Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease

Charles Perrings, Carlos Castillo-Chavez, Gerardo Chowell, Peter Daszak, Eli P. Fenichel, David Finnoff, Richard D. Horan, A. Marm Kilpatrick, Ann P. Kinzig, Nicolai V. Kuminoff, Simon Asher Levin, Benjamin Morin, Katherine F. Smith, Michael Springborn

Research output: Contribution to journalArticlepeer-review

70 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)464-475
Number of pages12
Issue number4
StatePublished - Dec 2014

All Science Journal Classification (ASJC) codes

  • Health, Toxicology and Mutagenesis
  • Ecology


  • economic epidemiology
  • epidemiological economics
  • incentives
  • infectious disease


Dive into the research topics of 'Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease'. Together they form a unique fingerprint.

Cite this