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An optimization model for reducing typhoid cases in developing countries without increasing public spending

Authors
Journal
Vaccine
0264-410X
Publisher
Elsevier
Publication Date
Volume
27
Issue
10
Identifiers
DOI: 10.1016/j.vaccine.2008.12.032
Keywords
  • Typhoid Vaccine
  • Policy
  • Optimization
  • User Charges
  • Vaccine Demand
Disciplines
  • Mathematics
  • Political Science

Abstract

Abstract This article considers the investment case for using the Vi polysaccharide vaccine in developing countries from two perspectives: reducing typhoid cases and limiting new health care spending. A case study is presented using data from South and Southeast Asia. The purpose of the paper, however, is to draw broad implications that may apply to developing countries in general. Typical consumer demand functions developed from stated preference household surveys in South and Southeast Asia are used to predict probabilities of adults and children purchasing typhoid vaccinations at different prices. These functions are incorporated in a formal mathematical model. Using data from the recent literature for South and Southeast Asia for typhoid incidence, Vi vaccine effectiveness, public cost of illness, and vaccination program cost, three mass vaccination policy alternatives are evaluated: charging adults and children different (optimal) prices, charging uniform prices, and providing free vaccines. Assuming differential pricing is politically feasible, different vaccine prices for children and adults would maximize the number of typhoid cases avoided from a mass vaccination program if the public sector faces a budget constraint on spending for the vaccination program. However, equal prices for children and adults produce very similar results, and they might be more readily accepted by the community. Alternatively, if vaccines are free, the number of cases is not significantly reduced compared to either pricing policy, but a large external financial contribution from government or donors would be required. A Monte Carlo simulation explores the effects of uncertain parameters on vaccination program outcomes.

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