Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease
C. Perrings,C. Castillo-Chavez,G. Chowell,P. Daszak,Eli P. Fenichel,D. Finnoff,R. Horan,A. Kilpatrick,A. Kinzig,N. Kuminoff,S. Levin,B. Morin,Katherine F. Smith,Michael R. Springborn
Published 2014 in EcoHealth
ABSTRACT
PUBLICATION RECORD
- Publication year
2014
- Venue
EcoHealth
- Publication date
2014-09-19
- Fields of study
Medicine, Economics, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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