insights from economic- epidemiology ramanan laxminarayan resources for the future, washington dc
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Insights from economic-epidemiology
Ramanan LaxminarayanResources for the Future, Washington DC
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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
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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.
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Overview
Individual response and disease Incentives of institutions (to invest in
hospital infection control) Optimal allocation of resources between
two regions (or hospitals)
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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
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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
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Geoffard and Philipson, Int. Econ. Rev., 1996
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Blower et al, Science, 2000
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Blower et al, Science, 2000
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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
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Philipson, NBER, 1999
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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
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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
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Dow et al, Am Econ Rev, 1999
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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)?
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Stoneburner and Low-Beer, Science, 2004
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Stoneburner and Low-Beer, Science, 2004
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Stoneburner and Low-Beer, Science, 2004
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NNIS Data, 2004
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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)
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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
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Smith, Levin, Laxminarayan (PNAS, 2005)
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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
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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?
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Rowthorn, Laxminarayan, Gilligan Submitted
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Rowthorn, Laxminarayan, Gilligan Submitted
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Rowthorn, Laxminarayan, Gilligan Submitted
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Rowthorn, Laxminarayan, Gilligan Submitted
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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
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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
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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
0.4
0.6
0.8
1.0Worst 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
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
0.5
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.