 please.
35:00 Uh,
35:01 sorry.
35:02 So,
35:03 um,
35:03 in this paper,
35:04 I discussed policy response to coronavirus pandemic in Bangladesh.
35:07 This is a very preliminary version of my paper.
35:10 Uh,
35:10 it's just discussion of policies,
35:13 uh,
35:13 macroeconomic situation,
35:14 some comments on future policy.
35:16 Uh,
35:17 no empirical analysis or simulation is done,
35:19 but I hope to do near future when we have more data.
35:22 Um,
35:23 thank you,
35:23 Catherine,
35:24 first for giving,
35:25 uh,
35:25 the very introduction in Bangladesh.
35:27 So I'm skipping that,
35:27 we already lost like 5 minutes.
35:29 Uh,
35:30 this issue is important,
35:31 you know,
35:31 we are talking,
35:32 uh,
35:32 about policy intervention,
35:34 but policy intervention has some other impacts on other macroeconomic variables.
35:39 Because if we expand fiscal and monetary policy,
35:42 then it has impact on inflation,
35:43 um,
35:44 unemployment,
35:45 balance of payment,
35:46 those kind of things.
35:47 Uh,
35:47 major impacts on macroeconomy,
35:49 we all know,
35:50 we,
35:50 uh,
35:50 you know,
35:50 when there is economic crisis,
35:52 there is loss of economic activity and then lack of demand,
35:56 uh,
35:56 which caused consumer and firms to cause,
35:58 um,
35:59 caused by lack of confidence.
36:00 This lack of confidence,
36:01 lack of optimism is a very,
36:04 Uh,
36:04 important factor because it,
36:06 it reduces production,
36:07 output,
36:08 employment,
36:09 and all these
36:10 eventually leads to a slowdown in the economy and eventually
36:13 leads to re recession.
36:15 Next slide,
36:15 please.
36:18 Um,
36:19 so policies are taken,
36:20 you know,
36:20 uh,
36:21 different countries have different policies.
36:23 Healthcare expenditure increased globally,
36:25 and as I said,
36:26 expansionary fiscal and monetary policies.
36:29 Uh,
36:29 these
36:30 depends,
36:30 this policy expansion depends on some factors.
36:33 First of all,
36:33 fiscal capacity.
36:35 Uh,
36:35 stimulus packages are used in developed countries,
36:38 um,
36:38 as high as 20 to 25% because
36:41 they could afford.
36:42 Developing countries,
36:43 on the other hand,
36:44 could afford only 5 to 6% of their GDP.
36:47 Debt to GDP ratio is a very important factor.
36:49 Many of the developed countries are carrying
36:52 high debt to GDP ratio,
36:53 you know,
36:53 after,
36:54 uh,
36:54 2008,
36:55 uh,
36:55 recession,
36:57 and for that,
36:58 they
36:58 could use smaller debt,
36:59 uh,
37:00 smaller,
37:00 uh,
37:01 fiscal expansion.
37:02 Tax GDP ratio,
37:03 um,
37:04 I think Tim said,
37:05 um,
37:05 it's low in developing countries.
37:07 In Bangladesh,
37:08 it's only
37:09 11% of GDP.
37:11 Interest rate inflation and monetary policy instruments.
37:14 We know when we use
37:15 expansionary monetary policy,
37:17 interest rate goes down.
37:19 And if we use that continuously,
37:21 eventually,
37:21 interest rate is in liquidity trap.
37:24 Uh,
37:24 this is what happens during 2008,
37:27 uh,
37:27 Great Recession.
37:28 Interest rates were zero% in most developed countries.
37:32 Uh,
37:32 interest rates picked up after 2015,
37:35 but it was only
37:36 less than 1%.
37:37 So,
37:38 Escal and Mary,
37:39 both policies had their limitations,
37:41 um,
37:42 during the pandemic period.
37:43 Next slide,
37:44 please.
37:50 Uh,
37:51 Bangladesh is an interesting case because Bangladesh,
37:53 uh,
37:53 was the fastest growing nation,
37:56 uh,
37:56 for a decade,
37:57 you know,
37:57 with 7% plus GDP growth rate.
37:59 And this pandemic year,
38:01 this,
38:01 this,
38:01 uh,
38:02 better economic performance helped Bangladesh to cope better.
38:05 Um,
38:06 uh,
38:07 Catherine already said,
38:08 you know,
38:08 Bangladesh is the only country,
38:10 uh,
38:10 which had positive economic growth.
38:11 We actually,
38:13 uh,
38:13 had 5.2%.
38:14 Um,
38:15 in 2020.
38:16 There are some factors,
38:17 favorable factors,
38:18 like we had a
38:19 bumper agricultural production in,
38:21 in,
38:21 last year,
38:22 and,
38:22 uh,
38:23 um,
38:24 international remittances were
38:26 consistently high.
38:27 Also,
38:27 government,
38:28 uh,
38:28 incentive packages were timely.
38:31 We had similar effects on macroeconomy.
38:33 GDP went down,
38:34 unemployment increased,
38:35 poverty increased.
38:36 There are some specific features
38:38 Bangladesh and other developed countries had,
38:40 which we have to remember,
38:42 uh,
38:42 when we craft the policy.
38:44 First,
38:44 demographic structure.
38:46 Um,
38:47 we are a densely populated country,
38:49 per square kilometer,
38:50 1100 plus population.
38:53 So it's very difficult to implement social distance,
38:55 uh,
38:56 with such density of population.
38:58 Also,
38:58 younger population is greater than,
39:00 uh,
39:01 older population,
39:02 which means the vulnerable population,
39:04 uh,
39:05 is
39:05 less.
39:07 Major,
39:08 uh,
39:08 you know,
39:09 more than 80% workers work in informal sector.
39:13 Um,
39:14 this,
39:14 uh,
39:14 you know,
39:15 informal sector usually works as a,
39:18 Uh,
39:18 shock observer cushion when we have an economic crisis because,
39:22 um,
39:23 formal sector workers
39:24 take refuge in the informal sector.
39:27 Uh,
39:27 but this pandemic is unique because it
39:30 affected both formal and informal sector workers.
39:33 Um,
39:34 there is another important issue relevant to this is,
39:37 uh,
39:37 we do not have any unemployment benefit for formal or informal sector workers.
39:42 So,
39:42 in case of job loss,
39:44 a worker,
39:44 um,
39:45 you know,
39:46 tries to use
39:47 his
39:48 or her saving,
39:49 and sell land,
39:50 assets,
39:51 whatever they have,
39:52 uh,
39:53 borrow and when everything is used up,
39:56 they're out there
39:58 looking for a job
39:59 to survive.
40:00 And this is why
40:02 blanket lockdown is difficult to implement for a longer
40:06 period of time in a country like Bangladesh.
40:09 Low tax to GDP ratio,
40:10 as I just mentioned,
40:11 which is actually linked to
40:13 higher informal sector.
40:15 Healthcare capacity is very low.
40:17 We have less than one,
40:20 nurse,
40:21 physicians,
40:22 midwives.
40:23 For 1000 people.
40:26 Uh,
40:26 next slide,
40:26 please.
40:30 So what are the policies taken?
40:32 Well,
40:32 healthcare expenditure increased,
40:34 uh,
40:34 government used,
40:35 uh,
40:35 stimulus packages,
40:37 uh,
40:38 uh,
40:38 for,
40:39 um,
40:39 SMEs,
40:40 for,
40:41 uh,
40:42 industry,
40:42 for
40:43 export-oriented industry,
40:45 particularly ready-made garments.
40:47 Um,
40:48 also,
40:48 there was a refinancing project for agriculture for marginalized people,
40:52 farmers,
40:53 low-income professionals.
40:54 Uh,
40:55 interestingly,
40:55 most of this fiscal expansion was backed by the Central Bank,
40:58 Bangladesh Bank,
41:00 by directly increasing high-powered money.
41:03 In addition
41:04 to that,
41:05 cash bank also expand money supply by reducing the policy rates,
41:09 the cash reserve ratio reserve repo rate.
41:12 So the objective was,
41:14 uh,
41:14 you know,
41:15 of this expansion was to stimulate private credit growth,
41:18 which
41:19 unfortunately,
41:20 fortunately did not pick up,
41:22 and that created excess liquidity in the banking system.
41:26 Next slide please.
41:30 Uh,
41:31 good news is we,
41:32 uh,
41:32 you know,
41:32 our vaccination started early February.
41:35 Um,
41:36 already 2% of the pop,
41:38 nearly 2% of the population,
41:39 including me,
41:40 uh,
41:41 already got their first dose.
41:43 Uh,
41:43 vaccination will raise consumers and business confidence,
41:45 and this,
41:46 in addition to the growing pent-up demand,
41:48 will increase
41:49 aggregate demand and stimulate economic activities.
41:52 However,
41:53 there are many practical issues remain to be addressed.
41:56 Nick slide please.
41:59 First of all,
42:00 vaccines are all imported.
42:02 We have excellent,
42:03 uh,
42:03 communi immunization program,
42:05 but vaccines are all imported.
42:07 For COVID is imported from Serra Institute and COEX is giving us some.
42:11 So from these two sources,
42:13 uh,
42:13 you know,
42:13 uh,
42:14 that will cover 30% of the population,
42:17 phase by phase.
42:18 So the plan for the rest 30 to 40% of the population,
42:22 which is what we need to,
42:24 uh,
42:24 you know,
42:24 get herd immunity,
42:26 uh,
42:26 is yet to be shared by the government,
42:28 and,
42:29 but we hear that this will be implemented by 2022.
42:33 Next slide,
42:33 please.
42:37 Um,
42:39 some challenges in vaccination,
42:40 I should address that.
42:42 Uh,
42:42 vaccines travel a long way from the airport to the vaccine points in rural areas,
42:46 from airport to the,
42:47 uh,
42:48 they are taken to the national storage depot in Dhaka,
42:50 from Dhaka to the district,
42:52 and then from district to the Ukujelas.
42:54 And
42:55 mostly,
42:56 open-air rented trucks are used in,
42:58 in,
42:59 in this interdistrict transportation,
43:01 and these
43:01 open-air,
43:02 uh,
43:03 trucks are actually exposed to sunlight.
43:06 And we know that vaccines are a biological product,
43:08 they're very temperature sensitive,
43:10 and any temperature mistake
43:12 spoil,
43:13 uh,
43:13 vaccines.
43:14 Uh,
43:14 I think worldwide,
43:16 um,
43:16 $35 billion US dollar vaccine is spoiled every year.
43:21 And 70% of the population lives in rural areas,
43:23 and they get vaccines at local vaccination points on the day of vaccination.
43:29 So vaccines are taken there,
43:31 uh,
43:31 using local transports like rickshaw van
43:34 by porters in coal boxes.
43:37 And these coal boxes do not have any in-built cooling capacity.
43:42 Unused vaccines are returned to Uujela at the end of the day.
43:46 So this
43:47 transportation are the weakest link in
43:50 Bangladesh vaccine gold chain infrastructure.
43:53 Next up please.
43:55 Uh,
43:56 one minute,
43:57 Franzana.
43:58 Sure,
43:58 I'm wrapping up.
43:59 Next slide please.
44:03 Uh,
44:04 so setting up,
44:04 uh,
44:05 uh,
44:06 countrywide gold chain is necessary,
44:07 and this will create a huge
44:09 fiscal pressure.
44:10 My current research with the University of Birmingham and Harriet Watt is,
44:14 uh,
44:14 you know,
44:15 under UKRI funding.
44:16 Uh,
44:17 we just completed our survey,
44:18 currently analyzing data,
44:19 and,
44:20 uh,
44:20 we'll find out in a couple of months,
44:22 the best options for creating a robust gold chain system in Bangladesh.
44:26 Next slide,
44:26 please.
44:30 Uh,
44:31 about scope of policies,
44:32 there is scope for further fiscal expansion.
44:34 You know,
44:34 fiscal
44:35 deficit is only 3.5 to 5% for a decade.
44:39 We don't have enough resources.
44:41 Tax to GDP ratio is very low,
44:42 but
44:43 government's fiscal management is very good.
44:46 This is a very interesting point.
44:50 Private investment is not picking up,
44:52 so public investment has to continue.
44:55 You know,
44:55 that will create jobs,
44:56 that will,
44:57 um,
44:57 add potential output and increase employment.
45:01 Uh,
45:01 there is excess liquidity and there is concern if it,
45:03 uh,
45:04 if it will create inflation.
45:06 Uh,
45:06 I don't think so,
45:07 and this is why we have,
45:08 uh,
45:08 bumper food production.
45:10 International commodity prices are down,
45:12 oil prices are down,
45:13 so I wouldn't worry about inflation.
45:16 Government can use this excess liquidity for vaccine purchase
45:20 and setting up countrywide gold chain logistics.
45:23 I think that's the last slide.
45:25 Thank you very much for listening.
45:29 Uh,
45:30 excellent.
45:31 Uh,
45:31 thank you.
45:32 Thank you very much.
45:33 And sorry about the,
45:35 uh,
45:36 the glitch,
45:37 the technical glitch,
45:37 but,
45:38 uh,
45:38 we,
45:39 we managed well.
45:40 Uh,
45:40 so we have,
45:42 uh,
45:42 we have now,
45:44 uh,
45:45 finished all the presentations of the first,
45:48 uh,
45:48 uh,
45:48 section.
45:50 And um
45:51 we have,
45:52 uh,
45:53 before the question and answer,
45:54 we have,
45:55 uh,
45:56 uh,
45:56 Professor
45:57 uh Christopher Schneider,
45:59 who will uh um
46:01 give us his,
46:02 his view on this,
46:03 on this first session,
46:05 and then we'll have some time for
46:08 a question and answer.
46:10 Um,
46:11 uh,
46:11 Chris,
46:12 the floor is yours.
46:13 Thank you.
46:14 Thanks,
46:14 Maurizio.
46:15 Um,
46:15 pleasure.
46:16 Uh,
46:16 can you see my slides,
46:17 everyone?
46:19 Uh,
46:19 yes,
46:19 yes,
46:21 um,
46:22 a pleasure to be discussing these papers and
46:24 thank you very much for the invitation to,
46:26 to,
46:26 uh,
46:27 discuss these papers at the conference.
46:28 Um,
46:29 so here I am,
46:30 um,
46:31 I,
46:31 I wanted to make a joke that this is my first time in South Asia,
46:34 but I can't pretend,
46:35 uh,
46:35 to be there.
46:36 I,
46:36 I'm here in Hanover,
46:38 New Hampshire with 1 ft of snow on the ground,
46:40 um,
46:41 but,
46:41 um,
46:42 so I,
46:42 I learned quite a bit about South Asia from these presentations,
46:45 so.
46:45 Um,
46:46 I have these 3 papers to discuss.
46:48 Uh,
46:48 the first from the World Bank team is a general overview across all the countries,
46:51 and we look at specific,
46:53 um,
46:54 policies in Sri Lanka and Bangladesh.
46:57 So I'm going to start and just go in order and talk about the papers,
47:00 um.
47:01 Uh,
47:01 first,
47:02 starting with the World Bank team's,
47:03 um,
47:04 paper,
47:05 it's just a rich repository of,
47:07 of data on
47:08 COVID facts,
47:10 uh,
47:10 deaths,
47:11 infections,
47:12 how much testing is going on,
47:13 the demographics in the population,
47:15 you know,
47:15 the age and comorbidities,
47:17 uh,
47:18 the level of GDP,
47:19 government spending on health,
47:21 you know,
47:21 what the debt capacity is,
47:23 and also the economic harm suffered from COVID.
47:25 And,
47:26 and the World Bank team does this on average and
47:29 also looks at each of the eight South Asian countries.
47:32 It's just replete with data,
47:34 34 figure panels by my count,
47:36 and 16 tables.
47:37 I think this could become a go to reference for external parties
47:41 thinking about COVID-19 vaccination policy in the area,
47:44 and I actually could help inform the countries themselves.
47:48 Um,
47:48 after getting through all the data,
47:49 the heart of the analysis,
47:51 uh,
47:52 goes into three vaccine scenarios.
47:53 So the thought is to target 70% coverage,
47:57 uh,
47:57 the herd immunity threshold.
47:59 Um,
47:59 I,
47:59 I,
47:59 I noticed one of the comments in the chat,
48:01 uh,
48:02 uh,
48:03 said,
48:03 you know,
48:03 well,
48:03 there's some infection,
48:04 and so maybe you don't need to reach the 70% coverage.
48:06 Of course,
48:07 if testing is
48:09 expensive,
48:09 um,
48:10 and,
48:10 and there are new strains,
48:12 actually you may have to go up to the
48:13 70% coverage anyway.
48:15 The assumption is that 20% of it's going to be covered by COAX.
48:19 That's
48:20 the goal of COvax,
48:21 whether COAX actually achieves that goal.
48:23 And then the rest,
48:24 uh,
48:24 so
48:25 50% will be
48:27 covered by the countries,
48:28 and the assumption is 10%
48:30 is self-financed in 2021 and 40% in 2022,
48:33 and the reason there is that
48:35 there's capacity constraints in vaccine,
48:38 and the access to vaccines,
48:40 and so there's only so much that
48:42 developing and middle-income countries can get in 2021.
48:45 And so the assumption is to get 10% then and then fill in the rest in 2022.
48:51 The scenarios really differ only in terms of the
48:53 price that is negotiated for the vaccine deals,
48:56 um,
48:57 and how much distribution can be economized on.
49:02 So there are distribution constraints and funding constraints.
49:06 The distribution constraints,
49:07 the universal health coverage looks low in these countries,
49:13 although if you look on the other screen at the
49:16 DPT 3 vaccination rates are actually quite good in many of the countries,
49:20 not all.
49:20 There's some worries in Pakistan and Afghanistan,
49:23 but in the other countries it's actually greater than the global average.
49:27 Looking down at funding constraints and taking any of the scenarios,
49:31 but looking at the likely scenario,
49:33 um,
49:34 you know,
49:34 is this going to cause fiscal strain?
49:36 Yes,
49:38 um,
49:39 you know,
49:39 looking at the share of GDP,
49:40 it's,
49:40 it's a significant share,
49:42 um,
49:43 0.1%.
49:47 0.14% in 2021 and 0.35% in 2022.
49:52 Um,
49:52 is it an investment worth making?
49:54 Um,
49:54 I think all of the speakers
49:56 have agreed that it's an investment worth,
49:58 worth making,
49:59 um.
50:01 So,
50:02 uh,
50:02 to,
50:02 to,
50:03 you know,
50:03 wrap up,
50:03 uh,
50:04 you could take a glass half empty perspective,
50:06 uh,
50:06 I'm going to take a glass half full perspective here,
50:09 uh,
50:09 on the distributional constraints,
50:11 you know,
50:11 maybe the low UHC is,
50:13 is not the indication.
50:14 Look at the high DPT rates in many of the countries show promise,
50:17 I think,
50:18 and so,
50:19 um,
50:19 there,
50:19 there could be promise here that that won't be,
50:22 that'll be an achievable hurdle.
50:24 Uh,
50:24 of course some of the countries are going to need help.
50:27 Uh,
50:27 in terms of the financial constraints.
50:29 The required expenditures are high,
50:31 but they may not exceed the debt carrying capacity.
50:34 Now,
50:35 of course these countries are already in debt,
50:36 and this is going to add to the debt,
50:38 but there could be some revenue return if you
50:40 speed up opening of the recovery and GDP growth.
50:43 I mean,
50:43 it's not going to necessarily
50:45 pay for itself,
50:46 but even if it doesn't,
50:47 there's of course
50:48 going to be,
50:49 you know,
50:50 help to the
50:51 economy and also the health,
50:53 health benefits.
50:54 Um,
50:55 11 point is that,
50:56 you know,
50:57 the assumption is made in many of these papers that COVAX is
51:00 going to provide the 30 20% of the of the need,
51:05 and,
51:06 you know,
51:06 it's not fully funded yet,
51:08 so
51:09 the need for high income countries to fully fund COAX because these
51:13 low and middle income countries are depending on it
51:16 is crucial.
51:18 Um,
51:19 so that's the World Bank,
51:20 uh,
51:20 team,
51:20 and then moving on to the individual country studies,
51:24 starting with the Sri Lanka
51:25 study,
51:26 um,
51:26 by that Karini talked about.
51:28 Um,
51:29 I,
51:29 I was interested to see just the discussion of the progress or the,
51:34 the,
51:35 of the pandemic in,
51:36 in the country,
51:36 uh,
51:36 it's,
51:37 it's a bit sad of a story there that Sri Lanka
51:40 did so well as an island country holding back the,
51:42 uh,
51:43 the tide of COVID.
51:45 With tough restrictions,
51:46 but then in October,
51:48 the COVID cases surged there,
51:50 um,
51:50 and there was economic harm from the restrictions initially,
51:53 and of course,
51:54 then when the surge hit,
51:56 um,
51:56 more economic harm,
51:57 and so just enormous benefits from,
52:00 from vaccines there.
52:02 The
52:04 team
52:05 looked at a vaccine financing case
52:07 similar to
52:09 the World Bank team,
52:10 so 20% donated,
52:12 and then
52:12 they're looking at an 80% threshold for herd immunity,
52:15 so 60% self-financed.
52:17 The plan is
52:18 to buy AstraZeneca.
52:20 And the suggestion is this is a good investment.
52:22 Um,
52:23 the
52:24 self-financing needed was estimated to be $100
52:27 million
52:28 and it's going to,
52:29 they predict,
52:30 generate a gain in GDP of $112 million so it's going to
52:34 pay for itself in terms of the economy,
52:35 of course it's not all going to come to the government,
52:37 so it may
52:38 increase debt,
52:41 um.
52:42 They suggest financing through sin taxes,
52:45 um,
52:45 whether that can cover it all or not is,
52:47 is a question,
52:48 um,
52:48 if not,
52:49 you know,
52:49 still worth doing,
52:51 um,
52:51 and maybe,
52:52 uh,
52:52 just taking on loans,
52:54 um,
52:54 and it would pay back with the returns,
52:57 um,
52:57 from the economy.
52:58 Um,
52:59 so this team is very optimistic about the case for vaccines,
53:01 uh,
53:01 just a few concerns to add from
53:04 my perspective.
53:06 You know,
53:06 the assumption is that AstraZeneca is going to supply the 60%
53:10 after COVAX.
53:12 I do worry that has AstraZeneca just gone
53:15 to every country and promised the needed capacity,
53:17 and have they overpromised?
53:19 Will the doses be there when Sri Lanka is ready?
53:23 So are there things that the country can do to secure doses now,
53:26 um,
53:27 and,
53:27 you know,
53:28 anything that can be done now,
53:30 a vaccine dose in May 2021 is,
53:32 is worth so much more than a dose in May 2022,
53:36 um,
53:36 there's just so much harm to health,
53:38 mortality,
53:39 and the economy that can be avoided.
53:41 Um,
53:42 and as I mentioned,
53:43 uh,
53:43 syntaxes,
53:44 it's,
53:44 you know,
53:44 in a sense it's might be a free lunch,
53:46 if not,
53:47 Um,
53:48 do you stress the debt carrying capacity?
53:50 I think the answer is,
53:52 yes,
53:52 because of the health and economic returns.
53:54 You know,
53:55 whether to turn to the World Bank and draw on some of the
53:58 $12 billion of loans for distribution and purchases,
54:02 um,
54:02 would be an option.
54:04 Finally turning to uh Farzana's talk uh about
54:08 the work by the Bangladesh Barrack University team,
54:11 um,
54:12 was very interested to learn about the,
54:14 the Bangladesh experience,
54:16 uh,
54:17 how hard it is to socially distance in a crowded country,
54:20 that the informal sector,
54:21 it's just going to be hard for the government to lock that down,
54:24 um,
54:24 so there's only so much that can be done,
54:26 and of course if it is locked down,
54:28 it's going to be terribly painful for people
54:30 on the,
54:30 on the,
54:31 you know,
54:32 close,
54:32 close to low income people.
54:34 Um,
54:34 that said,
54:35 Bangladesh has done relatively well,
54:36 which is disheartening.
54:38 Um,
54:38 why?
54:39 The young population,
54:40 um,
54:41 maybe because their exports were still robust.
54:44 GDP grew by 5% in December 2020,
54:47 I think.
54:48 Here in the United States we love to see a performance like that.
54:52 Um,
54:52 the team argues for macro stimulus and argue for vaccine purchases.
54:57 Um,
54:58 just on the macro
54:59 stimulus side.
55:00 Um,
55:01 you know,
55:02 I'm not a macroeconomist,
55:03 I'm an industrial organization economist,
55:05 but it,
55:05 it seems to me that maybe thinking about things in terms of
55:07 stimulus packages is not necessarily the right way to think about it.
55:11 I don't think we're in
55:12 a Keynesian recession,
55:13 that there's a limit to demand,
55:15 I mean people just don't,
55:16 don't leave their houses,
55:18 and,
55:18 and in fact,
55:18 in some of the distancing and restrictive measures,
55:21 the whole point is to,
55:22 to hibernate the economy,
55:23 so
55:24 maybe we should think about these in
55:25 terms of rescue rather than stimulus packages and
55:28 um.
55:30 That that might be a useful way to think about it,
55:32 um,
55:32 as far as.
55:33 Vaccine purchases,
55:34 I just noticed in the paper this quote that said with the availability of vaccines,
55:38 economic activities will return to normal.
55:40 It's it's a very
55:42 positive note.
55:44 Um,
55:44 of course,
55:45 we'd rather this be early in 2020 rather than late in 2020,
55:49 so speed is of the essence,
55:51 as Hans Timmer said,
55:52 uh,
55:52 just to start us off.
55:54 You know,
55:55 there could be a $30 billion GDP difference to Bangladesh to have the doses
56:00 earlier rather than later.
56:02 Um,
56:02 you know,
56:02 are we sure that the capacity is there to supply the
56:06 needs of Bangladesh?
56:07 Have the suppliers overpromised,
56:08 and the only way that the doses are going to come
56:11 is in a trickle,
56:12 you know,
56:13 toward
56:13 much later than
56:14 folks would want it.
56:15 So
56:16 the recommendation would be to
56:18 try to continue to sign contracts and secure.
56:21 Uh,
56:22 doses as soon as possible
56:24 and try to expand capacity rather than say contract on doses.
56:30 Um,
56:31 and,
56:32 uh,
56:33 Excuse me.
56:37 Um,
56:38 so try to compare,
56:39 try to,
56:39 uh,
56:40 expand,
56:40 uh,
56:41 have contracts that expand capacity for,
56:43 for these countries rather than,
56:45 say,
56:45 buying doses,
56:46 which just finds the countries at the,
56:48 at the end of a queue,
56:49 which is puts you years out in terms of getting your vaccine.
56:53 And that is my last slide.
56:55 So enjoyed,
56:56 enjoyed the papers and just
56:57 very excited to see,
56:59 um,
57:00 the,
57:00 um,
57:01 you know,
57:01 people,
57:01 people thinking along the same lines that this is a good investment and just,
57:06 you know,
57:06 how to facilitate it and,
57:07 and really thinking ahead in terms of the,
57:09 how to get around these distributional constraints with the cold chain and things.
57:13 So thank you very much.
57:16 Thank you.
57:16 Thank you very much,
57:17 uh,
57:17 Chris.
57:18 Uh,
57:19 we're,
57:19 we're running a little late and,
57:22 um,
57:22 so,
57:23 uh,
57:24 I'm gonna eat up a little time in the,
57:27 of the
57:28 Uh,
57:29 break before the next session.
57:31 And,
57:32 uh,
57:32 I,
57:34 so I,
57:34 we have a,
57:35 we have a few,
57:36 a few questions,
57:38 uh,
57:38 that,
57:39 uh,
57:39 came,
57:40 uh,
57:40 through the,
57:41 uh,
57:42 through the chat.
57:43 So,
57:44 let me,
57:44 let me,
57:45 uh,
57:45 go through,
57:46 uh,
57:47 maybe three sets of questions.
57:50 Uh,
57:50 first,
57:51 OK,
57:51 so the first one is,
57:52 uh,
57:53 It's a bit about costs
57:55 and uh it's,
57:57 uh,
57:57 it's to,
57:58 uh,
57:59 probably to all the,
58:00 the panelists,
58:01 all,
58:01 all the questions.
58:02 So if you can answer quickly all of these.
58:04 So the first one is on the cost.
58:06 There is,
58:06 uh,
58:07 there is uh in one sense,
58:09 uh,
58:09 a possibility that the,
58:11 the costs are
58:13 Um,
58:13 uh,
58:14 quite high
58:15 because of reaching the,
58:17 the 70% herd immunity when you consider the fact that,
58:21 uh,
58:22 uh,
58:22 already,
58:23 uh,
58:24 uh,
58:24 these population have high sero prevalences,
58:26 so there are quite a,
58:28 uh,
58:29 A share of people that are already infected or protected.
58:33 Probably you don't need to
58:34 uh vaccinate that many.
58:36 So any reflection on that.
58:38 And the other one is on
58:41 The average cost,
58:42 uh,
58:43 internal cost for,
58:44 for delivering the vaccine that a cat presented,
58:48 though these costs have
58:50 also quite a bit of variation for certain population group based on their location,
58:55 uh,
58:55 etc.
58:56 Uh,
58:57 so if you have any
58:59 ideas of,
59:00 of,
59:01 of that as well,
59:02 would be,
59:02 would be interesting.
59:03 The second set of,
59:06 uh,
59:08 The question is,
59:08 is,
59:09 uh,
59:10 uh,
59:11 is about,
59:11 uh,
59:13 the,
59:13 the fact that,
59:14 that,
59:15 uh,
59:16 we saw for the case of Sri Lanka,
59:19 that there is some
59:21 consideration of rationalization of,
59:23 of taxation,
59:25 uh,
59:26 because of,
59:26 of the financing constraint.
59:28 Uh,
59:29 uh,
59:30 is there,
59:31 is there any other
59:33 Is this,
59:33 is this done in a context of
59:37 just quickly finding some
59:39 uh ways to increase revenues or is there a reflection
59:44 of a more long-term
59:47 uh changing of,
59:48 of the tax structure?
59:50 Similarly,
59:51 uh,
59:52 for Bangladesh,
59:53 Uh,
59:54 where there is,
59:55 uh,
59:55 there is a sense of
59:58 the one of the weakest link,
59:59 uh we learn
1:00:00 is the transportation.
1:00:03 Uh,
1:00:03 again,
1:00:04 is there a reflection beyond this crisis and
1:00:07 quickly,
1:00:08 uh,
1:00:09 uh,
1:00:10 uh,
1:00:10 delivering the vaccine,
1:00:11 uh,
1:00:11 uh,
1:00:12 to all the parts of the region
1:00:14 of the country?
1:00:15 Is that a reflection of
1:00:17 Uh,
1:00:17 what is,
1:00:18 what can be done long term,
1:00:20 uh,
1:00:21 for,
1:00:21 for the country in improving,
1:00:23 taking advantage in the way of the crisis and,
1:00:26 and improving things.
1:00:27 Um,
1:00:28 so these are,
1:00:29 these are two sets of questions that I can,
1:00:31 uh,
1:00:31 we can start going,
1:00:32 uh,
1:00:32 through the presenter.
1:00:33 Maybe C in the order of the,
1:00:36 of the presentation,
1:00:36 you want to start,
1:00:37 C.
1:00:38 All right,
1:00:39 thanks very much and I'm happy to share a few thoughts
1:00:42 about the idea of aiming to achieve a coverage level of 70% for
1:00:48 for herd immunity and as Doctor
1:00:50 Snyder mentioned as well,
1:00:51 there are many aspects,
1:00:54 many different things to consider here including
1:00:56 Um,
1:00:57 the target population and the target coverage and um
1:01:00 one of the next presentations by Doctor Mullani,
1:01:02 I believe will actually discuss the implications of high sero prevalence in SARS.
1:01:05 So looking forward to additional discussion there.
1:01:08 And some countries actually even before we think about 70% coverage,
1:01:11 some countries are not even aiming for 70% coverage themselves given that more,
1:01:16 also,
1:01:16 you know,
1:01:16 given that more than half the population in countries
1:01:18 like Afghanistan is actually under the age of 18.
1:01:20 Um,
1:01:21 that's kind of the age limit when the vaccine has not really been recommended.
1:01:24 Um,
1:01:25 below that age due to insufficient information so far.
1:01:28 Um,
1:01:28 and as,
1:01:29 as I also mentioned,
1:01:30 we don't really know how long natural immunity from previous
1:01:33 infection will last based on my most recent research,
1:01:36 so,
1:01:36 Um,
1:01:37 the recommendation is,
1:01:38 I think still to try to vaccinate everyone,
1:01:41 but you're exactly right that the 70% is a bit of
1:01:44 an arbitrary um choice for this sort of toy example.
1:01:48 And,
1:01:49 um,
1:01:49 certainly,
1:01:50 um,
1:01:50 I think more of the constraints in the short term will be on the distribution side,
1:01:55 on the production side than actually um in terms of,
1:01:58 you know,
1:01:58 I think we'll be several steps away from reaching 70% in the next
1:02:02 year or two
1:02:03 based on other constraints rather than,
1:02:05 um,
1:02:06 you know,
1:02:06 necessarily uh trying to uh
1:02:09 trying to reach that sort of that level.
1:02:10 So,
1:02:11 um,
1:02:11 I'll I'll,
1:02:12 uh,
1:02:12 many,
1:02:12 many different factors that are constantly changing um and well take
1:02:16 the point about um 70% being a pretty arbitrary level.
1:02:20 Thanks.
1:02:22 Thank you,
1:02:23 Kurt.
1:02:23 Uh,
1:02:24 Irene,
1:02:25 you have uh any reflections?
1:02:31 Hi,
1:02:32 um,
1:02:32 yeah,
1:02:32 so I'll just answer the question,
1:02:34 uh,
1:02:35 about Sri Lanka and about the kind of the targeted,
1:02:38 um,
1:02:38 tax,
1:02:39 uh,
1:02:39 revenue generating
1:02:41 strategies.
1:02:41 Um,
1:02:42 I think the question was whether these are more sort of
1:02:45 quick things specifically targeted for the vaccine strategy.
1:02:48 Um,
1:02:49 or whether it's kind of a reflection of the broader needs.
1:02:53 So I think it's the
1:02:54 second thing because,
1:02:56 um,
1:02:56 Sri Lanka,
1:02:57 as I mentioned,
1:02:58 is,
1:02:59 has very tight fiscal space and a very,
1:03:01 uh,
1:03:01 low revenue to GDP ratio of just like 10%.
1:03:04 Um,
1:03:05 so this is really a process that we need to get going,
1:03:08 and these,
1:03:09 uh,
1:03:09 suggestions are in the hope that,
1:03:11 um,
1:03:12 at least even,
1:03:13 I mean,
1:03:13 with the extra burden,
1:03:15 uh,
1:03:15 cost burden coming from not just the vaccination strategy,
1:03:18 but from the pandemic at large,
1:03:20 um,
1:03:21 these policies will start kind of rolling out.
1:03:23 So I think definitely not just because of,
1:03:25 of the vaccine strategy,
1:03:26 but in general,
1:03:27 Sri Lanka really needs to,
1:03:28 um,
1:03:29 get going with,
1:03:30 um,
1:03:31 Uh,
1:03:32 looking at its fiscal,
1:03:33 uh,
1:03:33 revenue generating policies a lot more seriously than it is at the moment.
1:03:38 Thank you.
1:03:41 Uh,
1:03:42 thank you very much.
1:03:43 Um,
1:03:44 Fasana,
1:03:45 any
1:03:46 reflections?
1:03:48 Um,
1:03:48 yes,
1:03:49 about,
1:03:49 uh,
1:03:51 I think there was a question about cold chain transportation link.
1:03:54 Well,
1:03:55 um,
1:03:55 the way it is planned,
1:03:56 it's phase by phase,
1:03:58 so probably we will survive,
1:03:59 you know,
1:04:00 until Lupoillas,
1:04:01 but in rural areas,
1:04:02 it will be problematic because,
1:04:04 um,
1:04:05 you know,
1:04:06 We cannot,
1:04:07 if we cannot arrange the vaccination centers in rural
1:04:10 areas,
1:04:10 it will be difficult.
1:04:12 People,
1:04:13 it will be difficult for the people to come to Upujelas,
1:04:15 uh,
1:04:15 to get the vaccination.
1:04:17 And there is no alternative,
1:04:19 uh,
1:04:20 um,
1:04:20 you know,
1:04:20 we have to set up,
1:04:21 uh,
1:04:23 cold chain
1:04:24 logistics for the,
1:04:25 you know,
1:04:25 whole country because
1:04:27 this is not for COVID,
1:04:28 but it's,
1:04:28 it's also for,
1:04:30 uh,
1:04:30 future calamities,
1:04:31 and also we do not have food cold chain.
1:04:34 Um,
1:04:35 in Bangladesh proper food culture chain.
1:04:37 So
1:04:38 this is something we have to do.
1:04:39 Thank you.
1:04:42 Thank,
1:04:43 thank you very much.
1:04:45 Perhaps there is a,
1:04:46 a,
1:04:47 a last question that I can,
1:04:49 uh,
1:04:49 pose to,
1:04:51 uh,
1:04:51 everybody,
1:04:52 uh,
1:04:53 uh,
1:04:55 including,
1:04:55 including us,
1:04:57 and others,
1:04:58 which is about,
1:04:59 uh,
1:05:00 uh,
1:05:00 this,
1:05:01 that has been mentioned a few times,
1:05:03 the
1:05:04 Uh,
1:05:04 high levels of,
1:05:05 of debt services or debt to GDP ratio.
1:05:08 And it's actually Avini that was asking this question,
1:05:12 whether,
1:05:13 whether there is
1:05:15 any discussion,
1:05:16 uh,
1:05:17 on,
1:05:17 on debt relief.
1:05:19 Uh,
1:05:20 anyone
1:05:21 wanna take this as a last,
1:05:23 before we close this,
1:05:24 uh,
1:05:24 session?
1:05:32 Yeah.
1:05:32 Hi.
1:05:32 So,
1:05:32 as far as I know,
1:05:33 there is no,
1:05:34 uh,
1:05:35 specific discussion on,
1:05:36 uh,
1:05:37 using debt relief,
1:05:38 um,
1:05:39 specifically for the vaccine strategy,
1:05:41 but
1:05:41 like I mentioned,
1:05:42 um,
1:05:43 the country is looking at
1:05:44 sort of direct financing options as well.
1:05:47 So this is possibly something to consider on top of the other options.
1:05:52 Thank you.
1:05:53 Uh,
1:05:54 Hans,
1:05:54 uh,
1:05:54 I see you
1:05:55 came on online with your video.
1:05:57 You wanna
1:05:58 say a word.
1:06:02 Yeah,
1:06:03 that was because you mentioned my name,
1:06:05 Maurizio.
1:06:08 Uh,
1:06:09 22 observations there.
1:06:12 First of all,
1:06:13 I want to emphasize what Chris Snyder uh already said.
1:06:17 That even if
1:06:21 the cost-benefit analysis is positive because you gain more GDP
1:06:26 than you pay on vaccinating the people,
1:06:29 that doesn't mean that it is easy for the government to pay for the vaccines
1:06:37 because
1:06:38 The governments will not get all the additional GDP as revenues,
1:06:44 and that means that it will add to the debt.
1:06:49 In the cost benefit analysis from the perspective of the government,
1:06:53 you really have to look also about at the future revenues
1:06:59 that you can
1:07:00 raise,
1:07:01 and because the
1:07:03 revenue base is small in South Asia,
1:07:06 that is a real challenge.
1:07:08 On the debt relief,
1:07:09 I don't think that
1:07:11 Uh,
1:07:12 the cost of the vaccination,
1:07:14 uh,
1:07:15 is,
1:07:15 uh,
1:07:16 another reason to
1:07:17 look at that relief,
1:07:19 uh,
1:07:20 but in general,
1:07:21 uh,
1:07:22 uh,
1:07:22 there are discussions going,
1:07:24 uh.
1:07:25 Uh,
1:07:25 going on about debt relief in South Asia,
1:07:29 because debt levels were already high and the pandemic
1:07:33 has caused,
1:07:34 uh,
1:07:34 obviously enormous economic damage,
1:07:37 which has increased the actual debt of governments,
1:07:41 but also Increased uh
1:07:43 what we call the hidden debt,
1:07:45 the contingent liabilities for the governments,
1:07:49 and,
1:07:49 and so to secure
1:07:51 and sustainable future growth paths,
1:07:54 we need in some countries,
1:07:57 some restructuring of the debt.
1:08:00 That's it for me,
1:08:01 uh,
1:08:01 Mauricio.
1:08:02 Oh,
1:08:02 OK.
1:08:03 Thank you.
1:08:03 Thank you,
1:08:04 answer.
1:08:04 Uh,
1:08:05 so we are,
1:08:06 uh,
1:08:06 we are left with 1 minute of break.
1:08:10 So I'll,
1:08:11 uh,
1:08:11 let's,
1:08:12 let's take it and we'll,
1:08:14 we'll resume,
1:08:15 uh,
1:08:15 shortly with the second,
1:08:17 uh,
1:08:18 session,
1:08:19 uh,
1:08:20 in 1 minute.
1:08:38 OK
1:09:23 OK,
1:09:24 I can,
1:09:24 I can,
1:09:25 um,
1:09:26 I can see that uh
1:09:28 Anup already
1:09:29 uh shared
1:09:31 the screen,
1:09:31 so that's,
1:09:32 that's good.
1:09:32 He's getting,
1:09:33 he's getting prepared,
1:09:34 excellent.
1:09:35 So,
1:09:35 uh,
1:09:36 I think we can,
1:09:37 uh,
1:09:37 we can start.
1:09:39 This was a smooth transition from the
1:09:42 first session to,
1:09:44 uh,
1:09:44 the second session.
1:09:46 And,
1:09:46 uh,
1:09:47 this is,
1:09:47 uh,
1:09:48 as I said,
1:09:49 focused on,
1:09:50 uh,
1:09:50 vaccine allocation and equity
1:09:52 issues.
1:09:53 We have again the same structure,
1:09:55 3.
1:09:56 Uh,
1:09:57 3 presentations,
1:09:58 and
1:10:00 then,
1:10:00 uh,
1:10:01 discuss it,
1:10:01 and then some question and answer.
1:10:03 Uh,
1:10:04 send your questions in the chat,
1:10:06 uh,
1:10:06 box.
1:10:08 And,
1:10:08 um,
1:10:09 uh,
1:10:09 10 minutes each presentation,
1:10:11 we'll warn you
1:10:12 via a message at 5 minutes,
1:10:14 and then I'll,
1:10:15 I'll interrupt quickly when you have 1 minute.
1:10:17 First presentation is on,
1:10:19 uh,
1:10:20 uh,
1:10:21 practically implementable
1:10:23 vaccination plan for South Asia.
1:10:25 Uh,
1:10:26 uh,
1:10:27 which the title now is Vaccine Allocation
1:10:29 Priority Us Disease Surveillance and Economic Data,
1:10:32 and an Application for Tamil Nadu.
1:10:35 Uh,
1:10:35 I hope the floor is yours.
1:10:40 You're,
1:10:41 you're muted and I'm sorry.
1:10:43 Thank you.
1:10:43 Can you hear me?
1:10:45 Uh,
1:10:46 yes,
1:10:47 thank you.
1:10:47 OK,
1:10:48 thank you,
1:10:48 Maurizio.
1:10:49 Uh,
1:10:50 yes,
1:10:50 uh,
1:10:50 so this is a joint work with uh Saj Soman at
1:10:54 University of Chicago,
1:10:55 Sari Ramachandran at UCSD,
1:10:58 Alice Chen and Trias Laktawala who are at US uh USC.
1:11:05 So,
1:11:06 uh,
1:11:06 I'm not gonna give a lot of background on COVID in India.
1:11:10 Uh,
1:11:10 the main thing I want to focus on is the vaccine allocation schedules.
1:11:14 Uh,
1:11:15 so there is a guidance from Ministry of Health,
1:11:18 uh,
1:11:18 that prioritizes healthcare workers,
1:11:20 frontline workers,
1:11:21 and older individuals.
1:11:23 Uh,
1:11:23 the,
1:11:23 uh,
1:11:24 specific age at which they're at expands over time.
1:11:27 Uh,
1:11:27 as the rollout continues.
1:11:29 Um,
1:11:30 so right now,
1:11:30 they're currently at,
1:11:31 uh,
1:11:32 immunizing those that are above 50,
1:11:34 uh,
1:11:35 and people that are 45 to 59 with certain comorbidities.
1:11:38 Um,
1:11:38 but if you look at the guidance document,
1:11:40 uh,
1:11:40 it is broadly,
1:11:41 uh,
1:11:42 emphasizing,
1:11:43 uh,
1:11:43 uh,
1:11:43 after that frontline workers,
1:11:45 uh,
1:11:45 vaccinating oldest first.
1:11:47 Um,
1:11:47 however,
1:11:47 it's There's a little bit of,
1:11:49 of vagueness in the,
1:11:50 uh,
1:11:50 guidance document,
1:11:51 and it tends to give states,
1:11:53 uh,
1:11:53 generic flexibility to prioritize groups
1:11:55 depending on prevalence.
1:11:57 What we want to do is,
1:11:58 uh,
1:11:59 look at a number of different vaccine allocation plans and see
1:12:01 if this is the right plan or there are better ones,
1:12:05 uh,
1:12:05 and also get a sense of what the value of vaccination is,
1:12:09 um,
1:12:10 So to do this,
1:12:11 what we do is we,
1:12:12 uh,
1:12:12 marry,
1:12:13 uh,
1:12:13 epidemiological model,
1:12:15 uh,
1:12:15 very standard econo epidemiological model,
1:12:17 uh,
1:12:18 but with a few advantages.
1:12:19 First is that it uses,
1:12:20 uh,
1:12:21 uh,
1:12:21 local epidemiological data,
1:12:23 both on contact rates,
1:12:25 on infection rates,
1:12:26 uh,
1:12:26 and on serial prevalence,
1:12:27 and then it marries that with a consumption forecasting model,
1:12:30 uh,
1:12:30 and,
1:12:31 and compares different models of evaluation,
1:12:33 both health-based,
1:12:34 uh,
1:12:35 and,
1:12:35 um,
1:12:36 ones that will be more familiar to economists.
1:12:39 Quickly go through some methods.
1:12:41 Uh,
1:12:41 so let me tell you about the data.
1:12:43 So,
1:12:43 uh,
1:12:43 we have daily death data,
1:12:45 uh,
1:12:45 by age and district,
1:12:46 uh,
1:12:47 from the state itself,
1:12:48 uh,
1:12:48 including features of the individuals that,
1:12:50 uh,
1:12:51 have,
1:12:51 um,
1:12:52 both gotten the disease,
1:12:53 uh,
1:12:53 and,
1:12:54 uh,
1:12:54 have died.
1:12:55 Uh,
1:12:55 we have a new serum prevalence survey that we finished in October,
1:12:59 November with the state,
1:13:00 uh,
1:13:01 26,000 people.
1:13:02 Representative at the district level.
1:13:04 We also borrow from the Luxman Iron Science article contact
1:13:08 rates from uh contact tracing for AP and Tamil Nadu,
1:13:12 uh,
1:13:12 and then for economic data,
1:13:14 we have,
1:13:14 uh,
1:13:15 functionally,
1:13:15 uh,
1:13:16 monthly income data
1:13:18 from CPHS,
1:13:19 uh,
1:13:19 which is the Consumer Pyramids household survey from CMIE,
1:13:22 uh,
1:13:23 in Tamil Nadu,
1:13:24 that's about 11,000 households.
1:13:27 We marry that with a
1:13:28 uh SIRD model.
1:13:30 It's specific to districts,
1:13:32 uh,
1:13:33 and then within districts,
1:13:34 there's,
1:13:35 uh,
1:13:35 seven age groups that interact.
1:13:37 Uh,
1:13:38 we use the Luxme and Nxmina and,
1:13:40 uh,
1:13:40 contact matrix,
1:13:41 uh,
1:13:41 to figure out that interaction.
1:13:43 We shut down more migration to make this a feasible,
1:13:46 uh,
1:13:46 one to simulate.
1:13:47 We estimate mortality rates,
1:13:49 uh,
1:13:49 directly from the data.
1:13:51 We estimate reproductive rates also from the data going all the way up to,
1:13:55 uh,
1:13:55 late December,
1:13:56 uh,
1:13:57 and then we,
1:13:58 uh,
1:13:58 simulate this model.
1:13:59 And we project it out.
1:14:01 Now the key thing to remember about this model is,
1:14:03 it's an SIRD model,
1:14:04 except that,
1:14:05 uh,
1:14:05 each of these bins,
1:14:07 uh,
1:14:07 gets vaccinated at a rate that we're gonna vary,
1:14:10 uh,
1:14:10 and then we allow vaccine efficacy to be less than perfect.
1:14:12 We're gonna choose 70% to match,
1:14:14 uh,
1:14:14 the AZ vaccine,
1:14:16 and these are all groups that are vaccinated
1:14:19 with different degrees of,
1:14:20 uh,
1:14:20 efficacy of the vaccine.
1:14:23 Meaning,
1:14:23 if you're,
1:14:24 for example,
1:14:24 already recovered,
1:14:25 there's no value to the vaccine incrementally.
1:14:28 OK.
1:14:29 We simulate 7 policies,
1:14:30 although I'm going to show a subset,
1:14:32 uh,
1:14:32 no vaccination is our control.
1:14:34 Uh,
1:14:34 then we have 3 priority scheme schemes,
1:14:36 random assignment,
1:14:38 uh,
1:14:38 um,
1:14:39 contact rate prioritization,
1:14:40 which focuses on the groups that have the highest contact rates based on lexin,
1:14:44 uh,
1:14:44 mortality rate prioritization which focuses on the
1:14:46 oldest group working its way down,
1:14:48 and we look at two speeds,
1:14:49 20,
1:14:50 25% of the population
1:14:51 vaccinated per year or 50% vaccinated in terms of number
1:14:55 of doses and you continue until the vaccination process is done.
1:14:59 Uh,
1:14:59 we look at a number of different metrics,
1:15:00 although I'm going to focus on lives saved,
1:15:02 life years saved,
1:15:03 and social value,
1:15:05 uh,
1:15:05 based upon aggregate willingness to pay for the longevity,
1:15:08 longevity and,
1:15:09 and consumption gains implied by vaccination,
1:15:11 uh,
1:15:12 but you can also look at VSL and VSLY.
1:15:15 Uh,
1:15:15 we will then also try to decompose,
1:15:17 uh,
1:15:18 some of,
1:15:18 uh,
1:15:19 some of these,
1:15:19 uh,
1:15:20 values,
1:15:20 uh,
1:15:21 from the social value
1:15:22 using a random assignment benchmark.
1:15:24 We'll try to decompose things into gains due to income and consumption,
1:15:28 uh,
1:15:28 and then we'll,
1:15:29 we'll talk about how you generate aggregate
1:15:31 social demand for the purposes of procurement.
1:15:34 I'm not going to spend a lot of time here,
1:15:35 but basically the valuation method is similar to that found in Murphy and Tel,
1:15:40 uh,
1:15:40 valuing longevity,
1:15:42 uh,
1:15:42 and then we,
1:15:44 uh,
1:15:44 use a specific implementation that you see,
1:15:46 uh,
1:15:46 in Garber and Phelps,
1:15:48 uh,
1:15:48 among others,
1:15:49 uh,
1:15:49 which makes,
1:15:50 uh,
1:15:50 willingness to pay,
1:15:51 roughly speaking,
1:15:52 uh,
1:15:53 a linear multiple
1:15:54 of present value of discounted,
1:15:57 um,
1:15:57 uh,
1:15:58 probability of living times future consumption.
1:16:02 OK.
1:16:03 Last thing on methods,
1:16:04 uh,
1:16:05 we have a consumption forecasting model again
1:16:07 with the outcome variable being household consumption,
1:16:09 uh,
1:16:09 actually being individual consumption,
1:16:11 so that's household consumption then,
1:16:13 uh,
1:16:13 allocated to individuals,
1:16:14 uh,
1:16:15 in the household,
1:16:16 uh,
1:16:16 based on the OECD formula or OECD method.
1:16:19 uh.
1:16:19 Uh,
1:16:19 and then we regress that on cases at the
1:16:22 local and national level to generate a forecasting model,
1:16:25 and then we use the
1:16:26 projections from the EPI model,
1:16:29 uh,
1:16:29 fit to the EPI,
1:16:30 uh,
1:16:30 to the disease data.
1:16:31 Uh,
1:16:31 we use those projections to get projected,
1:16:34 um,
1:16:35 consumption.
1:16:36 So,
1:16:36 let me just quickly go through the results.
1:16:38 The most important thing I want to point out is that the epidemic seems to be waning,
1:16:42 uh,
1:16:42 in Tamil Nadu,
1:16:43 even with recent data.
1:16:44 Uh,
1:16:44 this is,
1:16:45 these are past cases up until,
1:16:47 uh,
1:16:47 January.
1:16:48 Uh,
1:16:49 you see that there's a,
1:16:49 a significant decline.
1:16:51 This is estimated RT.
1:16:53 Uh,
1:16:53 you can see that it's also,
1:16:54 uh,
1:16:54 settled down,
1:16:55 uh,
1:16:56 and for a while up until January was actually a little bit below 1,
1:16:59 but it's around 1 now.
1:17:01 These are projected
1:17:03 log probabilities of death.
1:17:05 We put them on log scale to show you how because they declined so quickly.
1:17:08 So if we wanted to trace them out,
1:17:10 uh,
1:17:10 out to 2022,
1:17:12 uh,
1:17:12 we'd want to put it on a log scale,
1:17:13 but you can see it's a very low probability of death going forward.
1:17:16 This is aggregated across age groups.
1:17:19 Um,
1:17:20 here is,
1:17:21 uh,
1:17:22 if we plotted,
1:17:23 uh,
1:17:23 for different vaccine policy,
1:17:25 uh,
1:17:26 what the,
1:17:26 what our distribution of simulated results
1:17:28 are across 1000 simulations per scenario
1:17:31 of deaths and years of life lost.
1:17:33 This is no vaccination
1:17:35 at 25% of the population.
1:17:37 vaccinated.
1:17:37 This is what happens with the contact rate prioritization,
1:17:40 random assignment,
1:17:41 and mortality rate prioritization.
1:17:43 You can see the mortality rate prioritization,
1:17:45 uh,
1:17:45 is very valuable.
1:17:46 You can also see that as compared to say,
1:17:49 fast random assignment,
1:17:50 it's better to do age-based,
1:17:52 uh,
1:17:53 prioritization.
1:17:54 This is,
1:17:55 uh,
1:17:55 similar results except now,
1:17:56 uh,
1:17:57 denominating years of life lost.
1:18:00 Now,
1:18:00 I'm gonna switch to social value but also provide some more information on this.
1:18:04 So,
1:18:05 in this figure,
1:18:05 we've calculated the social value in the way that I indicated.
1:18:08 These are for select districts
1:18:10 for different age bins,
1:18:12 and this is the distribution,
1:18:14 this is a whisker plot that showed the
1:18:15 distribution of the simulations and the median,
1:18:17 just like in the last figure.
1:18:19 Uh,
1:18:19 and one of the things that you can see is that There's variation across districts,
1:18:23 but the more important thing is that in some districts,
1:18:25 it's going to be the case that you'll want to vaccinate,
1:18:28 uh,
1:18:28 if you just
1:18:29 maximize across age groups and districts.
1:18:32 If you want to uh vaccinate the,
1:18:34 the folks that have the highest value,
1:18:36 sometimes you'll want to vaccinate even younger people in
1:18:38 some districts before you get to the older groups,
1:18:40 uh,
1:18:40 in other districts.
1:18:44 Another interesting feature of this allocation is that even within a district,
1:18:49 you'll typically want to vaccinate if you use a benchmark random assignment
1:18:53 and figure out who has the highest value versus lowest value.
1:18:56 Um,
1:18:56 you will see that you'll want to generally vaccinate people that
1:18:59 are in the 60 to 69 age bin rather than 70.
1:19:02 And this is a figure that shows willingness to pay here,
1:19:05 age bins here,
1:19:06 but also for,
1:19:07 uh,
1:19:08 certain districts.
1:19:09 Uh,
1:19:09 so you can see how the,
1:19:10 the valuations also distributed across districts,
1:19:12 but the key result is that 60 to 69 has higher value.
1:19:16 And then you can plot this over the entire state,
1:19:19 uh,
1:19:19 and get,
1:19:20 for example,
1:19:20 a social demand function for the state to facilitate procurement.
1:19:25 Uh,
1:19:26 one minute,
1:19:27 uh,
1:19:27 Anu.
1:19:28 Thank you.
1:19:28 Perfect.
1:19:29 Um,
1:19:30 OK.
1:19:30 The other thing that you can do with this analysis is,
1:19:33 uh,
1:19:33 decompose the results,
1:19:35 the,
1:19:35 uh,
1:19:35 willingness to pay,
1:19:37 uh,
1:19:37 into the component that's due to improvements in health,
1:19:40 and then the amount that's due to improvements in consumption as disease,
1:19:45 uh,
1:19:45 declines.
1:19:46 Uh,
1:19:47 and the key takeaway is going to be that you value,
1:19:50 a lot of the value or
1:19:51 the vast majority of the value comes
1:19:53 from consumption gains rather than health gains.
1:19:55 So here you see willingness to pay,
1:19:57 but on a log scale,
1:19:58 These are the age bins.
1:20:00 Um,
1:20:00 the dark components are the components that are due to health.
1:20:04 The,
1:20:04 the hollowed-out components,
1:20:06 uh,
1:20:06 the non-filled components are the,
1:20:08 the components that are due to improvements in consumption,
1:20:10 uh,
1:20:11 and you see that there's almost no benefit,
1:20:13 uh,
1:20:13 from health,
1:20:14 uh,
1:20:14 to the health,
1:20:15 uh,
1:20:16 there's
1:20:16 little value to the health benefit for younger populations,
1:20:19 but even in these populations,
1:20:20 it's actually not that great.
1:20:21 The substantial portion of the gains,
1:20:24 and this is log scale,
1:20:25 comes from the consumption benefits.
1:20:28 This is average for Tamil Nadu.
1:20:30 So,
1:20:31 to conclude,
1:20:32 um,
1:20:32 we generally find that age prioritization,
1:20:34 uh,
1:20:35 is an optimal strategy.
1:20:36 Uh,
1:20:37 but if you were within,
1:20:38 within each region,
1:20:39 within each district,
1:20:40 let's say,
1:20:41 uh,
1:20:41 but if you did that,
1:20:41 you actually want to prioritize 60 to 69 1st before even 70.
1:20:45 Now,
1:20:46 it's gonna be the case that if you're willing to relax that
1:20:48 a little bit that you may want to vaccinate some districts before,
1:20:51 uh,
1:20:51 you get to other districts.
1:20:53 Uh,
1:20:53 so younger people even in some districts before other districts.
1:20:55 Um,
1:20:57 AIDS vaccination,
1:20:58 age prioritization has greater value than speed,
1:21:01 uh,
1:21:01 mainly because there's a small number of old people that
1:21:03 are vulnerable and you want to get to them first.
1:21:05 Uh,
1:21:05 and then finally,
1:21:06 a lot of the evaluation comes from consumption.
1:21:09 Uh,
1:21:09 uh,
1:21:10 the health risk is small,
1:21:11 but that health risk seems to have a big effect on consumption
1:21:14 in our forecasting model.
1:21:19 Uh,
1:21:20 great.
1:21:21 Uh,
1:21:21 thank you,
1:21:22 thank you very much.
1:21:23 And apart for this,
1:21:24 uh,
1:21:25 uh,
1:21:26 uh,
1:21:26 intense and fast presentation.
1:21:28 We,
1:21:29 uh,
1:21:29 can move quickly to the next presentation by
1:21:34 Yal Anil uh Shah from,
1:21:36 uh,
1:21:37 uh,
1:21:37 Center for Global Development.
1:21:39 Um,
1:21:41 Uh,
1:21:41 the floor
1:21:42 is,
1:21:43 uh,
1:21:43 yours,
1:21:44 Sarah.
1:21:44 Thank you,
1:21:45 Mauricio,
1:21:46 um,
1:21:46 can you hear me?
1:21:48 Um.
1:21:49 Yes,
1:21:49 we can and we can see your presentation as well.
1:21:52 I'm just going to share.
1:21:54 Great.
1:21:54 Um,
1:21:55 so thank you very much
1:21:56 to,
1:21:57 um,
1:21:57 everyone organizing this,
1:21:58 um,
1:21:59 conference and,
1:22:01 um,
1:22:01 my,
1:22:02 the title of my talk has actually changed a bit and it's a quite a nice follow-on from,
1:22:05 um,
1:22:05 Anoop's,
1:22:06 um,
1:22:07 presentation now actually.
1:22:08 So,
1:22:09 uh,
1:22:09 what I want to talk about is really a study that we've got on
1:22:12 right now,
1:22:12 which is looking at the cost effectiveness of serum prevalence based
1:22:16 COVID vaccine strategies in India.
1:22:19 And this is work that's um
1:22:21 currently being led by quite a few of our colleagues
1:22:23 and it's a unique collaboration involving supply chain modelers,
1:22:26 epidemiologists and health economists.
1:22:28 So we have the Indian Business School,
1:22:29 um,
1:22:30 Imperial College,
1:22:31 we have Doctor Sanit Mandal,
1:22:32 who's an independent consultant,
1:22:34 and also at the Center for Global Development.
1:22:38 And so,
1:22:39 I mean,
1:22:40 I,
1:22:40 I don't want to go into too much background because obviously everyone's heard a,
1:22:43 heard a lot about India,
1:22:44 um,
1:22:45 but
1:22:45 it,
1:22:45 you know,
1:22:46 it it,
1:22:46 it really is the point that
1:22:48 there's a pressing need to vaccinate those most at risk.
1:22:51 Um,
1:22:52 in India,
1:22:52 as I mentioned,
1:22:53 it sounds like the infection has already widely spread.
1:22:57 Um,
1:22:57 but it is heterogeneous in that there is significant variation across herbal,
1:23:02 urban and rural areas.
1:23:04 And so the question becomes of what would be
1:23:06 the optimal way of targeting a given vaccine supply
1:23:10 where it is needed most.
1:23:11 You know,
1:23:11 do you vaccinate only communities below a certain threshold serial prevalence
1:23:16 or those with the lowest serial prevalence?
1:23:18 And that's what our sort of,
1:23:19 that's what's motivating our analysis.
1:23:23 And so our approach at the minute,
1:23:25 I mean,
1:23:25 these are very preliminary results,
1:23:27 um,
1:23:28 and so that's why,
1:23:29 you know,
1:23:29 the slides are,
1:23:30 again,
1:23:31 uh,
1:23:31 we use an illustrative example um
1:23:34 as a case study here.
1:23:35 And here we focus on Uttar Pradesh as a case study,
1:23:38 um,
1:23:39 where,
1:23:39 you know,
1:23:40 across the state,
1:23:40 there is obviously urban and rural settings,
1:23:43 both with different serial prevalence and transmission intensities.
1:23:46 Now,
1:23:47 in India,
1:23:47 we know that um the government has
1:23:49 already started vaccinating essential health workers.
1:23:52 They're looking to vaccinate 30,
1:23:54 and as I mentioned,
1:23:55 the next stage is an age stratified vaccination campaign strategy.
1:24:00 And so
1:24:01 in our modeling,
1:24:02 we assume that there is only enough vaccine
1:24:05 to vaccinate 50% of the over 50 year olds in the state
1:24:09 that we're talking about.
1:24:10 And so our decision space really comes down to,
1:24:13 you know,
1:24:14 how would optimal vaccine allocation depend
1:24:17 on the existing serial prevalence in rural and urban settings.
1:24:21 And to answer this question,
1:24:23 we sort of focus on
1:24:25 epidemiological modeling,
1:24:26 which is a mathematical model of transmission dynamics of SARS-CoV-2.
1:24:30 And we integrate that with supply chain modeling,
1:24:32 which estimates the additional resources
1:24:34 required for COVID vaccine distribution,
1:24:36 and that includes um you know,
1:24:38 HR storage,
1:24:39 distribution costs
1:24:40 too.
1:24:41 Um and that's in addition to routine immunization.
1:24:45 So just a heads up as well that
1:24:47 the results are preliminary and should be considered
1:24:50 within the context of the assumptions made.
1:24:53 And I mean,
1:24:54 I don't want to go into too much detail of um
1:24:57 the epidemiological modeling,
1:24:59 but um it's a pretty standard modeling methodology.
1:25:02 So it's a deterministic compartmental model.
1:25:05 And um similar to ANOs,
1:25:06 we also have stratifications for urban and rural
1:25:09 um different age groups,
1:25:10 comorbidities.
1:25:12 And
1:25:13 for the purpose of estimating the epidemiological impact or benefit,
1:25:17 um,
1:25:17 we do assume
1:25:19 uh the emergence of a second wave in the future.
1:25:22 And as AO has also done,
1:25:23 we model a vaccine that is 70% effective at reducing infection,
1:25:27 and so we want to estimate the total deaths that
1:25:29 will result from any sort of scenario we model.
1:25:34 And so as an example,
1:25:35 um,
1:25:36 you know,
1:25:36 uh,
1:25:37 try to imagine an urban area in this state where,
1:25:40 you know,
1:25:41 serial prevalence of COVID is currently 40%
1:25:44 and rural areas have a serial prevalence of 10%.
1:25:47 And therefore,
1:25:48 there's two
1:25:49 strategies that we may want to think about.
1:25:51 One is a uniform strategy where you vaccinate 50%
1:25:54 of over 50 year olds in both urban and rural areas,
1:25:58 or a low prevalence low zero prevalence strategy where you
1:26:00 only vaccinate over 50 year olds in rural areas,
1:26:03 so about 80% coverage.
1:26:05 And the graph on the right,
1:26:06 on your X axis,
1:26:06 you've got days,
1:26:07 and on the Y axis you've got daily deaths.
1:26:09 Um,
1:26:10 and we're assuming that any vaccination campaign,
1:26:12 whether it be uniform or low,
1:26:14 low low serial prevalence,
1:26:16 occurs within 90 days.
1:26:18 Now,
1:26:18 if no vaccination is to occur,
1:26:20 you can see the blue.
1:26:22 Line that um that comes about,
1:26:24 which is the,
1:26:24 you know,
1:26:25 the second wave that we're talking about.
1:26:29 Now,
1:26:29 if we were to implement a uniform strategy,
1:26:31 you can see how the actual wave shifts and
1:26:35 decreases in size
1:26:36 over time,
1:26:36 and this is obviously
1:26:38 thinking that the uniform strategy would take place within 90 days
1:26:42 before the epidemic.
1:26:45 And if you do a low posterior prevalence strategy.
1:26:48 You can see the results here,
1:26:49 and
1:26:50 if we were to just quantify this.
1:26:52 In comparison to a no
1:26:55 vaccination strategy,
1:26:56 when,
1:26:56 you know,
1:26:56 no vaccination in this age group is conducted,
1:26:59 a uniform strategy result would avert 32% of deaths
1:27:02 and low sero prevalence would be 27% of deaths.
1:27:06 But obviously that is very dependent on serial prevalence within certain areas.
1:27:10 And so in the previous example I just showed you,
1:27:12 we assumed that rural areas have a serial prevalence of 10%.
1:27:16 And urban areas have a serial prevalence of 40%.
1:27:21 And the idea is,
1:27:22 if we fixed rural areas at 10% and we varied the urban serial prevalence,
1:27:26 does your decision change?
1:27:28 And so
1:27:29 you can see the blue line here where urban serial prevalence on the,
1:27:32 on the X axis and percentage of deaths averted on the Y axis.
1:27:36 And you can see
1:27:38 that's a line.
1:27:39 Now,
1:27:39 as soon as we introduce low zero prevalence,
1:27:41 we can see that at high urban sero prevalence,
1:27:44 there is a crossover point where
1:27:46 you may want to start shifting your resources
1:27:48 to a rural strategy or a low sero prevalence strategy.
1:27:52 And obviously there's caveats,
1:27:54 you know,
1:27:54 as I mentioned,
1:27:54 all the assumptions that we,
1:27:55 we,
1:27:56 I had mentioned earlier.
1:27:59 Now,
1:27:59 what we can also do is we can
1:28:01 vary rural serial prevalence and uh you know,
1:28:05 maybe increase rural serial prevalence to 40% rather than 10%.
1:28:08 And does that change
1:28:10 any decision?
1:28:10 And here we find that a uniform strategy is always preferred
1:28:13 when rural serial prevalence is sufficiently high.
1:28:16 And you can see herd immunity kicks in.
1:28:18 A bit later down.
1:28:20 Now,
1:28:21 obviously this all has an impact on supply chain um
1:28:23 and you know,
1:28:24 the distribution and administration.
1:28:25 If you're going to shift
1:28:27 your strategy towards a rural area,
1:28:29 you need to make sure you have the
1:28:30 supply chain capacity and the administration capacity there.
1:28:33 And so that's where the supply chain modeling kicks in,
1:28:35 really,
1:28:35 where,
1:28:36 you know,
1:28:36 the government of India has already stated
1:28:38 that routine immunization will carry on.
1:28:40 And so we developed a mathematical model to estimate the,
1:28:44 the use of transport,
1:28:45 storage,
1:28:45 vaccine administration capacity
1:28:47 due to routine immunization.
1:28:49 And then we model the additional resource requirements
1:28:52 and incremental costs for different COVID vaccine strategies,
1:28:55 and the same scenario really of,
1:28:57 you know,
1:28:57 50% of over 50s,
1:28:59 campaign duration of 90 days,
1:29:01 um,
1:29:01 uniform or low prevalence strategies as well.
1:29:05 And this is based on public.
1:29:08 And
1:29:22 16 stores and then monthly shipments between both
1:29:25 and session wide
1:29:27 shipments and
1:29:28 um.
1:29:30 What I want to show you now is actually
1:29:33 the resource utilization with COVID vaccines.
1:29:35 So
1:29:36 in the previous slide here,
1:29:37 this is basically the resource requirements for routine immunization.
1:29:40 But as soon as you add in
1:29:43 COVID vaccines into routine immunization,
1:29:46 your resource requirements change,
1:29:48 and the,
1:29:49 the,
1:29:49 the red line
1:29:50 is basically 100% capacity.
1:29:53 Of um your,
1:29:55 your system for the distribution and administration of vaccines,
1:29:58 and you can see that as you
1:30:00 introduce,
1:30:01 either with a uniform or a low prevalence strategy,
1:30:04 this has significant impacts on the um capacity of certain things.
1:30:09 So,
1:30:09 you know,
1:30:09 you can see large ILRs,
1:30:11 93% of districts would require additional
1:30:14 resources for large Iceland refrigerators,
1:30:16 vaccinators as well,
1:30:18 A&Ms are basically vaccinators,
1:30:19 you can see that there would need to be additional capacity from somewhere.
1:30:22 And most likely this would have to be an increased cost from,
1:30:25 you know,
1:30:25 the private sector or taken from other parts of the public health system.
1:30:30 And so,
1:30:31 you know,
1:30:31 if we were to,
1:30:32 I mean,
1:30:33 based on all of this,
1:30:34 yep,
1:30:35 I'm just wrapping up as well,
1:30:36 thank you.
1:30:37 And based on all of this,
1:30:38 we can actually calculate the incremental cost of COVID vaccine.
1:30:41 So this is
1:30:42 the cost
1:30:43 above the cost of routine immunization,
1:30:45 and then you can see it,
1:30:46 you know,
1:30:47 with the vaccine,
1:30:47 it's about 221
1:30:50 ₹220
1:30:52 per person.
1:30:54 And so in terms of cost effectiveness for both strategies,
1:30:56 you can see that there's similar conclusions shown as earlier,
1:30:59 whereas loyalty remembrance strategy is more cost
1:31:01 effective than uniform if urban exceeds 60%.
1:31:05 And so as concluding remarks,
1:31:07 um,
1:31:07 you know,
1:31:08 given the vaccination strategy,
1:31:09 we can estimate epidemiological impact,
1:31:11 potential cost.
1:31:13 Our framework is flexible,
1:31:14 you know,
1:31:15 we can look at different populations,
1:31:17 we can look at delayed dosing,
1:31:18 efficacy,
1:31:19 vaccine timing.
1:31:21 We haven't included the healthcare costs yet,
1:31:23 but we plan to.
1:31:24 And,
1:31:25 you know,
1:31:25 the idea is,
1:31:26 can we basically identify a set of heuristics when
1:31:28 we roll out this framework to different states,
1:31:31 um,
1:31:31 and identify heuristics,
1:31:33 you know,
1:31:33 considering collective information across different
1:31:35 geo geographies on zero prevalence.
1:31:38 Um,
1:31:38 and so I'll stop here,
1:31:40 um,
1:31:40 and hand it back to you.
1:31:46 Uh,
1:31:47 thank you very much,
1:31:48 uh,
1:31:49 Yao.
1:31:49 Thank you for
1:31:50 also everyone enjoying my
1:31:52 interruption at,
1:31:53 at one minute so graciously,
1:31:55 uh,
1:31:56 but it's,
1:31:56 it's for the benefit of,
1:31:57 of listening to all these interesting presentations.
1:32:00 So,
1:32:00 uh,
1:32:01 let's,
1:32:01 let's move,
1:32:02 uh,
1:32:02 quickly to
1:32:03 the final presentation of this,
1:32:05 uh,
1:32:06 session,
1:32:07 uh,
1:32:07 from,
1:32:08 uh,
1:32:08 uh,
1:32:08 uh,
1:32:09 uh,
1:32:09 Parha.
1:32:11 Uh,
1:32:11 um.
1:32:13 Mokoa,
1:32:14 uh,
1:32:14 Gi,
1:32:15 sorry about the,
1:32:16 uh,
1:32:17 my bad pronunciation from the Center of,
1:32:19 uh,
1:32:20 for Policy Research,
1:32:22 making COVID,
1:32:23 uh,
1:32:23 or the title has changed here as well,
1:32:25 impediments to universal COVID-19 vaccination.
1:32:28 The,
1:32:29 the floor is yours,
1:32:30 right.
1:32:30 Thank you.
1:32:32 and um
1:32:34 good day to everybody wherever they are
1:32:36 um
1:32:38 there's actually work based on a forthcoming contribution to the UNDP
1:32:41 policy series uh as I'd like to acknowledge that uh support
1:32:45 um so
1:32:46 this is going to be much less technical than the uh than heroes and
1:32:50 ands presentation,
1:32:51 but,
1:32:51 uh,
1:32:52 it's interesting that it focuses on one of the issues that sort of,
1:32:55 uh,
1:32:55 there is going forward.
1:32:57 Uh,
1:32:57 I'm would be quick with this,
1:32:59 so,
1:32:59 um.
1:33:03 Uh,
1:33:03 the,
1:33:03 the operate summary is fundamentally that,
1:33:06 um.
1:33:08 Uh,
1:33:08 you just read the first paragraph,
1:33:10 it is,
1:33:10 um,
1:33:11 in terms of production and capacity,
1:33:13 that's,
1:33:14 uh,
1:33:14 unlikely to be the binding constraint,
1:33:16 uh,
1:33:17 going forward,
1:33:17 and,
1:33:18 uh,
1:33:19 you can see that from the previous work that's been done,
1:33:22 uh,
1:33:22 in this area of the previous presentation that came in today,
1:33:25 uh,
1:33:26 but essentially getting the,
1:33:28 uh,
1:33:28 vaccine into people and more importantly,
1:33:30 uh,
1:33:31 convincing people to get vaccinated might actually be,
1:33:34 uh,
1:33:34 somewhat problematic.
1:33:36 Um,
1:33:37 so,
1:33:37 uh,
1:33:37 broadly speaking,
1:33:38 uh,
1:33:39 I'll quickly zip through this before we,
1:33:41 uh,
1:33:41 get together.
1:33:42 We're looking at,
1:33:43 uh,
1:33:43 on the supply side,
1:33:45 looking at approval,
1:33:45 production and delivery,
1:33:46 and the demand side,
1:33:48 of course,
1:33:48 affordability and acceptability.
1:33:49 Acceptability is actually going to be
1:33:51 one of the key issues going forward.
1:33:53 Uh,
1:33:53 we know that there are a large number of vaccines,
1:33:56 uh,
1:33:56 already in play
1:33:58 and more coming in,
1:33:59 uh.
1:34:00 Announced,
1:34:01 uh,
1:34:02 numbers over here.
1:34:02 The McKinsey report recently reported about,
1:34:05 uh,
1:34:05 the number that the industry is using about 12 billion.
1:34:08 You can see without the Chinese it's about 8 billion here.
1:34:11 So
1:34:11 there's a lot of,
1:34:13 uh,
1:34:13 supply that's
1:34:14 online.
1:34:15 Uh,
1:34:15 the question is,
1:34:16 um,
1:34:17 as,
1:34:18 um,
1:34:19 what was being put together earlier is
1:34:21 whether uh vaccines today versus vaccines the day after tomorrow,
1:34:24 and what difference is that is that in substance.
1:34:27 Uh,
1:34:27 this is,
1:34:28 uh,
1:34:28 a,
1:34:28 a slightly more expanded version of the table that,
1:34:31 uh,
1:34:31 were shown earlier,
1:34:33 and,
1:34:33 uh,
1:34:33 broadly it makes the point that apart from a few countries
1:34:37 for most,
1:34:37 uh,
1:34:38 people to get into the space,
1:34:40 uh,
1:34:40 at the,
1:34:41 uh,
1:34:42 level of about,
1:34:43 uh,
1:34:43 $10
1:34:45 per person,
1:34:45 uh,
1:34:46 which is either the jab,
1:34:48 uh,
1:34:48 Jansen single jab or the,
1:34:50 uh.
1:34:52 AstraZeneca
1:34:54 plus uh some uh
1:34:57 What you call,
1:34:58 um,
1:34:59 delivery costs,
1:35:00 uh,
1:35:00 it's not gonna break the bank,
1:35:01 it's going to be hard,
1:35:03 uh,
1:35:03 but it's not,
1:35:04 uh,
1:35:05 an impossible
1:35:06 fiscal burden.
1:35:08 Uh,
1:35:09 however,
1:35:09 there are other,
1:35:10 uh,
1:35:11 issues,
1:35:11 uh,
1:35:12 on authorization.
1:35:13 We have recently seen South Africa sort of,
1:35:15 uh,
1:35:16 having worries about variants,
1:35:17 and we come,
1:35:17 uh,
1:35:17 back to what choice this makes later.
1:35:20 Uh,
1:35:20 the issue about KOA,
1:35:22 uh,
1:35:22 both the presentations,
1:35:24 uh,
1:35:24 by Anup and Hiro essentially make the,
1:35:27 uh,
1:35:27 point that one needs,
1:35:29 one can think about
1:35:31 prioritizing spatially in a different way depending on
1:35:35 what's happening.
1:35:36 Uh,
1:35:36 in that particular space and what is likely to happen in that particular space,
1:35:40 uh,
1:35:40 we see right now Latin America is in,
1:35:42 uh,
1:35:43 pretty bad shape and therefore,
1:35:45 uh,
1:35:45 you would want to,
1:35:46 uh,
1:35:46 think about whether you want to,
1:35:48 uh,
1:35:49 prioritize
1:35:49 geographies in that space,
1:35:51 uh,
1:35:52 instead of,
1:35:53 uh,
1:35:54 perhaps other,
1:35:55 uh,
1:35:55 countries which,
1:35:56 uh,
1:35:56 may be in a much more comfortable situation right now.
1:35:59 Uh,
1:35:59 the other issue that would sort of come through the,
1:36:01 the logistics part we're now thinking of essentially putting.
1:36:05 Uh,
1:36:05 stuff in place,
1:36:06 uh,
1:36:07 but there's going to be a large issue with the
1:36:09 waste disposal story which might also be
1:36:11 something that one needs to start thinking about,
1:36:13 uh,
1:36:13 in particular cases.
1:36:15 There are issues of course with respect to indemnity which has become a big issue,
1:36:18 let's say for example,
1:36:19 in Argentina.
1:36:20 Uh,
1:36:21 but,
1:36:21 uh,
1:36:22 these are,
1:36:22 again,
1:36:23 uh,
1:36:24 uh,
1:36:24 the,
1:36:24 these are all little details that would need to be ironed out if you really want to,
1:36:29 uh,
1:36:29 make sure that the flow of,
1:36:31 uh,
1:36:31 vaccines is smooth,
1:36:32 uh,
1:36:32 going forward,
1:36:33 and,
1:36:33 uh,
1:36:34 organizations,
1:36:35 international organizations have the convening part to be able to,
1:36:38 uh,
1:36:39 negotiate these between firms,
1:36:41 uh,
1:36:42 and countries going forward.
1:36:43 COVAX has already done this,
1:36:44 and maybe it needs to be expanded.
1:36:47 So,
1:36:47 uh,
1:36:47 if you look at the broad,
1:36:49 uh,
1:36:49 stories,
1:36:49 uh,
1:36:50 you're looking at,
1:36:51 uh,
1:36:52 a situation where,
1:36:53 uh,
1:36:54 broadly successful,
1:36:56 uh,
1:36:56 national regulatory processes have been extremely accommodative,
1:36:59 uh,
1:37:00 perhaps too much as some would argue,
1:37:02 uh.
1:37:04 Production doses,
1:37:05 especially you see the daily news reports which essentially say that
1:37:09 uh
1:37:09 manufacturers who usually compete our
1:37:12 sharing capacity,
1:37:13 getting together,
1:37:14 uh,
1:37:14 either,
1:37:15 uh,
1:37:15 we need to get together or getting together,
1:37:17 uh,
1:37:18 for whatever commercial reasons,
1:37:20 uh,
1:37:20 and,
1:37:21 uh.
1:37:22 The logistics story of course benefits from an absence of
1:37:25 passenger travel which has opened up a fair degree of
1:37:28 uh cargo capacity in that particular.
1:37:31 Uh,
1:37:31 so
1:37:33 But then,
1:37:33 uh,
1:37:34 comes the story as to whether or not
1:37:36 people want to get vaccinated,
1:37:37 and,
1:37:38 uh,
1:37:38 this is the experience we have from the 1st,
1:37:42 6 weeks of,
1:37:43 uh,
1:37:43 India's vaccination.
1:37:44 Uh,
1:37:45 on the left hand side you have a
1:37:47 situation where the numbers of people vaccinated are,
1:37:49 uh,
1:37:49 and frontline workers vary as you can see enormously by state,
1:37:53 uh,
1:37:53 and,
1:37:54 uh,
1:37:54 uh,
1:37:55 these are all people who are offered.
1:37:56 There's no,
1:37:57 there's no supply constraint,
1:37:58 and,
1:37:58 and yet you see,
1:37:59 uh,
1:38:00 very sharp differences across states in the number of.
1:38:03 Uh,
1:38:03 healthcare and frontline workers who have been vaccinated at the end of last month,
1:38:07 and more importantly,
1:38:08 if you look at the,
1:38:09 uh,
1:38:09 right,
1:38:10 uh,
1:38:10 flank is the number of healthcare workers who showed up
1:38:13 to take their second dose,
1:38:15 uh,
1:38:15 after getting their first dose,
1:38:17 and that number is sort of hovering around 2/3 and not moving too much after that.
1:38:21 Uh,
1:38:22 so that's,
1:38:22 so this is one of the issues that one would need to confront,
1:38:25 and these are people who can actually,
1:38:27 uh,
1:38:28 Trace,
1:38:29 uh,
1:38:29 and,
1:38:29 and consequently it would be,
1:38:31 uh,
1:38:32 interesting to see how exactly,
1:38:33 uh,
1:38:33 the
1:38:34 population comes through.
1:38:35 Uh,
1:38:36 the,
1:38:37 uh,
1:38:38 and,
1:38:38 and,
1:38:38 so,
1:38:38 so broadly that's the,
1:38:40 uh,
1:38:41 first issue that we need to sort of,
1:38:42 uh,
1:38:43 start thinking together as to how,
1:38:44 uh,
1:38:45 we're coming forward
1:38:46 now,
1:38:46 uh.
1:38:48 This is where,
1:38:49 uh,
1:38:49 as,
1:38:50 uh,
1:38:50 was mentioned earlier,
1:38:51 we have about 150,000+ deaths,
1:38:54 uh,
1:38:54 11 million plus infections,
1:38:56 uh,
1:38:57 but in countries where the impact has been less severe,
1:38:59 uh,
1:39:00 or in Southeast Asia,
1:39:01 uh,
1:39:01 etc.
1:39:02 or in,
1:39:02 uh,
1:39:02 even in other countries,
1:39:03 what would be the actual
1:39:05 kind of demand,
1:39:06 uh,
1:39:06 is an open question.
1:39:08 Uh
1:39:10 The,
1:39:11 uh,
1:39:11 let's see if I can get done seems to be some issue with,
1:39:13 um,
1:39:14 yeah.
1:39:16 The other decisions,
1:39:17 uh,
1:39:17 broadly speaking for governments now is by now or later,
1:39:20 uh,
1:39:21 because,
1:39:21 uh,
1:39:23 you,
1:39:23 you have a single dose,
1:39:24 double dose story,
1:39:25 and you have an effectiveness of experience story.
1:39:27 Uh,
1:39:28 the second is,
1:39:29 uh,
1:39:30 do you want in terms of extending,
1:39:32 uh,
1:39:32 what England has done,
1:39:33 uh,
1:39:34 do you want to use
1:39:36 a double dose vaccines and just extend intervals,
1:39:38 uh,
1:39:38 substantially,
1:39:39 and,
1:39:39 uh,
1:39:40 as we move the route,
1:39:42 given the fact that people aren't showing up for the second dose,
1:39:44 we may end up having to.
1:39:46 You may end up getting
1:39:47 uh interesting trial data on that particular case
1:39:50 and uh fundamentally what is going to be your core uh
1:39:53 distribution strategy is going to be people to vaccines or vaccines.
1:39:57 Uh,
1:39:58 what you saw from,
1:40:00 uh,
1:40:00 Anno and,
1:40:01 uh,
1:40:01 Hero's presentation is basically reflected here,
1:40:04 uh,
1:40:05 in,
1:40:05 in some sense it gives you the share of cases,
1:40:07 uh,
1:40:08 by districts across India over time,
1:40:10 uh,
1:40:10 and right now about,
1:40:11 uh,
1:40:12 85% of cases are coming in
1:40:14 from about 60 odd districts,
1:40:17 uh,
1:40:17 which is about the top 10% of districts,
1:40:19 and the bottom 50%
1:40:20 have almost no cases.
1:40:23 Uh,
1:40:23 so,
1:40:24 uh,
1:40:25 do you really want to sort of look at a prioritization strategy,
1:40:28 uh,
1:40:28 spatially going forward,
1:40:30 uh,
1:40:30 and if you look at the map on the right,
1:40:32 what you have is a situation where,
1:40:34 uh,
1:40:34 essentially all the,
1:40:36 uh,
1:40:36 the top 10% of the districts now which have,
1:40:38 as I say,
1:40:38 of the cases
1:40:39 are all concentrated more or less in two states and a few localities.
1:40:44 Uh,
1:40:44 so in this context if it makes sense,
1:40:46 uh,
1:40:47 internationally I was talking about Latin America
1:40:49 within India,
1:40:50 uh,
1:40:50 what kind of spatial,
1:40:51 uh,
1:40:52 uh,
1:40:52 strategy makes sense,
1:40:53 and therefore within South Asia,
1:40:54 what kind of.
1:40:55 The first issue is
1:40:57 the spatial privatization is not receiving enough attention,
1:40:59 and I'm glad those two models,
1:41:01 uh,
1:41:02 have come through,
1:41:02 but that's one of the issues.
1:41:04 Uh,
1:41:04 really,
1:41:05 but on the,
1:41:06 at the same time,
1:41:07 if you're going to increase different kinds of segmentation,
1:41:09 it increases costs and how much
1:41:11 vaccination infrastructure has to be in place and,
1:41:14 uh,
1:41:14 up and running,
1:41:15 that's one of the issues that we need to worry about.
1:41:17 And uh in terms of delivery costs,
1:41:20 one of the issues already come up is what
1:41:22 exactly is the additionality that you're coming through,
1:41:24 uh,
1:41:25 given the fact that
1:41:26 uh right now,
1:41:27 for example,
1:41:28 in India,
1:41:28 what has been done was basically on board
1:41:30 a large capacity in the private sector into the,
1:41:33 uh,
1:41:34 uh,
1:41:35 vaccination personnel story,
1:41:37 uh,
1:41:37 and therefore the additional costs in some sense may or may not be great.
1:41:42 Uh,
1:41:42 111 minute a part time.
1:41:43 Yes,
1:41:44 one minute,
1:41:44 right,
1:41:44 absolutely.
1:41:45 So,
1:41:46 uh,
1:41:47 on the vaccines to people,
1:41:48 of course,
1:41:49 uh,
1:41:49 you needed to sort of get,
1:41:51 um,
1:41:52 a doorstep might be too difficult,
1:41:53 but,
1:41:54 uh,
1:41:55 what exactly do you want to do experiments with,
1:41:57 uh,
1:41:58 having large sites versus smaller sites and structures,
1:42:00 and,
1:42:00 and that is something we need to think about going forward is to
1:42:04 because reaching people and
1:42:05 its effect on their,
1:42:06 uh,
1:42:07 willingness to get vaccinated is going to be one of the major issues.
1:42:10 Uh,
1:42:10 and,
1:42:11 uh,
1:42:11 of course,
1:42:12 uh,
1:42:12 here we might have more ability to identify unvaccinated populations.
1:42:16 It's still required local to law
1:42:18 kind of structures.
1:42:19 Uh,
1:42:20 and finally,
1:42:20 on the private sector,
1:42:21 as you can,
1:42:22 uh,
1:42:22 come in to see,
1:42:23 uh,
1:42:23 there's been a large amount of onboarding,
1:42:25 but most of that capacity in the private sector,
1:42:28 about,
1:42:28 uh,
1:42:29 in terms of institutions that have been brought in,
1:42:31 are concentrated in big cities,
1:42:33 but also fortunately in smaller towns,
1:42:36 uh,
1:42:36 and consequently,
1:42:38 uh,
1:42:38 that has been,
1:42:39 uh,
1:42:40 uh,
1:42:41 that has an automatic,
1:42:43 uh,
1:42:44 sort of specialization that's sort of built in simply by the.
1:42:47 Uh,
1:42:47 nature of the,
1:42:48 uh,
1:42:48 availability of facilities going forward,
1:42:51 uh,
1:42:51 the fiscal reasons for the private sector are not something that we're,
1:42:54 uh,
1:42:54 looking forward to this point in time,
1:42:55 but,
1:42:56 uh,
1:42:56 it's delivery reasons that's coming.
1:42:58 Uh,
1:42:59 so in sum,
1:43:00 as I said,
1:43:01 uh,
1:43:01 I think the vaccine is not the binding constraint.
1:43:04 Uh,
1:43:04 deciding on whether to buy now or later is,
1:43:07 uh,
1:43:07 in,
1:43:08 in some sense what you are,
1:43:09 uh,
1:43:09 looking at.
1:43:10 Getting enough people to agree to take the vaccine,
1:43:12 I think is going to be the binding constraint.
1:43:15 Uh,
1:43:15 and then,
1:43:16 uh,
1:43:17 the whole issue of how do we get people to the vaccine and the,
1:43:19 and the various models that have
1:43:21 been,
1:43:21 uh,
1:43:22 got in place,
1:43:22 the role for the private sector,
1:43:24 uh,
1:43:24 and the role for the spatial,
1:43:26 uh,
1:43:26 thing going forward is coming through.
1:43:27 Finally,
1:43:29 uh,
1:43:29 as,
1:43:30 uh,
1:43:30 COVID moves into a more endemic situation,
1:43:33 uh,
1:43:34 currently in India we're seeing about,
1:43:37 uh,
1:43:37 100 deaths a day.
1:43:39 Uh,
1:43:40 what is the level of,
1:43:41 uh,
1:43:41 mortality that
1:43:43 we would take in an endemic situation compared to,
1:43:45 let's say,
1:43:46 other
1:43:46 diseases like tuberculosis,
1:43:48 etc.
1:43:49 uh,
1:43:49 before we decide that this is,
1:43:51 uh,
1:43:51 something that we can live with,
1:43:53 uh,
1:43:53 rather than try to,
1:43:55 uh,
1:43:55 get it down to,
1:43:56 uh,
1:43:56 0.
1:43:57 Thank you.
1:44:00 Uh,
1:44:00 OK.
1:44:01 Thank you very much,
1:44:02 uh,
1:44:03 uh,
1:44:04 uh,
1:44:04 Parha,
1:44:04 uh,
1:44:05 Yal,
1:44:05 and Anu for the
1:44:07 very interesting,
1:44:08 uh,
1:44:09 presentations.
1:44:10 Uh,
1:44:10 let me give
1:44:11 the floor now to our discussion,
1:44:13 uh,
1:44:14 Professor,
1:44:15 uh,
1:44:16 of Economics and International Health
1:44:18 at Harvard University,
1:44:19 uh,
1:44:20 David Channing.
1:44:21 Uh,
1:44:21 the floor is yours.
1:44:22 Thank you.
1:44:24 Uh,
1:44:24 thank you,
1:44:25 Maurizio.
1:44:25 Um,
1:44:26 uh,
1:44:27 I can't share a screen.
1:44:28 Can you allow me to do that?
1:44:33 Uh,
1:44:34 Kunyeing,
1:44:34 can you
1:44:35 help here?
1:44:37 Feel free to double-check the share icon.
1:44:42 And then before you click on the share icon,
1:44:44 please um
1:44:45 open up your PowerPoint in advance,
1:44:48 so you can see the thumbnail and pick from there.
1:44:51 Yeah,
1:44:51 I can,
1:44:52 I have it,
1:44:53 but the share icon won't open.
1:44:57 They
1:45:02 OK,
1:45:03 let me,
1:45:03 uh,
1:45:03 share the presentation
1:45:06 on your behalf.
1:45:07 I can feel free to,
1:45:08 uh,
1:45:09 request me to advance the slide.
1:45:11 Let me do that.
1:45:12 Yeah.
1:45:24 Thank you.
1:45:25 Um,
1:45:27 So,
1:45:27 uh,
1:45:28 you know,
1:45:28 these are 3 very interesting,
1:45:29 uh,
1:45:30 papers.
1:45:31 Uh,
1:45:32 I'm very happy to discuss them.
1:45:33 I'm going to focus on the equity issue.
1:45:35 There's a lot of issues in these papers,
1:45:37 but I think,
1:45:37 uh,
1:45:38 the,
1:45:38 there was an equity issue I'd really like to bring out.
1:45:40 Um,
1:45:41 next slide,
1:45:41 please.
1:45:43 Um,
1:45:44 I'm actually going to discuss them a little bit out of order.
1:45:47 I'm going to start with the paper,
1:45:48 um,
1:45:49 on the cost effectiveness approach,
1:45:52 and then go on to the,
1:45:53 uh,
1:45:53 the second paper,
1:45:54 which is really a sort of cost-benefit approach.
1:45:57 Uh,
1:45:57 and then,
1:45:58 and the third paper.
1:45:59 I would say that I think,
1:46:00 uh,
1:46:00 all three papers are somewhat different from the,
1:46:03 uh,
1:46:03 papers I got,
1:46:04 even over,
1:46:04 uh,
1:46:04 the space of a few days,
1:46:06 I think they've been quite big advances and differences in the papers.
1:46:09 So,
1:46:09 a little bit of what I'm going to say may be out of date,
1:46:11 but I'll,
1:46:11 uh,
1:46:12 I,
1:46:12 I'll try to match what the,
1:46:13 uh,
1:46:13 what the speaker said.
1:46:15 Uh,
1:46:15 next slide,
1:46:16 please.
1:46:18 Um,
1:46:19 so the cost effectiveness paper,
1:46:21 I think,
1:46:22 is a fairly standard,
1:46:24 uh,
1:46:24 cost effectiveness approach.
1:46:26 Uh,
1:46:26 the scenarios are actually slightly different.
1:46:28 The,
1:46:28 the,
1:46:29 um,
1:46:29 The I saw they were about um
1:46:32 uh
1:46:33 different roll-out strategies,
1:46:35 um,
1:46:35 rolling out faster rather than slower.
1:46:37 The current paper is much more about,
1:46:39 um,
1:46:40 a rural versus urban strategy,
1:46:43 um,
1:46:43 based on different zero prevalence and,
1:46:46 uh,
1:46:46 uh,
1:46:47 sort of the natural immunity from having been infected,
1:46:50 uh,
1:46:50 meaning that vaccination is less valuable in those areas.
1:46:55 Um,
1:46:56 but I think it's a,
1:46:56 it's a fairly standard epidemiological model.
1:46:59 Um,
1:46:59 and there are health benefits,
1:47:01 uh,
1:47:01 life years gained,
1:47:02 uh,
1:47:02 on the different scenarios.
1:47:04 Uh,
1:47:05 there are costs,
1:47:06 uh,
1:47:07 of the,
1:47:07 uh,
1:47:07 vaccine.
1:47:09 Um,
1:47:09 I've highlighted here,
1:47:10 uh,
1:47:11 hospitalization.
1:47:12 I think at the moment,
1:47:13 the,
1:47:13 uh,
1:47:14 the healthcare costs,
1:47:15 uh,
1:47:16 avoided are not,
1:47:17 um,
1:47:17 in the model,
1:47:18 but the,
1:47:18 the idea is that they will,
1:47:19 uh,
1:47:20 bring those in.
1:47:22 And then what they get as a bottom line is the cost effectiveness of each strategy,
1:47:28 looking at the life years gained,
1:47:30 the health gains versus the uh the costs of the vaccine.
1:47:35 Uh,
1:47:36 next slide,
1:47:36 please.
1:47:39 Uh,
1:47:39 I,
1:47:40 I,
1:47:40 I think there's a,
1:47:41 it wasn't quite clear what the,
1:47:42 uh,
1:47:43 perspective was,
1:47:44 whether this is a health sector versus societal perspective.
1:47:47 Uh,
1:47:48 there,
1:47:48 there's the idea that some of the hospitalization costs,
1:47:51 the cost savings to the health sector we brought in,
1:47:54 uh,
1:47:54 but will it include all of the,
1:47:56 uh,
1:47:56 out of pocket costs and in many of,
1:47:58 many of the,
1:47:58 uh,
1:47:59 the countries in the region,
1:48:00 the out of pocket costs are actually very substantial for healthcare.
1:48:05 Uh,
1:48:05 there's a set of paribus assumption here.
1:48:08 Basically,
1:48:08 this is a very standard,
1:48:09 uh,
1:48:10 uh,
1:48:10 cost effectiveness analysis.
1:48:12 Uh,
1:48:13 we're doing a,
1:48:13 a,
1:48:13 a health sector policy,
1:48:15 we're getting health benefits,
1:48:16 and there's a cost to the health sector.
1:48:18 But it really,
1:48:19 I think,
1:48:19 misses,
1:48:20 uh,
1:48:20 the bigger question that came out of the,
1:48:22 uh,
1:48:23 first session today,
1:48:24 which is essentially,
1:48:26 um,
1:48:27 uh,
1:48:27 this is not a uh uh uh a cereus parabus,
1:48:30 uh,
1:48:31 approach.
1:48:32 Um,
1:48:33 and essentially,
1:48:34 vaccination is an alternative to lockdown.
1:48:37 It's an alternative to suppression and social distancing.
1:48:40 And so there are going to be very large economic benefits of vaccination.
1:48:44 If we can relax lockdowns and people get back to work,
1:48:47 um,
1:48:48 the the economic benefits may be very big and may
1:48:52 be bigger than the health benefits.
1:48:56 Um,
1:48:56 but there is a struggle and a difficulty
1:48:58 in incorporating economic benefits into cost effectiveness analysis.
1:49:03 The,
1:49:03 um,
1:49:04 uh,
1:49:05 the benefits in those models are,
1:49:08 um,
1:49:09 Uh,
1:49:10 life years gained,
1:49:11 and
1:49:13 the economic benefits and money units and adding them together is difficult.
1:49:17 Uh,
1:49:17 there's a literature around,
1:49:19 uh,
1:49:19 for example,
1:49:20 measles vaccination,
1:49:21 that there are large cognition and schooling
1:49:23 benefits to measles vaccination as well as,
1:49:26 uh,
1:49:26 health benefits,
1:49:27 but that,
1:49:27 that literature sort of struggles with how to value those.
1:49:31 Um,
1:49:32 but I think,
1:49:32 you know,
1:49:32 this is a very good example of an
1:49:35 epidemiological model built into a cost effectiveness,
1:49:38 uh,
1:49:38 in the way that is normally done in the health literature.
1:49:41 Um,
1:49:43 The second paper is,
1:49:45 uh,
1:49:45 uh,
1:49:45 I think the reason I put it,
1:49:47 a second is it really sort of,
1:49:48 uh,
1:49:49 goes further and addresses this question.
1:49:52 And it looks at economic benefits of the policy as well as health benefits.
1:49:55 So I think the epidemiological model is similar.
1:49:58 I think they they differ in a,
1:49:59 in a lot of details,
1:50:01 but I think the,
1:50:01 the basic approach is similar,
1:50:03 uh,
1:50:04 with different cells of different types of people,
1:50:06 some infected,
1:50:06 some not infected,
1:50:07 and transition,
1:50:08 um,
1:50:08 rates between them.
1:50:11 Uh,
1:50:12 but here,
1:50:12 uh,
1:50:14 the,
1:50:14 uh,
1:50:15 the policy,
1:50:15 uh,
1:50:16 uh,
1:50:18 there are,
1:50:18 there are some policy differences.
1:50:20 Um,
1:50:21 uh,
1:50:21 in the paper I had was really this,
1:50:23 uh,
1:50:23 this trade-off between,
1:50:24 uh,
1:50:25 vaccination versus suppression and social distancing,
1:50:28 that the,
1:50:28 when we go to vaccination.
1:50:30 We're going to be able to relax the pressure and social distancing.
1:50:33 I think in the current paper,
1:50:34 there are more,
1:50:34 uh,
1:50:35 there's more detail on different vaccination policies.
1:50:38 But I think the crux of the matter and the
1:50:39 difference from the first paper is really including these economic benefits
1:50:43 from relaxing,
1:50:44 uh,
1:50:44 social distancing.
1:50:47 Uh,
1:50:48 and
1:50:49 relative,
1:50:50 uh,
1:50:50 to no policy,
1:50:51 the gain,
1:50:52 um,
1:50:52 is mainly health.
1:50:54 If you didn't have any policy,
1:50:55 the,
1:50:56 uh,
1:50:56 the vaccination would have uh big health benefits.
1:50:59 But given that you're in a world of suppression and social distancing,
1:51:03 uh,
1:51:03 which has given us quite big health benefits.
1:51:05 The main gain will be from relaxing those policies,
1:51:08 and it'll be mainly an income gain.
1:51:10 Uh,
1:51:11 there's a balance of both,
1:51:11 but I think what the paper shows is that
1:51:13 most of the,
1:51:14 over half the gains,
1:51:15 uh,
1:51:16 they were forecasting from vaccination were coming from,
1:51:19 uh,
1:51:19 income gains.
1:51:21 Uh,
1:51:21 they're also able to talk about externality to others.
1:51:24 Uh,
1:51:24 there's a difference between the private and social willingness to pay,
1:51:28 essentially because
1:51:29 the vaccinated people,
1:51:30 um,
1:51:31 don't,
1:51:31 um,
1:51:33 uh,
1:51:33 have this multiplier effect of,
1:51:35 um,
1:51:36 passing on infection to others.
1:51:38 Uh,
1:51:38 and,
1:51:39 uh,
1:51:39 all of these effects depends on the infection risks,
1:51:42 the numbers are already immune,
1:51:43 uh,
1:51:43 and income levels.
1:51:46 Um,
1:51:47 so next slide.
1:51:49 Um,
1:51:50 but I think that there's an equity issue that is sort of missing from this paper,
1:51:53 and it's a bit worrying.
1:51:55 Um,
1:51:55 it talks about different policies in different
1:51:57 areas due to different infection risks,
1:51:59 but it doesn't really address the issue of heterogeneity by income level.
1:52:04 Uh,
1:52:04 but what the paper implies essentially is
1:52:07 that the rich,
1:52:08 uh,
1:52:08 the better off,
1:52:09 will have much higher demand for vaccine because
1:52:11 they've got a higher willingness to pay.
1:52:13 And there's an assumption in the model
1:52:15 that the social
1:52:16 value of life you're gained is essentially proportional to income or consumption.
1:52:21 So we'd be much,
1:52:22 uh,
1:52:23 society wants to save the lives of richer people,
1:52:25 but not so much those of poorer people.
1:52:28 And that that essentially someone who earns 10 times as much
1:52:31 will have a value of life that is 10 times higher
1:52:34 than someone whose income or consumption is 10 times lower.
1:52:37 Um.
1:52:39 So,
1:52:40 uh,
1:52:40 I think,
1:52:40 you know,
1:52:40 this has been rejected,
1:52:42 you know,
1:52:42 this way of socially evaluating health has been rejected in the health sector.
1:52:46 Uh,
1:52:46 it's common in the economic sector,
1:52:48 and I think there is this enormous tension,
1:52:50 uh,
1:52:51 between the two approaches.
1:52:54 Uh,
1:52:54 I think in terms of,
1:52:55 uh,
1:52:55 analyzing the private demand,
1:52:57 uh,
1:52:58 for vaccine,
1:52:58 I think it's,
1:52:59 it's the right approach.
1:53:00 This is what people will use if they're going to buy the vaccine themselves,
1:53:03 but it's less clear to me it's the
1:53:04 right approach if we're thinking about social evaluations.
1:53:08 Uh,
1:53:09 I would say that the model has a,
1:53:11 uh,
1:53:11 uh,
1:53:11 has a demand for,
1:53:13 uh,
1:53:13 vaccination,
1:53:14 uh,
1:53:14 um,
1:53:15 by individuals.
1:53:16 I would say,
1:53:17 you know,
1:53:17 I would have liked to see,
1:53:18 uh,
1:53:19 maybe some more modeling of endogenous social distancing.
1:53:22 And to what extent is social distancing a luxury good?
1:53:25 Um,
1:53:26 and so,
1:53:26 um,
1:53:27 the rich may be able to afford social distancing more.
1:53:30 It gives them health benefits which are valuable to them,
1:53:32 and the costs may be lower,
1:53:34 um,
1:53:34 because they can,
1:53:35 they can,
1:53:35 uh,
1:53:36 do more,
1:53:36 um.
1:53:37 Uh,
1:53:38 working remotely,
1:53:39 whereas the poor,
1:53:40 uh,
1:53:41 need,
1:53:42 need to work more,
1:53:43 they need the money more and may not be able to work remotely.
1:53:46 And,
1:53:47 and so the,
1:53:47 uh,
1:53:48 the,
1:53:48 um,
1:53:49 the vaccine may be,
1:53:50 be,
1:53:50 be actually more equitable relative,
1:53:53 uh,
1:53:53 to a social distancing,
1:53:55 uh,
1:53:55 strategy.
1:53:56 Um,
1:53:57 but I,
1:53:57 but I think the,
1:53:58 uh,
1:53:59 this equity issue is really key.
1:54:01 Um,
1:54:02 next slide,
1:54:02 please.
1:54:05 Um,
1:54:06 so I think that the,
1:54:07 there's this really key issue about how we value health gains.
1:54:10 Uh,
1:54:11 so the health sector uses cost effectiveness and
1:54:13 basically just adds up the life years gained,
1:54:15 and that was the approach,
1:54:16 uh,
1:54:17 of the flipper.
1:54:18 Uh,
1:54:19 economics uses cost-benefit.
1:54:20 It weights each life year gained by the,
1:54:23 uh,
1:54:23 income or consumption level of the person,
1:54:25 um.
1:54:26 And
1:54:27 I think that does reflect willingness to pay,
1:54:29 but perhaps not social preferences.
1:54:33 Uh,
1:54:33 uh,
1:54:33 next slide.
1:54:37 Um,
1:54:38 you know,
1:54:38 I would actually,
1:54:39 uh,
1:54:39 you know,
1:54:39 push the authors of the second paper,
1:54:42 uh,
1:54:42 to,
1:54:43 uh,
1:54:43 take an alternative approach,
1:54:44 but perhaps,
1:54:45 you know,
1:54:45 um,
1:54:46 not just,
1:54:47 uh,
1:54:47 but not just use a money approach,
1:54:49 but also,
1:54:49 uh,
1:54:50 use,
1:54:51 um,
1:54:51 life years,
1:54:52 uh,
1:54:53 as a metric for valuing,
1:54:54 uh,
1:54:54 welfare gains.
1:54:56 Um,
1:54:57 so,
1:54:57 a rich person is,
1:54:58 is more willing to pay money for vaccination,
1:55:00 but will not be more willing to pay life years.
1:55:02 In fact,
1:55:02 I think the life year gains are similar
1:55:04 to the two groups.
1:55:06 And therefore,
1:55:06 the,
1:55:07 uh,
1:55:07 willingness to pay in life years will be
1:55:09 similar.
1:55:10 Um,
1:55:11 but then,
1:55:11 uh,
1:55:11 rather than convert life years to money,
1:55:13 I think we should value money and convert it to life years.
1:55:16 Um,
1:55:17 and money is going to be much less valuable to the rich.
1:55:19 The rich are not willing to give up very many life years for money.
1:55:23 Um,
1:55:24 and in fact,
1:55:24 the,
1:55:24 the,
1:55:25 the value of money is just one over the willingness to pay for a life year.
1:55:28 It's just the inverse.
1:55:29 Um,
1:55:30 and,
1:55:31 uh,
1:55:31 I think if you take that social perspective,
1:55:33 one minute,
1:55:34 sorry about that.
1:55:34 OK,
1:55:35 if you take that social perspective,
1:55:37 you are going to get very different results,
1:55:38 and I think there's this misapprehension
1:55:40 that the numer doesn't matter,
1:55:42 and it doesn't matter for positive economics,
1:55:44 but it matters enormously for welfare economics.
1:55:47 And I think the welfare rankings will be very different whether you
1:55:51 uh convert things into money unit equivalents or life year equivalents.
1:55:55 But I think it's a central issue on,
1:55:56 on the equity grounds,
1:55:58 uh,
1:55:58 how we value,
1:55:59 value life years and whether we value them
1:56:00 differently for people at different income levels.
1:56:03 Uh,
1:56:03 next slide.
1:56:06 Um,
1:56:08 so on the final paper,
1:56:09 I,
1:56:10 I,
1:56:10 I think I was,
1:56:10 uh,
1:56:11 I think the,
1:56:12 the financing section,
1:56:13 uh,
1:56:14 session earlier today really made this point that the costs of COVID
1:56:18 are going to be,
1:56:19 uh,
1:56:19 very high relative to normal health spending of many of the countries in the region
1:56:23 and may not be feasible.
1:56:26 Uh,
1:56:26 and I think there was a strong case,
1:56:28 we heard about Kovacs.
1:56:29 I think there's a strong case for international financing here.
1:56:33 Uh,
1:56:34 but,
1:56:34 you know,
1:56:35 it's a little bit unclear whether this is an equity or an efficiency argument.
1:56:40 Um,
1:56:41 and I think there's a strong,
1:56:42 um,
1:56:42 efficiency argument.
1:56:44 Uh,
1:56:44 next slide.
1:56:48 So I think the efficiency argument for global
1:56:50 funding for poor countries to help them with vaccination
1:56:54 is essentially an externality argument.
1:56:57 I think uh one way of thinking about this is if a country is fully vaccinated,
1:57:00 there's really no externality.
1:57:02 Um,
1:57:03 they're not going to be affected by what's going on in the rest of the world,
1:57:06 but I think that's not quite right.
1:57:07 And one reason is even in rich countries,
1:57:09 there's vaccine hesitancy,
1:57:11 and so not everyone will be vaccinated,
1:57:12 and so there'll be spillovers from the rest of the world.
1:57:15 Actually I think the major issue
1:57:17 is that if um
1:57:19 some countries don't vaccinate,
1:57:21 and there's large scale COVID infections,
1:57:23 there's gonna be mutation and the emergence of er new vaccine resistant strains.
1:57:28 And I think that we've seen uh that's I think perhaps happening already in Brazil.
1:57:32 And I think there's an enormous cost to
1:57:34 the world if er vaccine resistant strains emerge.
1:57:37 And so I think there's a strong case for
1:57:40 um
1:57:41 subsidizing vaccination internationally,
1:57:43 even by countries that are fully vaccinated
1:57:46 in order to prevent vaccine resistant strains,
1:57:48 and I think that trying to value that aspect
1:57:51 of the externality is going to be very important.
1:57:54 Uh,
1:57:55 thank you.
1:57:58 Uh,
1:57:58 thank you very much,
1:57:59 uh,
1:58:00 uh,
1:58:00 uh,
1:58:01 David,
1:58:01 and,
1:58:02 um,
1:58:03 And for the excellent discussion and um
1:58:06 Uh,
1:58:07 thank you again for everyone,
1:58:09 uh,
1:58:09 uh,
1:58:10 of the presenter.
1:58:11 Uh,
1:58:12 we have,
1:58:12 um,
1:58:14 We have some uh questions from,
1:58:16 uh,
1:58:18 from the chat
1:58:19 and uh
1:58:20 let me,
1:58:21 let me,
1:58:21 uh,
1:58:22 try to group them
1:58:24 and uh
1:58:25 ask them to
1:58:27 the,
1:58:27 uh,
1:58:28 the panelist.
1:58:30 OK.
1:58:30 So,
1:58:31 uh,
1:58:31 perhaps I,
1:58:32 I'll start with um.
1:58:35 With this,
1:58:35 uh,
1:58:35 uh,
1:58:36 echoing the reflections of,
1:58:38 uh,
1:58:39 uh,
1:58:39 David,
1:58:40 uh,
1:58:41 Canning our discussion,
1:58:42 um,
1:58:43 it would be useful to have some,
1:58:45 um,
1:58:46 uh,
1:58:47 additional reflection by all the,
1:58:49 the panelists about,
1:58:50 uh,
1:58:51 uh,
1:58:51 this,
1:58:52 um,
1:58:52 uh,
1:58:53 distributional impact.
1:58:54 We have seen that,
1:58:55 uh,
1:58:56 uh,
1:58:56 the risk of,
1:58:57 uh,
1:58:58 uh,
1:58:58 risk of,
1:58:59 uh,
1:58:59 getting,
1:59:00 uh,
1:59:00 uh,
1:59:01 infected,
1:59:02 uh.
1:59:02 Uh,
1:59:03 across space and across,
1:59:05 uh,
1:59:05 age group is important,
1:59:07 but
1:59:07 what about,
1:59:08 is,
1:59:08 is there any reflection about the,
1:59:10 uh,
1:59:11 uh,
1:59:11 poor versus,
1:59:12 uh,
1:59:12 versus rich?
1:59:13 Uh,
1:59:14 how does,
1:59:14 how can you,
1:59:15 uh,
1:59:15 take into account that?
1:59:17 The
1:59:19 Uh,
1:59:19 the second,
1:59:20 a second set of,
1:59:21 of,
1:59:21 of questions that
1:59:23 comes out and it's been,
1:59:24 uh,
1:59:24 has been
1:59:25 also mentioned by,
1:59:27 by David in this discussion is this,
1:59:28 uh,
1:59:29 uh,
1:59:29 uh,
1:59:30 counterfactual to the,
1:59:32 um,
1:59:32 vaccination.
1:59:33 And,
1:59:34 um,
1:59:35 uh,
1:59:35 I like it very much how
1:59:37 How David put it,
1:59:38 endogenous social,
1:59:40 uh,
1:59:40 social distancing,
1:59:41 in a,
1:59:42 in a way,
1:59:43 uh,
1:59:43 the question is how much can,
1:59:45 uh,
1:59:46 uh,
1:59:46 vaccination be combined
1:59:48 with,
1:59:49 uh,
1:59:49 with,
1:59:49 uh,
1:59:50 some voluntary,
1:59:51 uh,
1:59:52 suppression,
1:59:53 and is this voluntary suppression,
1:59:55 uh,
1:59:55 more than
1:59:56 mandated by the government,
1:59:58 uh,
1:59:58 uh,
1:59:59 impacting more certain groups,
2:00:00 uh,
2:00:00 uh,
2:00:01 uh,
2:00:01 than others.
2:00:02 And,
2:00:02 and,
2:00:03 uh,
2:00:03 so that's,
2:00:04 that's the second,
2:00:05 um,
2:00:06 area.
2:00:07 11,
2:00:11 last on,
2:00:12 on distribution is that,
2:00:13 uh,
2:00:14 Arta mentioned that,
2:00:15 that,
2:00:16 uh,
2:00:16 The,
2:00:17 uh,
2:00:18 one topic that is
2:00:20 beyond South Asia,
2:00:21 that is the distribution across countries,
2:00:24 uh,
2:00:25 which,
2:00:25 uh,
2:00:26 which is,
2:00:26 uh,
2:00:27 uh,
2:00:27 quite,
2:00:28 quite interesting because we're talking about,
2:00:30 uh,
2:00:31 uh,
2:00:31 uh,
2:00:32 something that is a public good that is not really a government at the,
2:00:35 at the global level.
2:00:37 So
2:00:37 any reflection on,
2:00:38 on,
2:00:39 on the allocation across countries is,
2:00:41 is also,
2:00:42 uh,
2:00:42 will be also interesting.
2:00:44 Um,
2:00:46 Uh,
2:00:46 yes,
2:00:47 I think,
2:00:47 uh,
2:00:48 there are some,
2:00:49 uh,
2:00:49 there are some more details on,
2:00:51 on,
2:00:51 on,
2:00:51 uh,
2:00:52 on
2:00:53 single
2:00:53 points,
2:00:54 but let's start with this.
2:00:56 Uh,
2:00:56 so I'll,
2:00:57 I'll give the floor again in the same order.
2:01:00 Uh,
2:01:01 so can you start,
2:01:03 please?
2:01:04 Thank you.
2:01:05 I'll
2:01:06 address two of those issues,
2:01:07 equity and,
2:01:09 uh,
2:01:10 so modeling social distancing,
2:01:12 specifically,
2:01:12 uh,
2:01:12 endogenous social distancing.
2:01:14 So,
2:01:15 on equity,
2:01:15 I think a number of the concerns that David raised,
2:01:17 uh,
2:01:18 can be addressed.
2:01:19 So,
2:01:19 for example,
2:01:20 even in our model,
2:01:21 when you calculate social value,
2:01:22 you could take the average of consumption gains
2:01:25 across all the,
2:01:27 uh,
2:01:27 districts in Tamil Nadu and use a simple,
2:01:29 uh,
2:01:30 as,
2:01:30 uh,
2:01:30 a kind of a single consumption gain value.
2:01:33 Which would be a way to equalize income.
2:01:35 This gets you a little bit closer to the VSLY calculation,
2:01:39 uh,
2:01:39 that we're talking about.
2:01:40 You can do that for any region you want to.
2:01:42 The,
2:01:42 the key is that the tool is pretty flexible in that regard.
2:01:45 Uh,
2:01:45 we chose the way that we did because it's standard in economics as you might expect.
2:01:49 Um,
2:01:49 second is,
2:01:50 um,
2:01:51 I think it's important to note that even with the social value calculation we use,
2:01:55 it's not just wealthy get
2:01:57 valued more.
2:01:58 Um,
2:01:58 that does happen,
2:01:59 but remember,
2:02:00 because we're looking at changes in willingness to pay to be in the
2:02:03 particular,
2:02:04 say,
2:02:04 vaccination policy
2:02:05 versus a no vaccination state,
2:02:07 what you're really interested in is changes in income.
2:02:10 Uh,
2:02:10 and that can vary.
2:02:11 So for example,
2:02:12 we know from the CMIE data that the fall in income was largest amongst,
2:02:16 uh,
2:02:16 daily laborers,
2:02:17 about 90% initially.
2:02:18 Uh,
2:02:18 it's still,
2:02:19 uh,
2:02:19 very much suppressed now,
2:02:21 and so those might be the folks that,
2:02:22 that gain the most.
2:02:23 Um,
2:02:23 it's also interesting to look at what Partha said about A small number of districts,
2:02:27 largely urban,
2:02:28 accounting for a,
2:02:29 a large percentage of the cases,
2:02:31 suggesting,
2:02:32 uh,
2:02:32 assuming that was representative,
2:02:33 then that suggests that a lot of the
2:02:35 health gains are concentrated in the urban areas,
2:02:37 uh,
2:02:37 which happen to be the high income areas too.
2:02:40 So the low income areas,
2:02:41 if you focus on them,
2:02:41 you don't get as many of the health gains.
2:02:43 The last thing I'll say is,
2:02:45 is,
2:02:45 uh,
2:02:45 I want to separate out the normative social
2:02:47 preferences from the empirically observed social preferences.
2:02:50 I'm not sure the empirically observed social preferences
2:02:52 weigh,
2:02:53 uh,
2:02:53 income equally,
2:02:54 uh,
2:02:55 or that is to say weight lives equally across areas.
2:02:57 I think it's probably a blend in India.
2:02:59 Uh,
2:02:59 to me,
2:03:00 from a normative perspective,
2:03:01 I'm always
2:03:01 worried that they weight
2:03:03 income too much,
2:03:03 but it is what is empirically observed.
2:03:06 And on modeling social distancing,
2:03:07 I completely agree.
2:03:09 We do a little bit of con,
2:03:10 uh,
2:03:10 a little bit of this in consumption forecasting cause that's
2:03:12 an all-in model of how consumption responds to disease,
2:03:15 which includes both policy response
2:03:17 and social distancing,
2:03:18 but we don't do it at all in the health modeling.
2:03:20 I think we should.
2:03:21 I think we could target,
2:03:22 for example,
2:03:23 RT
2:03:24 equals 1 and use that as a constraint to model the health response.
2:03:27 I think that would be a nice innovation.
2:03:28 and useful.
2:03:29 Uh,
2:03:29 the last thing I,
2:03:30 I want to point out is a very small thing,
2:03:31 which is even our consumption forecasting
2:03:34 has a limitation in the sense that the extent to which you think
2:03:37 or how you think consumption responds to disease really
2:03:39 depends on what part of last year you modeled.
2:03:41 If you model the first part of the year,
2:03:43 you're going to get a big response because of the
2:03:45 big drop in consumption at the start of the epidemic.
2:03:47 If you focus on the second half of the year,
2:03:49 it's a much softer response.
2:03:52 Uh,
2:03:53 thank you,
2:03:54 Anna.
2:03:55 Uh,
2:03:56 please mute when you don't talk,
2:03:57 and,
2:03:58 uh,
2:03:58 we,
2:03:58 uh,
2:03:59 Ira,
2:03:59 any
2:04:00 reflections?
2:04:01 Uh,
2:04:02 thanks for that,
2:04:02 Mauricio,
2:04:02 and thank you,
2:04:03 um,
2:04:03 David.
2:04:04 Um,
2:04:04 I mean,
2:04:05 Anoop's done a great job in,
2:04:07 um,
2:04:07 sort of dissecting quite a few of those things.
2:04:09 Um,
2:04:10 I guess in terms of
2:04:12 equity,
2:04:12 um,
2:04:14 David's points are well well noted.
2:04:16 Um,
2:04:16 our modeling approach is still quite preliminary that way,
2:04:19 and so we're trying to build in
2:04:21 all of these different issues,
2:04:22 um,
2:04:22 you know,
2:04:23 both equity of vaccine and also equity of healthcare as well,
2:04:26 um,
2:04:27 especially in India.
2:04:28 Uh,
2:04:28 rural areas don't have access to healthcare or even oxygen or these sorts of things,
2:04:32 so we,
2:04:32 we are trying to build in these different constraints.
2:04:35 Um,
2:04:36 with regards to the perspective,
2:04:38 um,
2:04:39 as I,
2:04:39 uh,
2:04:39 I,
2:04:40 I,
2:04:40 I,
2:04:40 I don't think I mentioned it,
2:04:41 but we are trying to take a societal perspective,
2:04:44 um,
2:04:45 and there are obvious obvious limitations to how much we can include,
2:04:48 but again,
2:04:48 well noted on,
2:04:50 um,
2:04:50 everything David has said,
2:04:51 and we'll be taking this back and
2:04:54 including it.
2:04:54 Uh,
2:04:55 within the model.
2:04:56 Now,
2:04:56 um,
2:04:57 I
2:04:57 agree,
2:04:57 I also agree with Anoop regarding social
2:04:59 distancing and the actual comparator as well.
2:05:02 Um,
2:05:03 our approach is very much from an epidemiological and supply chain sense,
2:05:07 and so,
2:05:08 um,
2:05:09 as Anu mentioned,
2:05:10 we can obviously,
2:05:11 you know,
2:05:11 vary,
2:05:12 um,
2:05:12 RT or R00 and,
2:05:14 and look at uh the sensitivity of that as well.
2:05:17 Um,
2:05:17 and again,
2:05:18 uh,
2:05:19 all I can say is these are preliminary results and we're planning
2:05:21 to take this all back and obviously further build our model up.
2:05:26 Uh,
2:05:28 thank you,
2:05:28 thank you,
2:05:28 Raul.
2:05:29 Uh,
2:05:29 I,
2:05:30 I emphasize that even in a few days,
2:05:32 these papers are changing.
2:05:33 So this is,
2:05:34 uh,
2:05:34 this is,
2:05:35 uh,
2:05:35 really,
2:05:36 really on the go.
2:05:37 Uh,
2:05:37 Arthur,
2:05:38 any,
2:05:39 any
2:05:39 reflections?
2:05:45 I agree with the efficiency argument that uh
2:05:49 Uh,
2:05:49 David made and,
2:05:51 uh,
2:05:51 fundamentally it's sort of the implicit assumption behind,
2:05:54 uh,
2:05:55 why I say that,
2:05:56 uh.
2:05:57 Uh,
2:05:57 financing would not be a constraint because the,
2:06:00 uh,
2:06:01 global benefits from actually,
2:06:03 uh,
2:06:04 intervening
2:06:04 is high.
2:06:06 Uh,
2:06:06 however,
2:06:07 the mechanisms of these things take time to churn,
2:06:10 and that's why I think the,
2:06:11 uh,
2:06:12 problem with,
2:06:12 uh,
2:06:13 distribution strategy,
2:06:14 which is essentially built on,
2:06:15 uh,
2:06:16 population,
2:06:17 uh,
2:06:17 perhaps needs a relook,
2:06:18 uh,
2:06:19 given the kind of,
2:06:19 uh,
2:06:20 structure that we're seeing now.
2:06:21 And secondly,
2:06:22 I think we're underestimating the vaccine hesitancy story,
2:06:26 uh,
2:06:26 especially in countries with,
2:06:28 uh,
2:06:28 relatively low levels of,
2:06:30 um,
2:06:32 Uh,
2:06:33 What you call,
2:06:34 um,
2:06:35 uh,
2:06:35 uh,
2:06:36 infection at this point in time,
2:06:38 uh,
2:06:38 and,
2:06:39 uh,
2:06:40 consequently,
2:06:41 uh,
2:06:41 what you do have is a situation where,
2:06:44 uh,
2:06:44 unless you try and address that part of the story,
2:06:47 you might end up having,
2:06:49 uh,
2:06:49 you might actually end up also privatizing,
2:06:51 uh,
2:06:51 another,
2:06:52 uh,
2:06:52 structure in terms of infection,
2:06:53 but also in terms of
2:06:54 where people are actually willing to take the vaccine,
2:06:57 maybe the place where you need to supply more vaccine to make it.
2:07:00 Uh,
2:07:00 and that's true
2:07:01 both within country and,
2:07:03 uh,
2:07:03 across countries,
2:07:05 uh,
2:07:05 going forward.
2:07:06 Thank you.
2:07:10 Uh,
2:07:10 thank,
2:07:10 thank you,
2:07:11 uh,
2:07:11 Parha.
2:07:12 Um,
2:07:13 uh,
2:07:14 while I am,
2:07:15 uh,
2:07:15 uh,
2:07:16 tempted to ask,
2:07:17 uh,
2:07:17 another round of questions,
2:07:19 I,
2:07:19 uh,
2:07:20 because all of this is,
2:07:21 is extremely interesting,
2:07:23 uh,
2:07:23 I think we have,
2:07:25 uh,
2:07:26 already,
2:07:26 uh,
2:07:27 left with just 1.5,
2:07:29 2 minutes from the,
2:07:31 um,
2:07:32 Next,
2:07:33 uh,
2:07:33 uh,
2:07:33 keynote lecture.
2:07:34 So
2:07:35 I'll,
2:07:35 uh,
2:07:36 I'll,
2:07:36 uh,
2:07:37 I'll,
2:07:37 uh,
2:07:37 thank you again,
2:07:38 everybody from the first section,
2:07:40 the second section,
2:07:41 all the presenters,
2:07:42 uh,
2:07:42 and the two excellent discussions.
2:07:44 And,
2:07:45 uh,
2:07:46 let's take one minute
2:07:47 and regroup,
2:07:48 uh,
2:07:49 uh,
2:07:49 uh,
2:07:50 soon for the,
2:07:51 uh,
2:07:52 keynote lecture.
2:07:53 Uh,
2:07:53 thank you all.
2:10:12 OK.
2:10:13 Uh,
2:10:14 welcome back,
2:10:14 uh,
2:10:15 uh,
2:10:16 everyone.
2:10:18 So,
2:10:18 uh,
2:10:19 I,
2:10:20 I think we're ready.
2:10:22 There's a,
2:10:23 there's,
2:10:23 uh,
2:10:24 someone that has the,
2:10:26 OK.
2:10:26 So I think we are ready to start the last,
2:10:29 uh,
2:10:29 uh,
2:10:30 session of today,
2:10:31 first day of our conference.
2:10:33 And
2:10:34 It's a,
2:10:35 it's an honor to have a,
2:10:37 a keynote lecture from,
2:10:40 from Michael Kremer,
2:10:41 which,
2:10:41 uh,
2:10:42 really doesn't need much of an introduction,
2:10:44 but I will try
2:10:45 anyway,
2:10:46 very quickly.
2:10:46 Uh,
2:10:47 uh,
2:10:47 uh,
2:10:48 Professor Kremer has been professor of economics at MIT,
2:10:52 Harvard,
2:10:52 and now at,
2:10:53 uh,
2:10:53 Chicago.
2:10:55 Uh,
2:10:55 as you all know,
2:10:56 he's a,
2:10:57 a Nobel laureate of 2018 together with uh Banner G and,
2:11:01 and,
2:11:01 and Du Flo.
2:11:03 is a recent,
2:11:04 uh,
2:11:04 uh,
2:11:06 research covers
2:11:07 fields of experiments in,
2:11:09 uh,
2:11:09 experimental fields in,
2:11:10 uh,
2:11:10 in education,
2:11:11 health,
2:11:11 water,
2:11:12 uh,
2:11:12 and agriculture in developing countries,
2:11:14 but especially,
2:11:15 uh,
2:11:16 uh,
2:11:16 economics of research and development and innovation.
2:11:19 And vaccines.
2:11:20 Uh,
2:11:21 so that's,
2:11:21 that's really relevant.
2:11:23 He has developed the
2:11:25 advanced market commitment for vaccine to,
2:11:28 to simulate,
2:11:28 uh,
2:11:29 stimulate private investment in vaccine research
2:11:33 and,
2:11:33 uh,
2:11:33 the distribution of vaccines
2:11:35 in the developing world.
2:11:36 So,
2:11:37 uh,
2:11:38 uh,
2:11:38 it's a,
2:11:39 it's a great pleasure to have you,
2:11:41 uh,
2:11:41 present this keynote lecture.
2:11:43 Uh,
2:11:44 the floor is yours.
2:11:46 Uh,
2:11:47 Michael,
2:11:47 thank you.
2:11:51 Great,
2:11:51 thank you very much.
2:11:53 Um,
2:11:54 Uh,
2:11:55 let me see if I can share some,
2:11:56 uh,
2:11:57 share my screen.
2:11:58 Um,
2:12:11 Is the screen being shared?
2:12:14 OK.
2:12:15 Yes,
2:12:15 yes,
2:12:16 we see,
2:12:16 we see your
2:12:18 uh Gmail account now.
2:12:21 Actually,
2:12:22 can I ask,
2:12:22 is Arthur Baker,
2:12:24 well,
2:12:25 On the line,
2:12:26 uh,
2:12:26 is it,
2:12:27 can you do the train
2:12:29 from there?
2:12:29 That would be easier for me.
2:12:33 Or if Arthur Baker's online,
2:12:35 um,
2:12:36 uh,
2:12:37 perhaps Arthur could,
2:12:38 um,
2:12:39 could share them if he's available,
2:12:40 if he's
2:12:41 able to do that.
2:12:44 I'll
2:12:45 I'm still working on it,
2:12:46 and I'll keep,
2:12:47 keep,
2:12:47 uh,
2:12:48 keep going on it.
2:12:49 Maybe,
2:12:50 maybe mine will eventually get up.
2:12:55 It looks like then.
2:12:57 I it's coming,
2:12:58 yes,
2:12:58 we can see it.
2:13:14 OK,
2:13:14 how does that look?
2:13:16 Uh,
2:13:17 very good,
2:13:18 perfect.
2:13:18 We can,
2:13:18 we can see it.
2:13:20 Great.
2:13:21 OK,
2:13:21 thanks very much.
2:13:22 Apologies for the,
2:13:23 uh,
2:13:24 delay on the tech side,
2:13:25 um.
2:13:27 Um,
2:13:28 so I'd like to
2:13:29 talk about,
2:13:30 uh,
2:13:31 the vaccine supply.
2:13:32 Obviously,
2:13:33 that's uh,
2:13:33 just a subset of the,
2:13:35 the larger issues that are involved,
2:13:37 but,
2:13:37 uh,
2:13:38 this is an issue that,
2:13:39 you know,
2:13:40 I've been working on together with a large group of economists.
2:13:43 Uh,
2:13:43 you'll see some of the,
2:13:44 uh,
2:13:45 the,
2:13:45 the people on the left as well as,
2:13:46 uh,
2:13:47 uh,
2:13:47 statisticians with uh expertise in epidemiology.
2:13:52 We recently,
2:13:53 uh,
2:13:53 just a few days ago,
2:13:55 uh,
2:13:55 came out with an article in Science,
2:13:58 and we also have an article that will be in the American Economic Review
2:14:03 papers and proceedings issue.
2:14:04 So,
2:14:05 these are not,
2:14:06 these two articles are
2:14:08 really take a global perspective.
2:14:09 They're not focusing on South Asia in particular,
2:14:13 but,
2:14:13 uh,
2:14:13 we would love to share some of the results and,
2:14:15 and would love to,
2:14:17 uh,
2:14:17 discuss,
2:14:18 uh,
2:14:18 what,
2:14:19 what's,
2:14:19 what's relevant to South Asia.
2:14:23 Um
2:14:26 We're also,
2:14:27 I should say we're also working on a 3rd paper
2:14:29 on the issue of how to best
2:14:32 allocate existing vaccine supplies.
2:14:34 So the first two papers focus on
2:14:37 investments in vaccine in increasing the supply of vaccines,
2:14:41 and the third one is how to use the existing supply more efficiently.
2:14:45 OK.
2:14:46 Um,
2:14:46 I don't seem to be able to advance my slides.
2:14:49 So,
2:14:50 I think,
2:14:51 um,
2:14:52 I think we will probably have to,
2:14:54 um,
2:14:55 see if somebody else can share the slides on my,
2:14:58 my behalf.
2:15:00 Hello,
2:15:00 Michael,
2:15:01 this is Ronald,
2:15:02 um.
2:15:03 Uh,
2:15:04 Kun Ying,
2:15:05 do you want to come in,
2:15:05 or,
2:15:06 yep,
2:15:07 uh,
2:15:07 uh,
2:15:07 let me,
2:15:08 let me,
2:15:08 uh,
2:15:08 share my screen.
2:15:09 I get it.
2:15:10 Thank you.
2:15:17 So,
2:15:17 uh,
2:15:18 each month,
2:15:19 COVID-19 kills around 300,000 people
2:15:23 and reduces global GDP by about $500 billion.
2:15:27 Um,
2:15:27 and I should note that more comprehensive,
2:15:30 uh,
2:15:30 measures of harm are much higher.
2:15:32 So,
2:15:33 uh,
2:15:33 for example,
2:15:34 Cutler and Summers.
2:15:35 An estimate for the US
2:15:38 that includes the value of health,
2:15:39 in fact,
2:15:40 probably doesn't even capture everything because it
2:15:43 doesn't take into account the disruption to education
2:15:46 and the long run impact of that on human capital,
2:15:49 but they estimate $800 billion per month
2:15:52 just for the US.
2:15:54 Um,
2:15:55 so really,
2:15:55 uh,
2:15:56 an order of magnitude higher.
2:15:58 Um,
2:15:58 you know,
2:15:59 in,
2:15:59 in our papers we sort of
2:16:01 assume that total economic costs are,
2:16:03 are twice GDP costs.
2:16:06 Um,
2:16:06 so,
2:16:07 you know,
2:16:07 then,
2:16:08 then you might think that there's,
2:16:09 you know,
2:16:10 globally 1 $1 trillion a month,
2:16:13 uh,
2:16:13 being lost.
2:16:15 And
2:16:16 Accelerating vaccination could help avert those costs,
2:16:20 both the human costs and the economic costs,
2:16:22 more quickly.
2:16:23 And I think it's,
2:16:24 it's immediately apparent from those numbers
2:16:27 that even a small acceleration of vaccination
2:16:30 um generates tremendous
2:16:33 human and economic benefits.
2:16:36 Now,
2:16:36 how can you,
2:16:37 how do you get
2:16:38 acceleration of vaccination coverage?
2:16:41 Well,
2:16:41 they're,
2:16:41 they're.
2:16:42 Really there are 3 elements,
2:16:44 I'm focusing on 2 here.
2:16:46 The first one,
2:16:48 we did some of would have been,
2:16:49 ideally we would have done more,
2:16:51 um,
2:16:51 and that is invest early on.
2:16:53 So
2:16:54 it,
2:16:54 it,
2:16:55 many countries made investments
2:16:58 before we knew
2:16:59 for sure whether the vaccines would work,
2:17:01 while the vaccines were still being tested.
2:17:03 And I think that made a,
2:17:04 made a lot of sense.
2:17:06 The
2:17:07 second element is large scale capacity investment.
2:17:10 So why is large scale capacity investment important?
2:17:14 Well,
2:17:14 roughly speaking,
2:17:16 the time until vaccination is the number of people who need to be vaccinated,
2:17:20 divided by the capacity.
2:17:22 That gives you how many months it's gonna take to do the,
2:17:25 do the vaccination.
2:17:26 Um,
2:17:27 so.
2:17:28 Increasing the capacity,
2:17:30 in some ways it's like you're trying to fill a bucket,
2:17:32 and if you have a narrow diameter pipe,
2:17:34 it's gonna take a long time.
2:17:36 If you have a wide diameter pipe,
2:17:37 you can fill the bucket much faster.
2:17:40 Um,
2:17:40 uh,
2:17:41 having a lot of uh
2:17:42 capacity
2:17:44 to produce,
2:17:44 um,
2:17:45 more vaccines each year
2:17:47 is,
2:17:47 uh,
2:17:47 or each month
2:17:49 is going to,
2:17:50 um,
2:17:50 it's like a,
2:17:51 a wider diameter pipe.
2:17:53 Um,
2:17:54 one thing to note is that's gonna be particularly useful
2:17:58 for the people who are
2:18:00 at the back of the queue,
2:18:02 so to speak.
2:18:02 So
2:18:03 if it,
2:18:04 imagine it was gonna take 2 years to vaccinate everybody in the world,
2:18:08 well,
2:18:08 if we double capacity,
2:18:10 that could be done in 1 year.
2:18:12 That shortens the queue by 1 year for the,
2:18:14 for the people at the back of the queue.
2:18:16 It's shorter,
2:18:17 if you're just one month into the queue,
2:18:19 then it,
2:18:19 it saves you a fortnight.
2:18:21 So
2:18:21 it's a much um
2:18:23 it's,
2:18:23 it's,
2:18:24 this is actually increasing
2:18:26 capacity promotes global equity.
2:18:30 The,
2:18:30 the final element is efficient use of existing vaccine capacity,
2:18:34 and I'll,
2:18:35 I'll discuss that later on in the talk.
2:18:38 Um,
2:18:38 why don't we go on to the next slide?
2:18:44 One thing that our work suggests is that the social value of
2:18:49 early investment in large scale capacity investment is much
2:18:53 greater than the private value to a vaccine manufacturer.
2:18:56 So
2:18:57 if you remember those numbers that I cited on the,
2:19:00 at,
2:19:00 at the beginning on the
2:19:02 um
2:19:02 on the social cost of the epidemic,
2:19:05 um
2:19:06 using those types of numbers,
2:19:08 and those are,
2:19:08 those in turn come from numbers from the World Bank and the IMF and and others,
2:19:13 um,
2:19:13 we estimate the value of additional vaccine capacity,
2:19:17 um.
2:19:18 At,
2:19:19 you know,
2:19:20 between $600 and $1000 per course.
2:19:23 That's
2:19:24 the value of adding on
2:19:26 additional doses to where we are.
2:19:28 Now that
2:19:29 depends a lot on when that's ready.
2:19:30 If we could have it ready by April,
2:19:32 um,
2:19:33 then it would be,
2:19:34 um,
2:19:35 you know,
2:19:35 closer to $1000 per course
2:19:37 to ready by July,
2:19:39 uh,
2:19:39 closer to $600.
2:19:41 But either way,
2:19:42 that dwarfs the price per course
2:19:45 that is,
2:19:45 that vaccine producers are going to make.
2:19:48 And that's depending on the vaccine,
2:19:50 anywhere between $6.40 dollars per course.
2:19:54 So the,
2:19:56 so
2:19:56 now,
2:19:58 society
2:19:59 has made some choices,
2:20:01 um,
2:20:01 and,
2:20:02 you know,
2:20:03 there are many good reasons for this.
2:20:04 To say we're not going to pay
2:20:06 um
2:20:07 the,
2:20:08 the,
2:20:08 uh,
2:20:08 we're not going to pay the full marginal uh value of this to the society.
2:20:12 We're not going to pay all of that to the vaccine producers.
2:20:15 And,
2:20:18 but
2:20:19 what that does mean is that there's a gap,
2:20:21 and while there may be very good reasons for that,
2:20:24 it means there's a gap between
2:20:26 the social value of the vaccine and the purely commercial incentives
2:20:30 to invest in expanding capacity.
2:20:32 So this is a situation where
2:20:34 the
2:20:35 marginal benefit of vaccine capacity is much greater than the marginal
2:20:40 cost of uh uh well,
2:20:42 much greater than the,
2:20:43 the value to the producer.
2:20:44 um
2:20:45 and uh
2:20:46 likely much greater than the marginal cost.
2:20:49 And that means that
2:20:50 we can't necessarily just count on
2:20:53 um
2:20:54 on,
2:20:55 on uh
2:20:56 on the response of the vaccine producers under existing
2:20:59 um
2:21:00 institutions
2:21:01 to
2:21:02 produce the
2:21:03 optimal amount of vaccine capacity.
2:21:06 And there may be a case
2:21:07 uh for,
2:21:08 for
2:21:09 carefully craft crafted public policy.
2:21:12 Next,
2:21:12 when we go on to the next slide.
2:21:17 Um,
2:21:18 so,
2:21:19 there are a number of,
2:21:20 of,
2:21:20 um,
2:21:21 of entities,
2:21:22 national governments,
2:21:24 uh,
2:21:24 like the US or India or
2:21:27 made advanced deals for billions of courses.
2:21:32 And COAX made some deals as well.
2:21:33 The World Bank has put aside $12 billion in financing
2:21:37 for vaccination,
2:21:39 which
2:21:39 can be.
2:21:40 Used for vaccine purchases.
2:21:41 My,
2:21:42 I may be out of date on this,
2:21:43 and I,
2:21:43 I,
2:21:44 I know there are many people from the World Bank,
2:21:46 uh,
2:21:46 at the meeting.
2:21:47 Um,
2:21:47 my impression is that countries
2:21:50 that right now that
2:21:51 $12 billion
2:21:52 that's a substantial amount of that $12 billion
2:21:55 it remains and is available to countries for,
2:21:59 for financing vaccine purchases.
2:22:00 Um,
2:22:02 and
2:22:02 you know,
2:22:03 one of the questions that we've tried to ask in our work
2:22:06 is,
2:22:07 would it be worth it for countries to borrow to finance those vaccine purchases
2:22:12 for beyond the 20% of the population that might be covered by COVAX.
2:22:16 Um,
2:22:17 and,
2:22:18 you know,
2:22:18 generally it looks like it,
2:22:20 it,
2:22:20 it would be.
2:22:21 Um,
2:22:22 the,
2:22:22 uh,
2:22:23 I wouldn't even say generally,
2:22:24 actually,
2:22:25 even for very low income countries,
2:22:27 this looks like a fantastic,
2:22:28 uh,
2:22:29 investment.
2:22:30 Another
2:22:31 question is,
2:22:32 you know,
2:22:32 would further investments in vaccine capacity now,
2:22:35 uh,
2:22:36 be beneficial and
2:22:37 how to structure them most efficiently,
2:22:39 and then,
2:22:40 uh,
2:22:40 um,
2:22:41 how can we use our existing capacity more efficiently
2:22:44 when we go on to the next slide.
2:22:48 OK,
2:22:48 um,
2:22:49 so let me start out with this question of,
2:22:51 of the,
2:22:52 uh,
2:22:52 the value of vaccine capacity,
2:22:54 um,
2:22:55 and then,
2:22:55 um,
2:22:56 then talk about the ways,
2:22:58 um,
2:22:58 how to structure expansions,
2:23:01 contracts for expansion of vaccine capacity,
2:23:03 and,
2:23:03 um,
2:23:04 and then finally,
2:23:05 how to use existing capacity better.
2:23:07 We go to the next slide.
2:23:11 Uh,
2:23:12 we convince again.
2:23:18 OK.
2:23:19 Um,
2:23:20 so,
2:23:21 you know,
2:23:21 if we
2:23:23 There's some rough calculations of the
2:23:26 uh of the value of,
2:23:28 of existing capacity are,
2:23:30 are on this slide.
2:23:31 Um,
2:23:32 you know,
2:23:32 there's,
2:23:33 it's actually a somewhat complicated question to get at
2:23:37 how much capacity we currently have.
2:23:39 Um,
2:23:39 you know,
2:23:40 there have been various announcements,
2:23:41 but there's also been
2:23:43 delays in ability to,
2:23:44 uh,
2:23:45 to,
2:23:46 to produce and.
2:23:46 In some cases,
2:23:47 you know,
2:23:48 we'll take 3 billion courses
2:23:50 as our baseline
2:23:52 with half coming online in January,
2:23:54 half in April.
2:23:55 Um,
2:23:56 um,
2:23:56 in that case,
2:23:57 we estimate that existing capacity
2:24:00 is worth
2:24:01 $17.4 trillion or $5800 per,
2:24:05 per course.
2:24:06 So just enormously valuable investment,
2:24:08 the investments we already made.
2:24:10 Um,
2:24:11 you can then say,
2:24:11 well,
2:24:11 what would be the,
2:24:12 the,
2:24:13 um,
2:24:14 the
2:24:15 impact of,
2:24:16 of expanding this capacity.
2:24:19 Um,
2:24:20 the,
2:24:20 um,
2:24:21 and,
2:24:22 you know,
2:24:22 I think
2:24:23 that,
2:24:24 um,
2:24:25 why don't we,
2:24:25 um,
2:24:26 let me go on to the next slide for that.
2:24:31 So what would be the value of additional capacity?
2:24:34 Um,
2:24:35 well,
2:24:36 As I indicated before,
2:24:38 it depends on,
2:24:39 on,
2:24:40 uh,
2:24:40 on when it's available.
2:24:42 Um,
2:24:43 so
2:24:44 if,
2:24:44 if capacity could be available in,
2:24:48 in,
2:24:48 um,
2:24:49 in April,
2:24:49 we estimate close to $1 trillion of value.
2:24:53 Um,
2:24:54 if it's available in,
2:24:56 in July,
2:24:57 um,
2:24:58 more like,
2:24:59 uh,
2:24:59 uh,
2:25:00 $600 billion.
2:25:03 It,
2:25:03 um,
2:25:03 so that corresponds to anywhere from $1000 to $600
2:25:08 per course,
2:25:08 course of capacity.
2:25:09 I think that,
2:25:10 you know,
2:25:10 why the big gap,
2:25:11 it really highlights the value of speed,
2:25:14 um.
2:25:15 The
2:25:16 and of course this is assuming a $3 billion baseline that would have been higher if we
2:25:21 we have negative shocks to supply and have less available,
2:25:25 would be less
2:25:26 if we have more capacity available,
2:25:28 but still,
2:25:29 even in those more conservative scenarios.
2:25:33 Say we had $4 billion in baseline capacity
2:25:35 and the the benefit only comes available in in July,
2:25:39 the new capacity only comes available then.
2:25:41 Still,
2:25:42 you would get benefits of
2:25:44 roughly $260 per course compared to the price of
2:25:48 $6 to $40 right now.
2:25:50 And the analysis suggests that's,
2:25:52 you know,
2:25:52 good value not just for
2:25:54 high income countries,
2:25:56 but also for LMICs.
2:25:59 So since we're in a situation in which the
2:26:02 social value of additional capacity now would be high,
2:26:05 the question is how can we,
2:26:08 how can we best go about
2:26:09 um trying to obtain that capacity.
2:26:12 If you go to the next slide.
2:26:14 And is it even possible?
2:26:16 So,
2:26:17 you know,
2:26:17 there's debate,
2:26:18 um,
2:26:19 there's um,
2:26:20 you know,
2:26:20 some people will argue that
2:26:22 all feasible capacity is,
2:26:24 is currently being used,
2:26:25 but,
2:26:26 you know,
2:26:26 there could also be opportunities to install
2:26:28 new factories or repurpose existing ones or,
2:26:31 or find new ways to increase yield um
2:26:34 in existing processes or find,
2:26:36 you know,
2:26:36 creative ways to get more raw material supplies.
2:26:40 Now,
2:26:40 you know,
2:26:41 the value of that would be much higher than the price.
2:26:44 So,
2:26:45 Even though the initially available capacity that
2:26:49 you know,
2:26:51 Has been brought into production,
2:26:52 the existing price,
2:26:53 um,
2:26:54 even if that has been used up,
2:26:56 it may be worth
2:26:57 soliciting bids from firms
2:26:59 for capacity expansion to identify possible investments.
2:27:03 And
2:27:04 that's the stuff that we think
2:27:06 makes sense.
2:27:07 You'll notice that I've written that the governments could do this.
2:27:10 This is also something that international organizations could do.
2:27:13 You know,
2:27:13 it's,
2:27:14 it's,
2:27:14 uh,
2:27:14 it depends on the size of the country.
2:27:16 Obviously
2:27:17 South Asia has,
2:27:18 has large enough countries that
2:27:22 perhaps.
2:27:24 Those governments could solicit bids themselves,
2:27:27 um,
2:27:27 but I think if,
2:27:28 if we think about,
2:27:29 um,
2:27:30 some
2:27:31 smaller countries either in the region or
2:27:33 globally,
2:27:34 uh,
2:27:34 it may make sense for international organizations.
2:27:37 It probably does make sense for international
2:27:39 organizations to be soliciting the bids.
2:27:42 Uh,
2:27:42 so that could be,
2:27:43 for example,
2:27:44 Gay or Kovacs
2:27:46 could solicit bids.
2:27:47 Obviously they would need,
2:27:48 um,
2:27:50 uh,
2:27:50 financing lined up to,
2:27:51 to,
2:27:52 to be able to
2:27:53 um.
2:27:54 Uh,
2:27:55 encourage,
2:27:56 uh,
2:27:56 the bids to come in.
2:27:59 Uh,
2:27:59 can we go into the next slide?
2:28:02 How should the contracts be structured?
2:28:04 Well,
2:28:05 if the contracts specify the number of doses without delivery dates,
2:28:09 then,
2:28:09 um,
2:28:10 you know,
2:28:10 producers might just
2:28:12 not expand their capacity
2:28:14 and just add countries to the back of the queue.
2:28:17 And,
2:28:18 you know,
2:28:18 the,
2:28:19 the firm's
2:28:20 incentives in that case to fulfill orders more quickly
2:28:24 would be much less than the social benefits of doing so.
2:28:27 So,
2:28:28 Um,
2:28:30 if you think about this,
2:28:31 it's like hiring a contractor to work on a,
2:28:33 on a home construction project.
2:28:35 Um,
2:28:36 you know,
2:28:36 the contractor
2:28:37 has,
2:28:38 in many cases will come back and say,
2:28:41 I couldn't get the work done in time,
2:28:42 you know,
2:28:43 I'll just do it later.
2:28:44 At that point,
2:28:45 it's very difficult to do anything about it.
2:28:47 Well,
2:28:47 how do you address that?
2:28:48 Well,
2:28:49 in large scale commercial construction contracts,
2:28:52 they're often penalty or bonus clauses for speed.
2:28:56 The issue here is that
2:28:58 the,
2:28:59 um,
2:29:00 you know,
2:29:00 trying to have penalties or bonuses that match the
2:29:04 social value of speed
2:29:05 would require,
2:29:06 you know,
2:29:06 very,
2:29:07 very large penalty or bonus clauses,
2:29:09 and that's what
2:29:12 the level of risk involved uh would,
2:29:14 would,
2:29:14 would uh probably not be acceptable,
2:29:16 um,
2:29:17 since there are factors outside anybody's control which can affect
2:29:20 um
2:29:21 how,
2:29:21 how,
2:29:22 um,
2:29:23 how quickly vaccines can come online.
2:29:25 Um,
2:29:26 I think the,
2:29:27 you might also risk unintended consequences if you had
2:29:30 that,
2:29:31 um,
2:29:31 that type of
2:29:32 very,
2:29:33 very,
2:29:33 um,
2:29:34 if you had massive penalties or bonuses of the
2:29:37 order of
2:29:38 magnitude of hundreds of billions of dollars that we've been talking about.
2:29:41 That's just a,
2:29:42 a non-starter.
2:29:43 So I think what,
2:29:44 what
2:29:45 makes sense is that contracts should include provisions for capacity expansion.
2:29:51 In particular,
2:29:52 it makes sense to
2:29:54 Have companies submit bids of what they need to do to expand their capacity
2:29:59 and then to offer to cover those costs.
2:30:03 Uh,
2:30:03 what do we go to the next slide?
2:30:07 Um,
2:30:10 I think it's going to be important not just to try to increase final capacity,
2:30:15 but also to think about supply chains.
2:30:18 So
2:30:19 we're in a situation in which society has decided
2:30:22 that
2:30:22 we're not going to,
2:30:24 we're gonna have some limits on pricing.
2:30:25 We're not going to have to have
2:30:27 prices reflect the marginal social value.
2:30:30 Um,
2:30:31 and.
2:30:32 In,
2:30:33 in the,
2:30:33 in the middle of the pandemic,
2:30:34 in the middle of an emergency,
2:30:36 uh,
2:30:36 some companies like AstraZeneca have explicitly said
2:30:40 they're doing this on a nonprofit basis.
2:30:43 I think even companies that are doing this,
2:30:45 uh,
2:30:45 haven't made those pledges.
2:30:47 They're aware that if they tried to charge too much,
2:30:49 you know,
2:30:49 they would face a political
2:30:53 blowback.
2:30:54 So.
2:30:55 Now,
2:30:56 as I say,
2:30:56 there may be very good reasons for that,
2:30:58 but we need to think about what are the consequences
2:31:01 uh for the,
2:31:03 For the,
2:31:04 for the system as a whole,
2:31:07 and one important consequence might be for supply chains.
2:31:10 So if there's high demand for vaccine production,
2:31:14 But if it's not possible for the intermediate input producers to
2:31:18 um
2:31:19 to,
2:31:20 to raise
2:31:21 if there uh if there are limits on the extent to which they're,
2:31:23 they can raise prices,
2:31:25 we might not have a sufficient supply of inputs.
2:31:28 So
2:31:29 here's the logic.
2:31:30 You have a large expansion of vaccine capacity,
2:31:32 and we have seen a huge expansion,
2:31:34 much bigger than anybody would have anticipated.
2:31:37 That will cause a spike in demand for inputs.
2:31:40 Now,
2:31:40 meeting that might require a large scale
2:31:43 increase in manufacturing capacity for the inputs.
2:31:46 We need to.
2:31:48 Uh,
2:31:49 Build new factories,
2:31:50 for example.
2:31:51 But if the demand increases temporary,
2:31:54 of course we don't know,
2:31:55 it may well be,
2:31:56 and it seems likely that we'll need
2:31:58 COVID vaccines on an ongoing basis.
2:32:00 But there's at least some risk
2:32:02 you're thinking about building a factory to produce inputs.
2:32:05 There's a risk that you,
2:32:07 that that capacity won't be
2:32:09 used for the next 20 years,
2:32:12 that it'll be idle in the long run.
2:32:14 And this could be a capacity investment that would normally last
2:32:18 20 years and would be amortized over that period.
2:32:20 But if you don't know
2:32:22 that
2:32:23 um you've got a short demand for that period,
2:32:25 then
2:32:26 you might be reluctant to make that investment.
2:32:29 That means
2:32:30 if,
2:32:30 if if the output price is fixed at normal values,
2:32:34 it might be hard to justify that investment commercially.
2:32:37 You know,
2:32:38 what's the solution?
2:32:39 Well,
2:32:39 you know,
2:32:40 there are a number of ways to address this,
2:32:42 um,
2:32:42 but again,
2:32:43 one possible approach would be for public financing
2:32:47 to help support investment in intermediate input capacity.
2:32:51 Again,
2:32:51 companies could submit bids,
2:32:53 say how much it would cost them to increase,
2:32:56 uh,
2:32:56 production of,
2:32:57 you know,
2:32:57 whether it's a bioreactor,
2:32:58 whether it's bioreactors,
2:33:00 whether it's uh
2:33:01 uh delivery devices,
2:33:02 some of these things are,
2:33:03 are.
2:33:04 Gonna be more relevant than others,
2:33:06 uh,
2:33:06 or in fact just,
2:33:08 uh,
2:33:08 inputs and vaccine production.
2:33:10 Um,
2:33:11 the,
2:33:11 um,
2:33:13 companies could submit bids for that,
2:33:14 uh,
2:33:14 how much would it cost to do that,
2:33:16 and then they could,
2:33:16 that could be publicly,
2:33:17 uh,
2:33:18 supported.
2:33:19 Um,
2:33:19 to
2:33:20 enable
2:33:21 rapid capacity expansion for future investment,
2:33:24 for future pandemics,
2:33:25 you know,
2:33:26 it's going to be very important to put these,
2:33:28 uh,
2:33:28 advanced investment in supply chains.
2:33:30 I think
2:33:31 it's really,
2:33:32 maybe I can come back to this in,
2:33:33 in Q&A,
2:33:34 but we've been thinking about the COVID-19 epidemic.
2:33:38 Um,
2:33:38 a lot of people are very concerned
2:33:40 that
2:33:41 countries,
2:33:42 some countries,
2:33:42 you know,
2:33:43 bought up supply early on,
2:33:45 um.
2:33:46 You know,
2:33:46 there's multiple ways to see that issue,
2:33:48 but clearly if we're thinking about the possibility of future,
2:33:51 future pandemics,
2:33:53 you know,
2:33:53 the best,
2:33:54 the best,
2:33:55 uh,
2:33:56 antidote to,
2:33:57 uh,
2:33:58 destructive competition to try to get,
2:34:00 uh,
2:34:01 get to lock up supply
2:34:03 is to make sure there's lots of capacity
2:34:06 in advance and,
2:34:08 um,
2:34:09 it.
2:34:10 Global public investment in supply chains
2:34:13 uh could be,
2:34:14 could be very important in,
2:34:16 in trying to address that.
2:34:17 And when we,
2:34:18 when we go on to the next uh slide.
2:34:25 OK.
2:34:26 Um,
2:34:27 OK.
2:34:28 So this is,
2:34:28 um,
2:34:29 let me switch,
2:34:30 uh,
2:34:30 switch gears now.
2:34:31 So up till now,
2:34:32 I've been talking about
2:34:33 how can we increase vaccine capacity.
2:34:36 The second,
2:34:37 the,
2:34:38 the other topic that I wanted to address is
2:34:42 Given the capacity we have,
2:34:43 are there ways to use it more efficiently?
2:34:45 And here,
2:34:46 you know,
2:34:46 this is work that we're,
2:34:48 that we're that's currently in progress.
2:34:50 Um,
2:34:51 I,
2:34:52 you know,
2:34:52 this is obviously going to be
2:34:54 up to
2:34:55 medical people as it should be to make these decisions,
2:34:58 but I have been involved in some modeling on the potential benefits of some ways of,
2:35:03 of,
2:35:04 um,
2:35:05 of
2:35:06 basically stretching our vaccine supply,
2:35:08 getting more out of our existing
2:35:10 supply.
2:35:11 So
2:35:11 I wanted to
2:35:13 talk about the potential benefits of this.
2:35:15 The one approach is,
2:35:16 is the first dose is first.
2:35:18 Um,
2:35:19 so giving the second dose after
2:35:21 12 weeks rather than 4 weeks.
2:35:23 That obviously can allow more people to receive the first dose sooner,
2:35:26 and there's
2:35:27 seems likely,
2:35:28 um,
2:35:28 based on,
2:35:29 on our reading of the evidence that
2:35:31 uh the first dose conveys a lot of the overall protection.
2:35:35 So that,
2:35:36 some modeling we've done suggests that
2:35:38 could substantially reduce mortality and infections.
2:35:41 Um,
2:35:43 the UK adopted the strategy,
2:35:45 you know,
2:35:45 early data from the UK seems to support that idea.
2:35:48 Um,
2:35:49 the,
2:35:50 um,
2:35:51 the
2:35:52 giving,
2:35:53 um,
2:35:53 second doses,
2:35:55 um.
2:35:56 Uh,
2:35:57 you know,
2:35:57 another approach would be to say,
2:35:59 um,
2:36:00 maybe there could be some subset of the population.
2:36:02 They got the
2:36:04 two doses in,
2:36:05 in
2:36:06 Europe
2:36:07 after a 4 week delay,
2:36:08 so maybe the
2:36:09 most at-risk populations could get them
2:36:13 um
2:36:14 after the shorter delay,
2:36:16 but others we could,
2:36:17 once we get past those
2:36:19 most critical populations,
2:36:20 another strategy would be to
2:36:22 do first doses first outside of the most critical populations.
2:36:26 Another approach would be to say if people are
2:36:29 previously infected,
2:36:30 they only get one dose,
2:36:32 um,
2:36:32 but people who've who've uh,
2:36:34 others get
2:36:35 get both doses.
2:36:36 So there are a variety of strategies along these lines,
2:36:39 and
2:36:40 there's some modeling we've done suggests
2:36:42 potentially very large benefits of this.
2:36:45 OK,
2:36:45 um,
2:36:46 when we go on to the next slide.
2:36:49 You know,
2:36:49 Another approach would be to adjust the dosage.
2:36:53 So
2:36:53 early in the,
2:36:54 the standard,
2:36:55 uh,
2:36:55 the standard thing that um
2:36:57 um
2:36:58 makes sense in most situations is to design the dosage
2:37:02 to maximize the trade-off
2:37:05 side effects uh against efficacy
2:37:07 and choose the dosage that's optimal for whoever's getting the vaccine in their,
2:37:11 in their arms.
2:37:13 Now this is a situation,
2:37:14 and that makes complete sense when
2:37:17 there's.
2:37:18 When,
2:37:18 you know,
2:37:18 vaccines is available in,
2:37:20 in full,
2:37:21 um,
2:37:22 as you know you can buy as much vaccine as you,
2:37:24 as is needed,
2:37:24 and it's,
2:37:25 and the cost is relatively low relative to the benefits.
2:37:28 There's no real need to focus on conserving
2:37:31 vaccine supply.
2:37:33 In this situation,
2:37:34 where it may take years,
2:37:35 uh,
2:37:36 it may take a couple of years to vaccinate the whole world,
2:37:39 um,
2:37:40 you know,
2:37:40 the,
2:37:40 the extra vaccine that you could save could be very
2:37:43 valuable for somebody else and for society as a whole.
2:37:48 So
2:37:48 there's at least a case for taking not just a medical approach to this,
2:37:53 thinking about the individual patient getting the vaccine,
2:37:55 but a public health approach that thinks about the population as a whole.
2:37:59 I think that's reinforced because
2:38:01 just like we don't really know the optimal
2:38:05 amount of time between the 1st and 2nd dose,
2:38:07 only some things have been tested,
2:38:09 not everything.
2:38:10 We don't really know the optimal dosage for vaccines.
2:38:13 You know,
2:38:13 certain things were tried,
2:38:15 um,
2:38:15 and we have evidence on their impact,
2:38:18 but we don't have,
2:38:19 uh,
2:38:19 we don't know for sure what's,
2:38:21 what's optimal,
2:38:22 even from the standpoint of the individual.
2:38:24 Now,
2:38:25 um,
2:38:28 If there's,
2:38:29 it could well be,
2:38:30 and uh my understanding is that um
2:38:33 there could,
2:38:34 it could be that
2:38:35 much lower doses would be,
2:38:37 would,
2:38:37 would work
2:38:38 very well from the standpoint
2:38:40 of an individual patient.
2:38:41 You know,
2:38:41 we don't know that for sure,
2:38:42 but it seems possible.
2:38:44 Um,
2:38:44 you know,
2:38:44 there's one interpretation of some AstraZeneca results suggest that
2:38:48 a half dose,
2:38:49 there was a.
2:38:49 Mistake during the trial.
2:38:51 Um,
2:38:51 one interpretation of that is that a half dose followed by a full dose might be
2:38:55 more effective than a full dose.
2:38:57 There are other,
2:38:58 you know,
2:38:58 interpretations of that,
2:39:00 but
2:39:00 if we could
2:39:01 get
2:39:02 moved to a half dose or even a quarter dose,
2:39:04 that would obviously,
2:39:06 uh,
2:39:07 very,
2:39:07 you know,
2:39:07 have a huge impact on vaccine capacity.
2:39:10 So,
2:39:11 um,
2:39:12 when we go to the next slide?
2:39:17 Um,
2:39:19 If you would go one more and then maybe we'll come back to this.
2:39:22 So,
2:39:23 I think the
2:39:24 um
2:39:26 In this situation where there's
2:39:28 very large potential benefits from
2:39:31 uh from other ways of,
2:39:33 of,
2:39:34 of delivering vaccines,
2:39:35 uh,
2:39:36 from lowering the doses,
2:39:37 from
2:39:38 uh a first doses first approach.
2:39:41 I think
2:39:42 Information.
2:39:44 On the impact of this would be very valuable.
2:39:47 In fact,
2:39:47 it would be valuable
2:39:49 to the world as a whole,
2:39:51 the the because that information could affect vaccine policy
2:39:54 in many countries.
2:39:55 It'd be particularly valuable
2:39:57 for low and middle income countries which tend to be at the back of the queue
2:40:01 and don't have access to too many doses.
2:40:03 You know,
2:40:03 less valuable for the,
2:40:05 the,
2:40:05 the US or or
2:40:08 or UK or UAE or Israel which already have a lot of uh uh doses.
2:40:13 Um,
2:40:14 the,
2:40:14 um,
2:40:15 how would we find this out?
2:40:17 Well,
2:40:18 we'd find out through additional vaccine trials,
2:40:21 and
2:40:21 those could be done,
2:40:23 um,
2:40:23 by conducting dosing strategies head to head.
2:40:27 You could try the uh status quo dosing strategy
2:40:31 against a,
2:40:31 a single dose,
2:40:33 against uh smaller doses.
2:40:35 You wouldn't necessarily need a control group because the comparison would be
2:40:40 not to
2:40:41 um
2:40:42 not to
2:40:43 not getting a vaccine at all,
2:40:44 but comparing to the
2:40:46 uh existing vaccines.
2:40:48 Those,
2:40:49 those,
2:40:50 that could be embedded,
2:40:51 those trials could be embedded in vaccine roll-outs and done at very large scale.
2:40:56 Um,
2:40:56 and this would be low risk because the safety's already
2:40:59 been tested.
2:41:01 Um,
2:41:01 in the language of economics,
2:41:02 this would have a very large option value.
2:41:05 If we found out that
2:41:07 that going with a half dose or a quarter dose
2:41:11 provided the same protection as
2:41:14 the current status quo dose,
2:41:16 that would have immense benefits for the world,
2:41:19 would save many lives,
2:41:20 would allow our economies and societies to go back to,
2:41:24 to,
2:41:24 uh,
2:41:25 to get back to something approaching normalcy much,
2:41:27 much more quickly.
2:41:29 If it turned out that this didn't work.
2:41:32 You know,
2:41:33 then at that point,
2:41:34 um,
2:41:35 you could provide the second dose to people who got,
2:41:37 who hadn't got it.
2:41:38 You could,
2:41:39 um,
2:41:39 provide,
2:41:40 uh,
2:41:40 follow-up,
2:41:41 uh,
2:41:42 uh,
2:41:42 larger doses to people if needed.
2:41:44 So
2:41:45 there's,
2:41:46 there's,
2:41:47 you know,
2:41:47 the benefits are huge.
2:41:49 The,
2:41:49 uh,
2:41:50 the sorry,
2:41:50 let me restate that.
2:41:51 The potential benefits are huge.
2:41:53 The downside is very limited.
2:41:55 But
2:41:56 there's not much incentive for a private firm to finance these trials.
2:42:00 They really need to be funded publicly
2:42:03 and because the benefits would be global.
2:42:06 I think there's a very strong case for
2:42:09 international organizations to support these trials.
2:42:12 So I think this is one of the
2:42:14 highest,
2:42:14 uh,
2:42:15 highest priority investments that could be made.
2:42:18 Let me go back a slide.
2:42:22 Um,
2:42:24 OK.
2:42:25 Um,
2:42:26 Um,
2:42:27 I mention one other thing that,
2:42:29 that could be done,
2:42:30 which is to make sure that we use all the available vaccines.
2:42:35 So,
2:42:35 you know,
2:42:35 there's different vaccines out there,
2:42:37 they differ in a variety of ways.
2:42:40 Some,
2:42:40 some uh may have lower efficacy,
2:42:42 some have higher efficacy.
2:42:44 This is,
2:42:44 you know,
2:42:45 they all have pretty high efficacy against the,
2:42:47 the most severe forms of the disease,
2:42:49 but they,
2:42:50 they have different efficacy against less severe forms.
2:42:53 Um,
2:42:53 and there,
2:42:54 you know,
2:42:54 there might be different efficacy against different strains,
2:42:57 uh,
2:42:57 obviously,
2:42:58 um,
2:42:59 you know,
2:43:00 different storage requirements,
2:43:01 etc.
2:43:02 So,
2:43:03 different,
2:43:03 um,
2:43:04 using all of these as soon as they're available globally
2:43:08 will provide the most social benefit.
2:43:10 Um,
2:43:10 you know,
2:43:10 I've already
2:43:12 talked about the,
2:43:12 the importance of speed.
2:43:15 Um,
2:43:15 we've done some calculations,
2:43:17 you know,
2:43:17 if,
2:43:17 if a country had access
2:43:19 to a 70% effective vaccine now
2:43:22 or a 95% effective one in 3 months,
2:43:25 we find that there are higher benefits
2:43:26 from starting with the immediately available one.
2:43:28 So
2:43:29 for countries that are in that situation,
2:43:32 I think the important thing is to get some vaccine out
2:43:34 right away.
2:43:35 Um,
2:43:36 but the,
2:43:37 the other,
2:43:38 when we go on to,
2:43:38 uh,
2:43:40 maybe
2:43:40 skip two slides.
2:43:42 But given that different countries will have different
2:43:46 access to different vaccines,
2:43:47 they sign different contracts,
2:43:49 and that vaccines have different characteristics.
2:43:52 Countries may have different needs or preferences,
2:43:55 and
2:43:56 countries might end up with vaccine allocations that aren't
2:43:59 optimally matched to their needs.
2:44:01 That means that there could be gains in terms of
2:44:03 utilization of all the vaccines on a global basis.
2:44:06 If,
2:44:07 if,
2:44:08 um,
2:44:09 if there was a vaccine exchange mechanism,
2:44:11 uh,
2:44:11 probably run through COVAX that would enable
2:44:14 countries to engage in mutually beneficial trades.
2:44:17 I think that's um,
2:44:18 you know.
2:44:19 I,
2:44:19 I may not have all my facts straight,
2:44:21 but I think the US is,
2:44:23 is,
2:44:23 um,
2:44:23 sitting on some vaccines
2:44:25 now that it's not using,
2:44:26 but it's not,
2:44:27 um,
2:44:28 it's not actually sitting on some vaccine
2:44:30 capacity that isn't authorized for the US,
2:44:33 um,
2:44:33 but
2:44:34 that other countries might be able to use.
2:44:36 That's a,
2:44:36 a crazy situation and it makes sense to
2:44:39 find ways to either do exchanges or donations,
2:44:42 uh,
2:44:42 to address that issue.
2:44:47 We go on to the next slide.
2:44:49 Um,
2:44:50 OK,
2:44:51 um.
2:44:52 Just to conclude,
2:44:53 um,
2:44:54 I think the value of investing to expand vaccine capacity is still very large,
2:44:59 you know,
2:44:59 just to,
2:45:00 um,
2:45:01 refine that argument a little bit.
2:45:03 I mean,
2:45:03 you know,
2:45:04 there is a lot of uncertainty.
2:45:05 We don't know,
2:45:06 uh,
2:45:06 what's gonna happen,
2:45:07 that's been a characteristic of this epidemic
2:45:10 throughout.
2:45:10 But I think if,
2:45:11 if we think about the asymmetries,
2:45:13 if we
2:45:14 invested in capacity now and it turned out that
2:45:17 that capacity couldn't be,
2:45:18 uh,
2:45:19 couldn't,
2:45:19 that,
2:45:20 you know,
2:45:20 it didn't come on.
2:45:21 or the epidemic
2:45:24 finished
2:45:25 and you know just went away
2:45:28 before it can come online,
2:45:29 well,
2:45:29 maybe we've spent a few billion dollars.
2:45:32 But the
2:45:33 opposite scenario
2:45:35 where there's
2:45:36 where we have less effective capacity than we believe because of
2:45:40 either because of production difficulties or because of
2:45:44 new strains that mean that we can't use all of the existing vaccines,
2:45:48 um,
2:45:48 there we're talking about.
2:45:51 Losing hundreds of billions or trillions of dollars a month
2:45:54 and
2:45:55 you know,
2:45:55 hundreds of thousands of lives,
2:45:57 so
2:45:58 that asymmetry means it's,
2:45:59 it's really worth
2:46:00 doing what we can to
2:46:02 further expand investment even at this
2:46:05 late date.
2:46:06 So
2:46:06 soliciting bids from firms to identify opportunities makes sense.
2:46:10 This
2:46:12 contract should include provisions for capacity investment,
2:46:15 and we should be trying to address supply chain constraints as well as the
2:46:19 final production.
2:46:20 And then finally,
2:46:21 I think it makes sense to find ways to use existing capacity
2:46:25 more efficiently.
2:46:26 If we can,
2:46:27 we can,
2:46:28 you know,
2:46:28 think about trade-offs.
2:46:30 Speed and efficacy,
2:46:31 think about things like first doses first or
2:46:34 or or uh or
2:46:35 adjusting the dosage,
2:46:36 we'll need trials probably
2:46:38 to to do that,
2:46:39 um,
2:46:40 but
2:46:41 investing in those trials is uh is
2:46:43 is very valuable and finally we should have some sort of
2:46:46 cross-country um
2:46:47 uh vaccine exchange.
2:46:50 Um,
2:46:50 very happy to,
2:46:51 to
2:46:52 hear reactions and,
2:46:53 and discuss these issues.
2:46:58 Thank you very much,
2:46:59 uh,
2:46:59 uh,
2:47:00 Michael,
2:47:00 for,
2:47:01 for your,
2:47:02 uh,
2:47:02 lecture.
2:47:03 Uh,
2:47:04 very,
2:47:04 very clear.
2:47:05 Your case for speed was,
2:47:07 was well taken.
2:47:08 Uh,
2:47:09 I have,
2:47:10 I have uh maybe a couple of questions,
2:47:11 but I don't want to take.
2:47:12 Advantage of,
2:47:13 of my position of,
2:47:14 of moderating.
2:47:15 So
2:47:15 I know that there is an answer as a question.
2:47:18 So
2:47:18 uh I'll,
2:47:19 uh,
2:47:20 I'll give him the floor and then there is the question on the chat box.
2:47:24 So,
2:47:24 that answer,
2:47:25 uh,
2:47:26 please start
2:47:27 with your question.
2:47:30 Good morning and thanks so much,
2:47:32 Michael.
2:47:33 fascinating overview.
2:47:35 Also from South Asia's perspective.
2:47:38 It's,
2:47:38 it's very helpful to have that global overview.
2:47:41 You made that important point that
2:47:43 not just the supply of vaccines is enormously valuable,
2:47:47 but the speed of supply is really valuable,
2:47:52 and you would assume that that would be reflected in price differentiation.
2:47:57 That those who get the vaccines first,
2:48:00 they pay a higher price.
2:48:02 The reality seems to be the opposite.
2:48:04 It seems to be that developing countries,
2:48:08 when they try to purchase beyond the COVX supply,
2:48:13 they pay actually a relatively high price relative to what high income.
2:48:17 Countries have negotiated.
2:48:20 So my question is,
2:48:21 how do you see the inefficiency
2:48:24 of that price differentiation?
2:48:27 And then a related question is,
2:48:29 what is the economic rationale.
2:48:33 Behind the fact that these negotiated advanced market placements
2:48:39 are not being disclosed,
2:48:40 so that we don't actually know what prices are
2:48:43 being paid and and what the price differentiation is.
2:48:46 So,
2:48:47 so what is
2:48:48 the economic rationale there because it seems when speed is so important
2:48:52 that price differentiation is also important.
2:48:55 Thank you so much.
2:48:58 That,
2:48:59 uh,
2:49:00 question up.
2:49:01 Um,
2:49:01 so the first issue is,
2:49:02 you know,
2:49:03 why aren't the first doses being sold for more,
2:49:05 and
2:49:06 you know,
2:49:06 we estimate that the social value of,
2:49:09 of those initial doses is indeed much,
2:49:12 much higher than the social value of,
2:49:13 of,
2:49:13 of later doses.
2:49:15 Completely agree with you on that.
2:49:17 In some types of markets,
2:49:19 um,
2:49:19 you know,
2:49:20 if this were,
2:49:21 if the.
2:49:21 If the vaccines were all being allocated through a global auction system,
2:49:25 uh,
2:49:25 then,
2:49:26 um,
2:49:26 then,
2:49:27 you know,
2:49:27 perhaps we would see that reflected in the prices.
2:49:29 But in fact,
2:49:30 the,
2:49:30 the prices here are very influenced by
2:49:33 political and legal and ethical constraints.
2:49:35 And,
2:49:36 um,
2:49:37 but that doesn't necessarily mean that translate into fairness,
2:49:40 uh,
2:49:41 um,
2:49:42 and in fact there's,
2:49:43 you know,
2:49:44 a lot of unfairness in the system and you're,
2:49:46 you're,
2:49:46 you know,
2:49:47 you're pointing out 11 form of that,
2:49:49 um.
2:49:50 I will say that even the higher prices,
2:49:53 so for example when South Africa went outside and bought additional
2:49:57 doses,
2:49:57 they had to pay a higher price for that.
2:50:00 That if,
2:50:01 if,
2:50:02 if nonetheless,
2:50:03 despite paying a higher price than the uh
2:50:05 than the uh the price that,
2:50:07 you know,
2:50:07 some of the other prices out there,
2:50:09 it's still an enormous bargain.
2:50:11 If you look at it from the standpoint of the,
2:50:13 but if you're looking at this as a finance ministry,
2:50:16 and you think about the
2:50:18 um the loss.
2:50:19 Just the pure amount that countries are spending
2:50:22 on on dealing with the epidemic and the huge macroeconomic losses,
2:50:26 you know,
2:50:26 paying for vaccine doses is,
2:50:28 is an incredibly high return on investment
2:50:32 um
2:50:33 uh way of spending funds,
2:50:35 so it's.
2:50:36 Uh,
2:50:37 if you're senior finance ministry and you don't control the global system,
2:50:40 um,
2:50:41 but you have to think about the interests of your country,
2:50:43 I would,
2:50:44 it's still worth paying to go beyond the,
2:50:46 um,
2:50:46 the,
2:50:47 uh,
2:50:47 the COVAC allocation.
2:50:49 Uh,
2:50:49 what we need to think about from a global system point
2:50:51 of view is how to address this problem in the future,
2:50:54 and I think the way to address the problem in the future
2:50:56 is a key element of that,
2:50:58 is to make sure that there's a lot that we have to basically
2:51:02 invest in enough.
2:51:04 Intermediate
2:51:05 uh input production,
2:51:07 uh,
2:51:07 make sure there's enough bioreactors,
2:51:09 enough,
2:51:09 you know,
2:51:10 delivery devices,
2:51:11 glass vials,
2:51:11 etc.
2:51:12 enough adjuvants,
2:51:13 enough raw materials
2:51:14 to deal with a,
2:51:15 a pandemic,
2:51:16 should it appear,
2:51:17 and you know that's both a,
2:51:19 you know,
2:51:19 that will require some public investment.
2:51:21 Because the private sector won't,
2:51:24 won't,
2:51:24 you know,
2:51:25 pay to stockpile those things
2:51:27 um
2:51:27 on the chance an epidemic will occur,
2:51:29 and you know some of this will become obsolete,
2:51:31 so I don't want to claim there's zero cost,
2:51:33 but this is a cost that's measured in the billions of dollars globally
2:51:36 and you know,
2:51:37 could obviously avert.
2:51:38 Catastrophe.
2:51:39 So it's,
2:51:40 it's worth doing,
2:51:41 um,
2:51:42 and it would,
2:51:42 I think,
2:51:43 have the side benefit
2:51:45 of
2:51:46 helping,
2:51:47 having that
2:51:48 if there is that capacity in place enough for the world,
2:51:51 then there's much less temptation for
2:51:53 individual countries to start doing things that
2:51:56 create negative.
2:51:56 Externalities for other countries like
2:51:58 prohibiting exports or
2:52:01 uh or trying to you know sort of seize buy
2:52:03 up all the available capacity or something like that.
2:52:07 Um,
2:52:07 the second part of your question had to do with transparency.
2:52:10 Um,
2:52:10 I don't know whether my co-author Chris Snyder is on the line.
2:52:13 Are,
2:52:13 are you on the line,
2:52:14 Chris?
2:52:18 OK.
2:52:19 Um,
2:52:19 um,
2:52:20 well,
2:52:20 let me see if I can take a crack at it.
2:52:22 I,
2:52:22 I would just say that the issues about whether contracts should be public,
2:52:26 you know,
2:52:27 Chris is an industrial organization economist who,
2:52:29 who specializes in
2:52:31 this type of question,
2:52:32 um.
2:52:35 It's actually a complicated question.
2:52:37 Um,
2:52:37 you know,
2:52:37 there are maybe potential benefits of,
2:52:40 of that,
2:52:40 but there's also potential downsides.
2:52:43 So,
2:52:43 you know,
2:52:43 one standard result in industrial organization,
2:52:46 not specifically about vaccines and not necessarily about public
2:52:50 procurement,
2:52:51 but
2:52:52 you know,
2:52:52 sometimes.
2:52:54 Having,
2:52:54 um,
2:52:55 if,
2:52:56 if all contracts,
2:52:57 if you're thinking,
2:52:58 if you're a manufacturer and you're thinking about giving a discount,
2:53:01 well,
2:53:02 You might not want to give a discount if you think
2:53:04 that's going to force you to give a discount next time.
2:53:07 So you might be more reluctant to give a discount.
2:53:10 If,
2:53:11 if,
2:53:11 if you think everything's gonna become transparent,
2:53:14 or if there's collusion among manufacturers,
2:53:17 that may be easier to enforce if there's transparency.
2:53:21 So,
2:53:21 uh,
2:53:22 or
2:53:23 call it public information,
2:53:24 I'll be more technical.
2:53:25 The transparency sounds,
2:53:26 I guess the transparency sounds like,
2:53:29 oh,
2:53:29 that's gotta be a good thing,
2:53:30 um.
2:53:31 And it may well be that the the on balance,
2:53:34 transparency,
2:53:35 the benefits outweigh the costs,
2:53:36 but there are potential costs.
2:53:38 I think this requires,
2:53:39 you know,
2:53:39 careful thought,
2:53:40 um,
2:53:41 um,
2:53:42 and
2:53:43 I would focus
2:53:44 right now.
2:53:44 I would focus more on expanding supply
2:53:47 so we can expand speed or accelerate delivery.
2:53:50 That seems the first order issue to me.
2:53:55 Uh,
2:53:55 thank you,
2:53:56 Michael.
2:53:56 Uh,
2:53:57 there's,
2:53:57 there's,
2:53:58 there was one
2:53:59 more question,
2:54:01 uh,
2:54:02 that I can pass along.
2:54:04 So the,
2:54:05 uh,
2:54:06 uh,
2:54:06 clearly,
2:54:07 uh,
2:54:07 if we don't have the vaccine doses,
2:54:09 if we don't have the production,
2:54:11 uh,
2:54:11 we,
2:54:12 we can't even discuss the next step.
2:54:14 But the next step is important.
2:54:16 Uh,
2:54:16 once,
2:54:17 uh,
2:54:17 once,
2:54:17 uh,
2:54:18 the doses are there,
2:54:19 We,
2:54:20 we observe
2:54:22 issues in delivering the doses from,
2:54:24 from where they are arriving in the airport to,
2:54:27 to the actual arms uh uh
2:54:29 and bodies of,
2:54:30 of the people.
2:54:30 Do you see?
2:54:32 Do you see any,
2:54:33 uh,
2:54:34 probably the arguments are equivalent there.
2:54:36 We should also
2:54:38 invest in the capacity of delivering this,
2:54:40 or
2:54:40 what is your thoughts there?
2:54:42 What are your thoughts?
2:54:44 You're,
2:54:45 you're,
2:54:45 you're muted,
2:54:45 you're muted.
2:54:46 Sorry.
2:54:50 Uh,
2:54:50 and,
2:54:51 uh,
2:54:51 this,
2:54:51 yes,
2:54:52 you're,
2:54:52 I completely agree.
2:54:53 The same logic that,
2:54:54 that says there's huge,
2:54:56 uh,
2:54:57 um,
2:54:57 you know,
2:54:58 uh,
2:54:58 economic as well as health value to
2:55:00 accelerating
2:55:02 production.
2:55:02 Obviously that,
2:55:03 that value is only realized if those vaccines reach people.
2:55:07 So,
2:55:07 uh,
2:55:08 having a delivery system that functions well is,
2:55:10 is vitally important.
2:55:12 Um,
2:55:12 you know,
2:55:12 I
2:55:14 I spoke about production because that's the topic that I've been,
2:55:17 been working on,
2:55:18 but,
2:55:19 um,
2:55:19 you know,
2:55:19 the,
2:55:19 the delivery is also really vital.
2:55:24 Uh,
2:55:24 OK.
2:55:25 Uh,
2:55:26 great.
2:55:27 Uh,
2:55:27 I,
2:55:28 um,
2:55:29 Yeah,
2:55:29 I think I,
2:55:30 I don't see any other uh question.
2:55:33 So maybe I'll,
2:55:33 I'll,
2:55:34 uh,
2:55:34 I'll ask one which is related to what the,
2:55:37 uh,
2:55:38 what,
2:55:38 uh,
2:55:38 the,
2:55:38 the,
2:55:39 the discussion that you just had earlier,
2:55:41 but that is
2:55:42 11 of the
2:55:44 One of the,
2:55:45 uh,
2:55:46 issue that you mentioned is that the,
2:55:48 there may be a,
2:55:49 a supply constraint in the intermediary,
2:55:51 uh,
2:55:52 goods to the,
2:55:52 to the production.
2:55:54 And,
2:55:54 uh,
2:55:55 uh,
2:55:55 you,
2:55:56 you,
2:55:56 you've said that,
2:55:57 uh,
2:55:58 it's,
2:55:58 it's probably very difficult to think of
2:56:01 a large private investment because demand is temporary.
2:56:05 Uh,
2:56:06 for,
2:56:07 for the vaccine potentially.
2:56:08 So you,
2:56:08 it,
2:56:08 it's gonna be,
2:56:09 it's gonna be idle for,
2:56:11 for the long run,
2:56:12 so it doesn't make a lot of sense.
2:56:13 But
2:56:13 you also,
2:56:14 there's was also mentioned that the price of output is fixed.
2:56:17 Now,
2:56:18 um,
2:56:19 is it,
2:56:19 is it,
2:56:20 uh,
2:56:21 can we have a discussion about
2:56:23 someone can pay more,
2:56:24 uh,
2:56:25 uh,
2:56:25 or,
2:56:26 or is this part of the,
2:56:27 of the,
2:56:28 uh,
2:56:28 auction,
2:56:30 and the way that the prices are decided?
2:56:32 I,
2:56:32 I,
2:56:32 I'm just
2:56:33 reiterating a little bit of discussion of
2:56:36 can,
2:56:36 can the price not be fixed
2:56:39 and someone can afford to pay more.
2:56:44 Sorry again for muted that,
2:56:45 sorry,
2:56:45 but.
2:56:51 You know?
2:56:52 Right.
2:56:53 Um,
2:56:54 the,
2:56:54 um,
2:56:57 So I,
2:56:58 I think that,
2:56:59 you know,
2:56:59 there are very important global equity issues here
2:57:02 and
2:57:03 there are multiple ways to address that.
2:57:06 So if we think about
2:57:07 um
2:57:08 the
2:57:08 benefits of,
2:57:10 of,
2:57:10 of,
2:57:10 of averting the next pandemic or being able to deal with the next pandemic,
2:57:15 you know,
2:57:15 that is really something that
2:57:17 um
2:57:18 from at an economic,
2:57:20 from an economic.
2:57:20 standpoint,
2:57:21 most of the benefits will go to higher income countries.
2:57:24 Um,
2:57:25 so if we think about what's equitable financing for,
2:57:28 uh,
2:57:28 putting in these stockpiles of vaccines for financing,
2:57:32 uh,
2:57:32 sorry,
2:57:33 stockpiles of intermediate inputs for vaccines,
2:57:35 um,
2:57:36 stockpile,
2:57:36 um,
2:57:37 perhaps financing,
2:57:38 uh,
2:57:38 production capacity,
2:57:40 so factories that could produce
2:57:42 bioreactors or glass vials.
2:57:44 And,
2:57:44 and,
2:57:44 and so on,
2:57:45 um,
2:57:45 you know,
2:57:46 who should cover the costs of,
2:57:48 of that?
2:57:49 Well,
2:57:49 you know,
2:57:49 the biggest beneficiaries are probably going to be the high income countries,
2:57:53 um,
2:57:54 and so it probably makes sense for them
2:57:56 to do a disproportionate share of the financing.
2:57:59 Um,
2:58:00 you know,
2:58:00 that could be done in a variety of ways.
2:58:02 First,
2:58:02 they could just put out more cash.
2:58:04 Um,
2:58:04 second,
2:58:04 you could say that if the,
2:58:06 if,
2:58:07 You know,
2:58:07 part of the contract could potentially be
2:58:09 that the output from these factories that there'd be,
2:58:13 would be sold at cost or closer to cost for,
2:58:16 you know,
2:58:16 for low income countries or for low and middle income countries.
2:58:19 There are various ways to,
2:58:21 to design systems like that,
2:58:23 um,
2:58:23 but I,
2:58:24 I agree that thinking about equity and financing of this does make sense.
2:58:31 OK.
2:58:31 Uh,
2:58:33 I,
2:58:34 uh,
2:58:35 there's,
2:58:36 just 11 question that,
2:58:38 uh,
2:58:39 came,
2:58:39 a moment ago,
2:58:40 so I'm just reading it out,
2:58:42 uh,
2:58:42 for you.
2:58:43 Uh,
2:58:44 mm,
2:58:45 OK,
2:58:45 so the question is about the,
2:58:47 the,
2:58:48 a bit of demand side
2:58:49 and it goes like this.
2:58:51 What would it take to build acceptability
2:58:54 for head to head trials?
2:58:57 Uh,
2:58:57 different vaccine should be fine,
2:58:59 but different doses may be,
2:59:00 uh,
2:59:01 more addictive.
2:59:02 Any
2:59:03 Uh,
2:59:03 thoughts on that?
2:59:06 Yes,
2:59:07 you know,
2:59:12 I think that,
2:59:12 am I not muted?
2:59:14 I,
2:59:14 I think somebody keeps muting me.
2:59:15 OK,
2:59:15 great.
2:59:16 Um,
2:59:16 so I think that um having a,
2:59:19 um,
2:59:21 If you think about
2:59:23 willingness to join a trial,
2:59:24 you know,
2:59:25 probably you wouldn't be doing the trial among the,
2:59:28 among the elderly or,
2:59:30 or health workers.
2:59:31 It would probably be people like,
2:59:32 uh,
2:59:33 people like me who are,
2:59:35 who would be further back in the queue,
2:59:37 um,
2:59:38 and
2:59:39 so,
2:59:39 or people younger than me for that matter.
2:59:41 And
2:59:42 the,
2:59:42 um,
2:59:43 If you're thinking about somebody who's further back in the queue,
2:59:46 if I think about myself,
2:59:48 if I had the chance to volunteer for a trial tomorrow,
2:59:51 where I might get the full dose,
2:59:52 or I might get a partial dose,
2:59:54 and I should emphasize that the
2:59:56 pharmacological model suggests these partial doses might be just as effective.
3:00:00 You know,
3:00:00 I would,
3:00:01 if,
3:00:01 if my alternative right now is to wait without any vaccine at all,
3:00:05 I'd be very happy to sign up for a trial like that.
3:00:07 And obviously if it turns out that the trial,
3:00:09 if I get the high dose,
3:00:10 great.
3:00:10 If I get the lower dose,
3:00:12 that might also turn out to be fine.
3:00:14 If it doesn't turn out to be fine,
3:00:15 you know,
3:00:16 part of the provisions in the trial could be,
3:00:18 we'll,
3:00:18 we'll,
3:00:19 we'll,
3:00:20 you know,
3:00:20 arrange the participants in the trial if the.
3:00:22 To come back suggesting
3:00:24 that a larger dose is necessary,
3:00:26 that they would get the full dose,
3:00:27 for example.
3:00:28 So,
3:00:29 um,
3:00:29 so the,
3:00:31 um,
3:00:31 so I think that there'd be plenty of people who
3:00:33 would want to sign up for a trial like this.
3:00:36 If you did have a trial like this,
3:00:38 then that would,
3:00:39 um,
3:00:40 and that was done with a large sample size and you got results quickly,
3:00:43 you know,
3:00:43 that could.
3:00:44 Have huge benefits for the world.
3:00:46 So I think this could be done.
3:00:48 Obviously it has to be,
3:00:49 it could be done ethically.
3:00:52 It would,
3:00:52 it does need to be financed,
3:00:54 and I think we,
3:00:55 that's something that
3:00:57 individual countries should think about.
3:00:59 Organizations like
3:01:00 the World Bank should think about.
3:01:02 Certainly
3:01:03 donors and philanthropists should think about it,
3:01:05 and
3:01:07 And um
3:01:08 I,
3:01:09 I,
3:01:10 I,
3:01:11 you know,
3:01:11 I guess I,
3:01:12 I would say that's a very high priority for the world.
3:01:14 I think it's doable.
3:01:18 Uh,
3:01:18 OK.
3:01:19 Thank you
3:01:20 very much.
3:01:21 Um,
3:01:23 let me ask,
3:01:23 uh,
3:01:24 orally,
3:01:25 quickly,
3:01:26 if anyone,
3:01:27 uh,
3:01:27 I don't see any more questions in the chat box.
3:01:29 If anyone wants to come in
3:01:32 directly,
3:01:32 uh,
3:01:33 opening the mic and talk now.
3:01:35 Uh
3:01:38 Uh,
3:01:39 going 1,
3:01:40 going 2.
3:01:42 Go 3,
3:01:43 OK.
3:01:44 So,
3:01:45 so I'll um,
3:01:46 uh,
3:01:47 OK,
3:01:47 again,
3:01:48 uh,
3:01:48 thank you so much for the stimulating and very interesting and clear,
3:01:53 uh,
3:01:53 lecture.
3:01:54 Thank you,
3:01:55 everybody who's still here from the other,
3:01:57 uh,
3:01:58 presentations.
3:01:59 Uh,
3:01:59 I learned,
3:02:00 uh,
3:02:00 a lot.
3:02:01 It was a very,
3:02:03 uh,
3:02:04 interesting,
3:02:04 um,
3:02:05 uh,
3:02:06 2 almost 3 hours.
3:02:07 3 hours actually.
3:02:09 So,
3:02:09 um,
3:02:10 uh,
3:02:10 just one final word,
3:02:12 which is,
3:02:13 uh,
3:02:13 I hope to see you all
3:02:15 again tomorrow for our second day starting,
3:02:19 uh,
3:02:20 uh,
3:02:20 again at 6 a.m.,
3:02:21 same,
3:02:22 same screen,
3:02:23 same channels.
3:02:24 You'll have the links.
3:02:26 So,
3:02:26 uh,
3:02:27 for,
3:02:27 for now,
3:02:27 we are done for the first day.
3:02:29 Thank you all.
3:02:31 Uh,
3:02:31 see you soon.
3:02:33 Bye.
- add-style
- lp-body-content