Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

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Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC
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Transcript of Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Page 1: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Insights from economic-epidemiology

Ramanan LaxminarayanResources for the Future, Washington DC

Page 2: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Economic Epidemiology

Mathematical conceptualization of the interplay between economics, human behavior and disease ecology to improve our understanding of – the emergence, persistence and spread of

infectious agents – optimal strategies and policies to control

their spread

Page 3: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Economics

Measuring health outcomes Provides a single metric to compare costs and

benefits both contemporaneously and over time. Incorporating behavior

Can alter conclusions reached by purely epidemiological models by incorporating behavior.

Comparing public policies Increases relevance for application in the real

world.

Page 4: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Overview

Individual response and disease Incentives of institutions (to invest in

hospital infection control) Optimal allocation of resources between

two regions (or hospitals)

Page 5: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Individual response and disease

Vaccinations– Insufficient incentives to vaccinate prevent

attainment of herd immunity thresholds Drug resistance

– Insufficient incentives to make appropriate use leads to ineffective drugs and increasing prevalence

Testing– Private testing behavior adds to public information

on disease prevalence

Page 6: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Rational epidemics

Prevalence response elasticity– Hazard rate into infection of susceptibles is

a decreasing function of prevalence (opposite of epidemiological model predictions)

– Application to HIV– Application to Measles

Page 7: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Geoffard and Philipson, Int. Econ. Rev., 1996

Page 8: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Blower et al, Science, 2000

Page 9: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Blower et al, Science, 2000

Page 10: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

When should governments intervene?

Disease prevalence increases adoption of public programs

Impact of public program may be zero if prevalence has already reached an individual’s threshold prevalence

Paradoxically, the role of government subsidies is lowest when prevalence is highest since individuals will protect themselves regardless

Page 11: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Philipson, NBER, 1999

Page 12: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Public price subsidies

Can price subsidies or mandatory programs achieve eradication?– Increase in demand by folks covered by

the program lowers the incentives to vaccinate for those outside the program

Do monopolistic vaccine manufacturers have an incentive to eradicate disease?– Market for their product would disappear

with eradicationGeoffard and Philipson, Int Econ Rev, 1997

Page 13: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.
Page 14: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Disease Complementarities

Incentive to invest in prevention against one cause of death depends positively on probability of dying from other causes

Intervening to prevent mortality not only prevents a death but also increases incentives for the family to fight other diseases

Page 15: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Dow et al, Am Econ Rev, 1999

Page 16: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Does the theory fit the facts?

Do individuals actually observe prevalence?

Why don’t we see prevalence responsiveness at work everywhere?

Importance of observational learning (herd behavior)?

Page 17: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Stoneburner and Low-Beer, Science, 2004

Page 18: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Stoneburner and Low-Beer, Science, 2004

Page 19: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Stoneburner and Low-Beer, Science, 2004

Page 20: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

NNIS Data, 2004

Page 21: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Optimal infection control

Infection dynamics are given by

X cX1 X X

Equilibrium prevalence is given by

Xc Sc 1 Sc 1 2 4 Sc

2Sc

Smith, Levin, Laxminarayan (PNAS, 2005)

Page 22: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Objective

Minimize costs of infection control andinfections

c DXc

Smith, Levin, Laxminarayan (PNAS, 2005)

Local minima, if they exist, are solutions to

1 DX ĉ 0

Page 23: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Smith, Levin, Laxminarayan (PNAS, 2005)

Page 24: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

X cX1 X X X Z

Y cY1 Y Y Y Z

Ż rX/n n 1Y/n Z Z

0

c DXt,c;n,ce tdt

The focal institution decides how much to invest in HIC by minimizing the net present value of discounted costs of HIC and hospitalization:

Smith, Levin, Laxminarayan (PNAS, 2005)

Strategic interactions with other hospitals

Page 25: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.
Page 26: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.
Page 27: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.
Page 28: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Implications for policy

Dutch experience: frequency of MRSA infections is < 0.5% after an intensive ‘‘search-and-destroy’’ campaign, compared with 50% in some areas

In Siouxland (Iowa, Nebraska, S. Dakota), an epidemic of VRE was reversed

Regionally coordinated response to epidemic Does this explain higher prevalence of ARB in

areas with high concentration of health care institutions?

Page 29: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Rowthorn, Laxminarayan, Gilligan Submitted

Page 30: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Rowthorn, Laxminarayan, Gilligan Submitted

Page 31: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Rowthorn, Laxminarayan, Gilligan Submitted

Page 32: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Rowthorn, Laxminarayan, Gilligan Submitted

Page 33: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Allocating resources

Expenditure on drugs is subject to the budget constraint

Finance is not transferable through time.

Problem is to choose F₁and F₂ so as to minimise the following integral

V 0

e rtI1 I2 dt

cF1 F2 M

Rowthorn, Laxminarayan, Gilligan Submitted

Page 34: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Optimal allocation

At low levels of infection in both populations– Preferentially treat population with higher

transmission coefficient because of greater economic value associated with greater potential to prevent secondary infections

At high levels of infection– Preferentially treat population with lower levels of

infection since the higher probability of re-infection in high infection populations reduces the economic value of treatment

Rowthorn, Laxminarayan, Gilligan Submitted

Page 35: Insights from economic- epidemiology Ramanan Laxminarayan Resources for the Future, Washington DC.

Best path

Time0 10 20 30 40 50 60 70

Pro

port

ion

infe

cte

d

0.00

0.05

0.10

0.15

0.20Worst path

Time0 10 20 30 40 50 60 70

Pro

port

ion

infe

cte

d

0.0

0.2

0.4

0.6

0.8

Best path

Time0 10 20 30 40 50 60 70

Pro

port

ion

infe

cte

d

0.0

0.2

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1.0Worst path

Time0 10 20 30 40 50 60 70

Pro

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cte

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0.0

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Proportion infected

Region 10.00 0.25 0.50 0.75

Re

gio

n 2

0.00

0.25

0.50

0.75

Time0 35 70

Tre

ate

d

0.0

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1.0

Time0 35 70

Tre

ate

d

0.0

0.5

1.0

Proportion infected

Region 10.00 0.25 0.50 0.75

Re

gio

n 2

0.00

0.25

0.50

0.75

Best path

Time0 10 20 30 40 50 60 70

Pro

port

ion

infe

cte

d

0.00

0.05

0.10

0.15

0.20

Region 1Region 2

Worst path

Time0 10 20 30 40 50 60 70

Pro

port

ion

infe

cte

d

0.00

0.05

0.10

0.15

0.20

Time0 35 70

Tre

ate

d

0.0

0.5

1.0

Proportion infected

Region 10.00 0.06 0.12 0.18

Re

gio

n 2

0.00

0.05

0.10

0.15

0.20

Time0 35 70

Tre

ate

d

0.0

0.5

1.0

Time0 35 70

Tre

ate

d

0.0

0.5

1.0

Time0 35 70

Tre

ate

d

0.0

0.5

1.0

a b c

d e f

g h i

Rowthorn, Laxminarayan, Gilligan Submitted

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Closing thoughts

Epidemiological models take little or no account of economic constraints or incentives faced by individuals or institutions

Economic models mostly ignore the spatial and temporal dynamics of disease.