title: Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis.
abstract: Traditional cost-effectiveness analysis (CEA) assumes that program costs and benefits scale linearly with investment-an unrealistic assumption for epidemic control programs. This paper combines epidemic modeling with optimization techniques to determine the optimal allocation of a limited resource for epidemic control among multiple noninteracting populations. We show that the optimal resource allocation depends on many factors including the size of each population, the state of the epidemic in each population before resources are allocated (e.g. infection prevalence and incidence), the length of the time horizon, and prevention program characteristics. We establish conditions that characterize the optimal solution in certain cases.
authors.affiliation: Department of Management Science and Engineering, Stanford University, Terman Building, Stanford, CA 94305, USA. brandeau@stanford.edu
authors.forename: Margaret L
authors.initials: ML
authors.lastname: Brandeau
authors.forename: Gregory S
authors.initials: GS
authors.lastname: Zaric
authors.forename: Anke
authors.initials: A
authors.lastname: Richter
mesh_terms: D003140:Communicable Disease Control / Q000191:economics*; D003362:Cost-Benefit Analysis; D004196:Disease Outbreaks / Q000191:economics / Q000517:prevention & control*; D014943:Global Health; D006301:Health Services Needs and Demand / Q000191:economics / Q000706:statistics & numerical data; D006801:Humans; D017059:Models, Econometric; D015995:Prevalence; D019057:Quality-Adjusted Life Years; D040841:Resource Allocation / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data