Talk
details:
Speaker: Frederick H. Chen
Title: Voluntary Vaccinations with Rational Expectations
Abstract:
The dynamics of an epidemic model with voluntary vaccinations
are analyzed. As is customary in economics, it is assumed
that agents in the model are forward-looking and have rational
expectations. That is, when they are deciding whether to vaccinate
or not, they consider all the possible future consequences
of their action, and, moreover, their estimates of the likelihood
of future events occurring are correct. It is shown that,
when vaccine efficacy is low, there are parameter values for
which multiple steady state equilibria and periodic equilibria
coexist. When multiplicity of steady states obtains, which
one the model converges to in some cases depends entirely
on agents' expectations concerning the future course of an
epidemic and not on the initial conditions of the model.
Speaker: Chris Bauch
Title: Spatial localization of transmission prevents
the free-rider problem in voluntary vaccination policy
Abstract:
Smallpox was globally eradicated several decades ago, and
in many jurisdictions this occurred under a voluntary vaccination
policy. However, game theory has indicated that this should
not have been possible: herd immunity means that the individual
incentive to vaccinate disappears once vaccine coverage is
sufficiently high, if there is even a small risk associated
with the vaccine. Thus, a high level of vaccine coverage under
a voluntary vaccination policy is not a Nash Equilibrium.
Both game theoretical and non-game theoretical analyses of
this "free rider problem", or "tragedy of the
commons" have usually assumed a significant degree of
homogeneous mixing in infectious disease transmission. Here,
we show that the free rider problem disappears once disease
transmission is spatially localized. In a random network through
which a generic SIR-type epidemic is spreading, and where
individuals choose whether or not to vaccinate based on infection
and vaccine risks, the free rider effect does not emerge until
the average neighbourhood size exceeds 40-60 neighbours. Beyond
this threshold, the free rider effect can result in large
final epidemic sizes. Similar effects are observed with smallpox-specific
parameters and natural history assumptions. This work suggests
that the free rider problem may not be an issue for treatable/preventable
diseases spread primarily through close contact, such as smallpox
and several sexually-transmitted infections. It also suggests
network models might be more appropriate for such diseases,
particularly where prevalence-behaviour interactions must
be incorporated.
Speaker: Eunha Shim
Title: Game theoric approach to epidemiological modeling
using antiviral drug use during influenza and rubella vaccination
as examples.
Abstract:
In general, the vaccination level determined by Nash strategy
is lower than the utilitarian optimum, since unvaccinated
individuals can benefit from reduced transmission in a community.
However, this generalization is no longer applied to the case
of rubella vaccination and antiviral drug use during pandemic
influenza due to gender-dependent motivation and resistance,
respectively. During pandemic influenza, individuals may experience
adverse effects of
antivirals although they benefits from reduced probability
and/or severity of infection. Within the community, antiviral
intervention reduces transmission, but also selects for drug
resistance. To evaluate how the balance among these factors
results in optimal coverage for both the individual and the
community, we developed an epidemiological game-theoretic
model of pandemic influenza. We parameterize the model with
survey data on actual perceptions regarding infection risk,
the level of resistance, the efficacy and adverse effects
of antivirals, and the willingness to pay for antivirals during
pandemic influenza. We find that the demand for antivirals
driven by self-interest during pandemic influenza would likely
be far lower than that which would maximize overall utility
for the population. For the case of rubella, individual decision
of a male to reject vaccination indirectly harms females by
increasing both the prevalence of the disease, resulting in
the increased risk of CRS. Therefore, women have higher individual
incentive to vaccinate against rubella than men whose symptoms
are minor, if any. To determine how individual (Nash strategy)
and community (utilitarian strategy) optimum levels of
accination against rubella are affected by various factors,
we present an age-structured epidemiological model in the
context of game theory.
Speaker: Sanjay Basu
Title: Achieving effective HPV vaccination levels in
the United States: a game-theoretic modeling study
Abstract:
Background:
HPV vaccines provide an opportunity to reduce the incidence
of cervical cancer. The optimization of public health policies
to reduce cervical cancer requires anticipating the degree
to which the public will adhere to vaccination recommendations.
Methodology:
We develop an epidemiological game theoretic model of HPV
vaccination to identify potential misalignments between utilitarian
vaccination
levels that are optimal for the community and those that maximize
the utility for an individual. We parameterize our model with
survey data
regarding actual perceptions about cervical cancer, genital
warts, and vaccination against HPV, collected from parents
of vaccine-eligible
children.
Principal Findings/Significance:
We find that vaccination levels based on the perceptions of
our survey respondents are much lower than vaccination levels
that would maximize overall health and economic benefit to
the community. We also find that addressing concerns about
vaccination among parents of potential recipients may help
achieve vaccination targets. However, the cost of vaccination
is a more significant impediment to achieving effective vaccination
levels, even in the context of the subsidization and cost-sharing
schemes that are currently available.
Speaker: Timothy Reluga
Title: The effects of life history on risky behavior
choice and disease transmission
Abstract:
Several population-game models of reasoned choice in the context
of epidemics have addressed cases where individuals occupy
a single life-history stage, with fixed costs for various
actions. However, for many diseases, the costs and consequences
of infection depend on the age of the individual at the time
of infection, and individuals may vary their behaviors in
response to changes in costs or future expectations. Dealing
with the resulting multi-dimensional problem can present computational
and conceptual challenges. This talk will present some methods
for the analyses of population games with age-dependent strategies.
Results including Nash and ESS properties will be established
for some example epidemic models. I'll discuss the implications
for planning control of endemic diseases and for population-game
modelling in general.
