COVID-19 Webinar:Fiscal, monetary and health policy responses and

implications for the economic outlook

Thursday, April 2, 2020 11 a.m. ETA discussion with

Alan Blinder, Bill Dudley, Jessica MetcalfModerated by Senator Bill Frist, M.D.

Webinar recording will be available at https://gceps.princeton.edu/events/

Sponsored by:

COVID-19: Current health trajectory, policy implications

C. Jessica Metcalf & Bryan T. Grenfell

Early outbreak

Two key quantities: R0, here = 2Serial interval:

initial case

Early outbreak

Two key quantities: R0, here = 2Serial interval:

Early outbreak

Two key quantities: R0, here = 2Serial interval:

Early outbreak

Two key quantities: R0, here = 2Serial interval:

… … … … … … … … …… … … … … …

Early outbreak

Two key quantities: R0, here = 2Serial interval:

… … … … … … … … …… … … … … …

Exponential growth

Feb 01 Feb 15 Mar 01 Mar 15

15

50500

Deaths

Feb 01 Feb 15 Mar 01 Mar 15

110

100

10000

Cases

New JerseyCaliforniaWashingtonNew York

https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv

Early outbreak

Two key quantities: R0, here = 2Serial interval:

… … … … … … … … …… … … … … …

Exponential growth

Feb 01 Feb 15 Mar 01 Mar 15

15

50500

Deaths

Feb 01 Feb 15 Mar 01 Mar 15

110

100

10000

Cases

New JerseyCaliforniaWashingtonNew York

https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv

Intervention impacts appear 2-3 weeks

in the future.

Early outbreak

https://www.cdc.gov/mmwr/volumes/69/wr/mm6912e2.htm?s_cid=mm6912e2_w#T1_downhttp://weekly.chinacdc.cn/en/article/id/e53946e2-c6c4-41e9-9a9b-fea8db1a8f51

A major public health issue:-asymptomatic transmission (?30-80%), impedes containment-severe outcomes for many, overwhelming health systems

Early outbreak

Cases are not infections

IFR << CFR

https://www.cdc.gov/mmwr/volumes/69/wr/mm6912e2.htm?s_cid=mm6912e2_w#T1_downhttp://weekly.chinacdc.cn/en/article/id/e53946e2-c6c4-41e9-9a9b-fea8db1a8f51

A major public health issue:-asymptomatic transmission (?20-80%), impedes containment-severe outcomes for many, overwhelming health systems

Early outbreak

https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30243-7/fulltext

Cases are not infections

IFR << CFR

A major public health issue:-asymptomatic transmission (?20-80%), impedes containment-severe outcomes for many, overwhelming health systems

Over time

Combine county level demography (Census data) and # of hospital beds (American Hospital Association), assume 40% of the pop. is infected; 80% show symptoms:

no beds; cases allocated to neighbouring counties.

Hospitalizations per hospital bed

https://github.com/ianfmiller/covid19-burden-mapping Ian Miller, Alex Becker

recovered

infected

‘herd immunity’

out$time

RE

0.5

1.0

1.5

2.0

2.5

3.0

0 5 10 15

0.0

0.2

0.4

0.6

0.8

1.0

Proportion

Susceptible

Infected

Recovered

R0 = 3

Pro

porti

on

Time (weeks)

susceptible

infected

Metcalf et al. 2015 Trends in Immunology

Over time

recovered

infected

‘herd immunity’

out$time

RE

0.5

1.0

1.5

2.0

2.5

3.0

0 5 10 15

0.0

0.2

0.4

0.6

0.8

1.0

Proportion

Susceptible

Infected

Recovered

R0 = 3

Pro

porti

on

Time (weeks)

susceptible

infected recovered

Metcalf et al. 2015 Trends in Immunology

Over time

recovered

infected

susceptible

‘herd immunity’

indirectly protected

out$time

RE

0.5

1.0

1.5

2.0

2.5

3.0

0 5 10 15

0.0

0.2

0.4

0.6

0.8

1.0

Proportion

Susceptible

Infected

Recovered

R0 = 3

Pro

porti

on

recovered

Metcalf et al. 2015 Trends in Immunology

Over time

recovered

infected

susceptible

‘herd immunity’

indirectly protected

out$time

RE

0.5

1.0

1.5

2.0

2.5

3.0

0 5 10 15

0.0

0.2

0.4

0.6

0.8

1.0

Proportion

Susceptible

Infected

Recovered

R0 = 3

Pro

porti

on

Metcalf et al. 2015 Trends in Immunology

Over time

Over time

0 5 10 15

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Time

Pro

porti

on in

fect

ed

#FlattenTheCurve

Health systems overwhelmed

Policies implemented: • Case based self-isolation mandated• Social distancing encouraged• Public events banned• School closure ordered• Lockdown ordered

https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/

Protect the health system + time to test therapeutics

Seasonality

Coronaviruses are ‘winter’ pathogens: reduced humidity / lower temperatures may increase transmission

Year

Cases

0500

1500

2500

0 1 2 3 4 5 6 7 8 9 10

winter

Year

Cases

0500

1500

2500

0 1 2 3 4 5 6 7 8 9 10

Seasonality

Coronaviruses are ‘winter’ pathogens: reduced humidity / lower temperatures may increase transmission

But magnitudes unlikely to overwhelm the effects of the large pool of susceptible individuals.

Year

Cases

0500

1500

2500

0 1 2 3 4 5 6 7 8 9 10

So many susceptible on first introduction - seasonal pattern disrupted

Rachel Baker, forthcoming

typical flu season

Miller et al. 2009 NEJM

Seasonality

Serology: a Global Immunological Observatory

Cases and deaths:

Susceptible

Infected

Recovered

Serology: a Global Immunological Observatory

Cases and deaths:Provide an incomplete window onto the epidemic

Susceptible

Infected

Recovered

Viewpoint

www.thelancet.com Published online April 5, 2016 http://dx.doi.org/10.1016/S0140-6736(16)30164-7 1

Use of serological surveys to generate key insights into the changing global landscape of infectious diseaseC Jessica E Metcalf, Jeremy Farrar, Felicity T Cutts, Nicole E Basta, Andrea L Graham, Justin Lessler, Neil M Ferguson, Donald S Burke, Bryan T Grenfell

A central conundrum in the study of infectious disease dynamics is to defi ne the landscape of population immunity. The proportion of individuals protected against a specifi c pathogen determines the timing and scale of outbreaks, and the pace of evolution for infections that can evade prevailing humoral immunity. Serological surveys provide the most direct measurement to defi ne the immunity landscape for many infectious diseases, yet this methodology remains underexploited. To address this gap, we propose a World Serology Bank and associated major methodological developments in serological testing, study design, and quantitative analysis, which could drive a step change in our understanding and optimum control of infectious diseases.

Epidemic dynamics result from an interaction between the contagious spread of infection, the resulting depletion of population susceptibility, and its replenishment via births, immigration, or waning immunity. Under-standing this interaction is key to assess the eff ect of vaccination, which artifi cially reduces the number of people susceptible to infection.

Researchers mainly observe infection dynamics and the eff ect of population (or herd) immunity in limiting spread via surveillance of clinically apparent cases of infection or deaths. This method has led to some powerful insights;1 however, even in the simplest instances in which subclinical infection is uncommon, cases only provide information about the dynamics of infection. Susceptibility and immunity are hidden variables. For infections that people can be completely immunised against, such as measles, susceptible reconstruction can be used to estimate immune profi les,2 but infection prevalence and vaccination coverage records are frequently inadequate to capture key social and geographical heterogeneities. Additionally, inference is weakened if the risk of infection is low.

Serological surveys (usually used to quantify the proportion of people positive for a specifi c antibody or, better yet, the titre or concentrations of an antibody) are potentially the most direct and informative technique available to infer the dynamics of a population’s susceptibility and level of immunity. However, the use of current serological tests varies greatly depending on type of pathogens and there are major methodological gaps in some areas for some pathogens and tests. In terms of use of current serological methods, infections can be classifi ed into four broad groups (appendix). The fi rst group contains acute immunising, antigenically stable pathogens (eg, measles, rubella, and smallpox) for which serology provides a strong signal of lifetime

protection and a clear marker of past infection (or vaccination).

The second group contains immunising, but antigenically variable pathogens (eg, infl uenza, invasive bacterial diseases, and dengue). Despite complexities (appendix), serology in some cases can provide powerful evidence, both for vaccine formulation and pandemic planning.3,4 A serum bank would have been extremely useful in interpretation of the unusual profi le of susceptibility associated with age in the 2009 infl uenza pandemic.3 For these fi rst two groups, if suitable serum banks existed, the deployment of current serological tests could have helped to clarify the association between serological profi les and protective immunity.

The third group includes infections for which infection-induced antibodies are not thought to be protective, such as tuberculosis in which the targets of the immune response vary with stage of infection; malaria, whereby infected erythrocytes generate several antibodies whose individual importance has not been fully elucidated (and might indicate exposure rather than protection5); and HIV. Although antibodies might not be representative of immunity against a pathogen, they do show current or previous infection.

Finally, the last broad grouping consists of infections that do not lead to reliably sustained, measurable antibody responses or for which presence of specifi c antibodies do not correlate with protection from future infection. These include many enteric infections and the human papillomavirus. In these cases, serological data can nonetheless be valuable to assess a population’s coverage of vaccine programmes if vaccination leads to long-lasting antibody responses.

In the context of public health, for immunisation against group one infections, vaccination programmes aim to protect vaccinated individuals and indirectly protect unvaccinated individuals by maintaining high population immunity.1 If a valid correlate of immunity is measurable in sera, serological surveys could be used to identify population subgroups in which immunity is low, or even to identify individuals in whom immunity has waned, and directly inform targeted vaccination strategies (appendix).

Household surveys are a major source of data for vaccination coverage in low-income countries.6 The recent extension of eff orts to measure biomarkers for infections such as HIV (eg, the Demographic Health Surveys) could provide infrastructure for sera collection for an expanded range of infections, thus leveraging an existing platform. For many infections, however, to

Published OnlineApril 5, 2016http://dx.doi.org/10.1016/S0140-6736(16)30164-7

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA (C J E Metcalf PhD, A L Graham PhD, Prof B T Grenfell PhD); Fogarty International Center, National Institute of Health, Bethesda, MD, USA (C J E Metcalf, N E Basta PhD, A L Graham, Prof B T Grenfell); Wellcome Trust, Gibbs Building, London, UK (J Farrar MD); London School of Hygiene & Tropical Medicine, London, UK (Prof F T Cutts MD);

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA (N E Basta); Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA (J Lessler PhD); Department of Medicine, School of Public Health, Imperial College London, London, UK (Prof N M Ferguson DPhil); and Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA (Prof D S Burke MD)

Correspondence to:Dr C Jessica E Metcalf, Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USAcmetcalf@princeton.edu

See Online for appendix

For more on the Demographic Health Surverys see http://www.dhsprogram.com/

Serology: a Global Immunological Observatory

Cases and deaths:Provide an incomplete window onto the epidemic

Susceptible

Infected

Recovered

Viewpoint

www.thelancet.com Published online April 5, 2016 http://dx.doi.org/10.1016/S0140-6736(16)30164-7 1

Use of serological surveys to generate key insights into the changing global landscape of infectious diseaseC Jessica E Metcalf, Jeremy Farrar, Felicity T Cutts, Nicole E Basta, Andrea L Graham, Justin Lessler, Neil M Ferguson, Donald S Burke, Bryan T Grenfell

A central conundrum in the study of infectious disease dynamics is to defi ne the landscape of population immunity. The proportion of individuals protected against a specifi c pathogen determines the timing and scale of outbreaks, and the pace of evolution for infections that can evade prevailing humoral immunity. Serological surveys provide the most direct measurement to defi ne the immunity landscape for many infectious diseases, yet this methodology remains underexploited. To address this gap, we propose a World Serology Bank and associated major methodological developments in serological testing, study design, and quantitative analysis, which could drive a step change in our understanding and optimum control of infectious diseases.

Epidemic dynamics result from an interaction between the contagious spread of infection, the resulting depletion of population susceptibility, and its replenishment via births, immigration, or waning immunity. Under-standing this interaction is key to assess the eff ect of vaccination, which artifi cially reduces the number of people susceptible to infection.

Researchers mainly observe infection dynamics and the eff ect of population (or herd) immunity in limiting spread via surveillance of clinically apparent cases of infection or deaths. This method has led to some powerful insights;1 however, even in the simplest instances in which subclinical infection is uncommon, cases only provide information about the dynamics of infection. Susceptibility and immunity are hidden variables. For infections that people can be completely immunised against, such as measles, susceptible reconstruction can be used to estimate immune profi les,2 but infection prevalence and vaccination coverage records are frequently inadequate to capture key social and geographical heterogeneities. Additionally, inference is weakened if the risk of infection is low.

Serological surveys (usually used to quantify the proportion of people positive for a specifi c antibody or, better yet, the titre or concentrations of an antibody) are potentially the most direct and informative technique available to infer the dynamics of a population’s susceptibility and level of immunity. However, the use of current serological tests varies greatly depending on type of pathogens and there are major methodological gaps in some areas for some pathogens and tests. In terms of use of current serological methods, infections can be classifi ed into four broad groups (appendix). The fi rst group contains acute immunising, antigenically stable pathogens (eg, measles, rubella, and smallpox) for which serology provides a strong signal of lifetime

protection and a clear marker of past infection (or vaccination).

The second group contains immunising, but antigenically variable pathogens (eg, infl uenza, invasive bacterial diseases, and dengue). Despite complexities (appendix), serology in some cases can provide powerful evidence, both for vaccine formulation and pandemic planning.3,4 A serum bank would have been extremely useful in interpretation of the unusual profi le of susceptibility associated with age in the 2009 infl uenza pandemic.3 For these fi rst two groups, if suitable serum banks existed, the deployment of current serological tests could have helped to clarify the association between serological profi les and protective immunity.

The third group includes infections for which infection-induced antibodies are not thought to be protective, such as tuberculosis in which the targets of the immune response vary with stage of infection; malaria, whereby infected erythrocytes generate several antibodies whose individual importance has not been fully elucidated (and might indicate exposure rather than protection5); and HIV. Although antibodies might not be representative of immunity against a pathogen, they do show current or previous infection.

Finally, the last broad grouping consists of infections that do not lead to reliably sustained, measurable antibody responses or for which presence of specifi c antibodies do not correlate with protection from future infection. These include many enteric infections and the human papillomavirus. In these cases, serological data can nonetheless be valuable to assess a population’s coverage of vaccine programmes if vaccination leads to long-lasting antibody responses.

In the context of public health, for immunisation against group one infections, vaccination programmes aim to protect vaccinated individuals and indirectly protect unvaccinated individuals by maintaining high population immunity.1 If a valid correlate of immunity is measurable in sera, serological surveys could be used to identify population subgroups in which immunity is low, or even to identify individuals in whom immunity has waned, and directly inform targeted vaccination strategies (appendix).

Household surveys are a major source of data for vaccination coverage in low-income countries.6 The recent extension of eff orts to measure biomarkers for infections such as HIV (eg, the Demographic Health Surveys) could provide infrastructure for sera collection for an expanded range of infections, thus leveraging an existing platform. For many infections, however, to

Published OnlineApril 5, 2016http://dx.doi.org/10.1016/S0140-6736(16)30164-7

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA (C J E Metcalf PhD, A L Graham PhD, Prof B T Grenfell PhD); Fogarty International Center, National Institute of Health, Bethesda, MD, USA (C J E Metcalf, N E Basta PhD, A L Graham, Prof B T Grenfell); Wellcome Trust, Gibbs Building, London, UK (J Farrar MD); London School of Hygiene & Tropical Medicine, London, UK (Prof F T Cutts MD);

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA (N E Basta); Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA (J Lessler PhD); Department of Medicine, School of Public Health, Imperial College London, London, UK (Prof N M Ferguson DPhil); and Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA (Prof D S Burke MD)

Correspondence to:Dr C Jessica E Metcalf, Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USAcmetcalf@princeton.edu

See Online for appendix

For more on the Demographic Health Surverys see http://www.dhsprogram.com/

Serology:Measurement of antibodies can complete the picture

Serology: understanding the early phase

0 5 10 15

0.00

0.05

0.10

0.15

0.20

Weeks

Cas

es (u

nder

-rep

orte

d)

true x under-reportingobserved

0 5 10 15

0.2

0.4

0.6

0.8

1.0

WeeksP

ropo

rtion

sus

cept

ible

Serology: understanding the early phase

0 5 10 15

0.00

0.05

0.10

0.15

0.20

Weeks

Cas

es (u

nder

-rep

orte

d)

fittedtrue x under-reportingobserved

0 5 10 15

0.2

0.4

0.6

0.8

1.0

WeeksP

ropo

rtion

sus

cept

ible

fittedtrue

Serology: understanding the early phase

0 5 10 15

0.00

0.05

0.10

0.15

0.20

Weeks

Cas

es (u

nder

-rep

orte

d)

fittedtrue x under-reportingobserved

0 5 10 15

0.2

0.4

0.6

0.8

1.0

WeeksP

ropo

rtion

sus

cept

ible

fittedtrue

Serology: the step-down

What will 'seropositive' mean?

‘Recovereds’ may be recalcitrant to re-infection for at least a season, based on:

-Experimental evidence from beta-coronaviruses -Indirect math models for alpha-coronaviruses -Profile of immunity following COVID-19 infection

Susceptible

Infected

Recovered

www.medrxiv.org/content/10.1101/2020.03.04.20031112v1 www.ncbi.nlm.nih.gov/pmc/articles/PMC2271881/

Testing health care workers, other essential professions could be part of movement to moving back to normality.

Low and Middle Income Countries

Social distancing may be impossible.

Engineering efficient spread of trusted information is essential.

Economic safety nets are urgent.

The backdrop of infection that the pandemic is spreading across is poorly understood.

Malavika Rajeev, Marjolein Bruijning, Fidisoa Rasambainarivo, Benjamin Rice

Open questions

What will be social and economic impact vs. epidemiological advantages of different shut down strategies be?

Will combinations of testing, registration and tracking open the way to advancing the Pandemic Recovery Trajectory?

What can we learn for next time?

EXTRA SLIDES

Estimates from Hubei:R0 between 2 and 3Serial interval ~ 1 week

Not over-dispersed

60% causes 80%

https://twitter.com/JustinLessler/status/1227344703567253505?s=20

Note! this assumes that new infections per infected individuals are ~ consistent.

Over-dispersion

Estimates from Hubei:R0 between 2 and 3Serial interval ~ 1 week

Not over-dispersed

60% causes 80%

Over-dispersed

20% causes 80%

Over-dispersion = rarer onward transmission but potentially more explosive outbreaks.

https://twitter.com/JustinLessler/status/1227375168130928641?s=20

Over-dispersion

Estimates from Hubei:R0 between 2 and 3Serial interval ~ 1 week

Not over-dispersed

60% causes 80%

Over-dispersed

20% causes 80%

100% of introductions cause onward transmission

40% of introductions cause onward transmission

https://twitter.com/JustinLessler/status/1227375168130928641?s=20

Over-dispersion