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2007-08-27 | Peer Reviewed

Using Private Demand Studies to Calculate Socially Optimal Vaccine Subsidies in Developing Countries

Whittington, Dale. 2007. “Using Private Demand Studies to Calculate Socially Optimal Vaccine Subsidies in Developing Countries.” : .
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Although it is well known that vaccines against many infectious diseases confer
positive economic externalities via indirect protection, analysts have typically
ignored possible herd protection effects in policy analyses of vaccination programs.
Despite a growing literature on the economic theory of vaccine externalities and
several innovative mathematical modeling approaches, there have been almost no
empirical applications.

The first objective of the paper is to develop a transparent, accessible economic
framework for assessing the private and social economic benefits of vaccination.
We also describe how stated preference studies (for example, contingent valuation
and choice modeling) can be useful sources of economic data for this analytic
framework. We demonstrate socially optimal policies using a graphical approach,
starting with a standard textbook depiction of Pigouvian subsidies applied to herd
protection from vaccination programs. We also describe nonstandard depictions
that highlight some counterintuitive implications of herd protection that we feel
are not commonly understood in the applied policy literature.
We illustrate the approach using economic and epidemiological data from two
neighborhoods in Kolkata, India. We use recently published epidemiological data
on the indirect effects of cholera vaccination in Matlab, Bangladesh (Ali et al.,
2005) for fitting a simple mathematical model of how protection changes with
vaccine coverage. We use new data on costs and private demand for cholera vaccines
in Kolkata, India, and approximate the optimal Pigouvian subsidy. We find
that if the optimal subsidy is unknown, selling vaccines at full marginal cost may,
under some circumstances, be a preferable second-best option to providing them
for free. © 2009 by the Association for Public Policy Analysis and Management.