Abstract

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
JournalEcoHealth
Volume11
Issue number4
DOIs
StatePublished - 2014

Fingerprint

infectious disease
epidemiology
Communicable Diseases
Epidemiology
Economics
prediction
economics
Disease Management
pathogen
Population
decision

Keywords

  • economic epidemiology
  • epidemiological economics
  • incentives
  • infectious disease

ASJC Scopus subject areas

  • Ecology
  • Health, Toxicology and Mutagenesis

Cite this

Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease. / Perrings, Charles; Castillo-Chavez, Carlos; Chowell, Gerardo; Daszak, Peter; Fenichel, Eli P.; Finnoff, David; Horan, Richard D.; Kilpatrick, A. Marm; Kinzig, Ann; Kuminoff, Nicolai; Levin, Simon; Morin, Benjamin; Smith, Katherine F.; Springborn, Michael.

In: EcoHealth, Vol. 11, No. 4, 2014, p. 464-475.

Research output: Contribution to journalArticle

Perrings, C, Castillo-Chavez, C, Chowell, G, Daszak, P, Fenichel, EP, Finnoff, D, Horan, RD, Kilpatrick, AM, Kinzig, A, Kuminoff, N, Levin, S, Morin, B, Smith, KF & Springborn, M 2014, 'Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease', EcoHealth, vol. 11, no. 4, pp. 464-475. https://doi.org/10.1007/s10393-014-0963-6
Perrings, Charles ; Castillo-Chavez, Carlos ; Chowell, Gerardo ; Daszak, Peter ; Fenichel, Eli P. ; Finnoff, David ; Horan, Richard D. ; Kilpatrick, A. Marm ; Kinzig, Ann ; Kuminoff, Nicolai ; Levin, Simon ; Morin, Benjamin ; Smith, Katherine F. ; Springborn, Michael. / Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease. In: EcoHealth. 2014 ; Vol. 11, No. 4. pp. 464-475.
@article{dda746efacdd4f1dad897230c8147656,
title = "Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease",
abstract = "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.",
keywords = "economic epidemiology, epidemiological economics, incentives, infectious disease",
author = "Charles Perrings and Carlos Castillo-Chavez and Gerardo Chowell and Peter Daszak and Fenichel, {Eli P.} and David Finnoff and Horan, {Richard D.} and Kilpatrick, {A. Marm} and Ann Kinzig and Nicolai Kuminoff and Simon Levin and Benjamin Morin and Smith, {Katherine F.} and Michael Springborn",
year = "2014",
doi = "10.1007/s10393-014-0963-6",
language = "English (US)",
volume = "11",
pages = "464--475",
journal = "EcoHealth",
issn = "1612-9202",
publisher = "Springer New York",
number = "4",

}

TY - JOUR

T1 - Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease

AU - Perrings, Charles

AU - Castillo-Chavez, Carlos

AU - Chowell, Gerardo

AU - Daszak, Peter

AU - Fenichel, Eli P.

AU - Finnoff, David

AU - Horan, Richard D.

AU - Kilpatrick, A. Marm

AU - Kinzig, Ann

AU - Kuminoff, Nicolai

AU - Levin, Simon

AU - Morin, Benjamin

AU - Smith, Katherine F.

AU - Springborn, Michael

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - economic epidemiology

KW - epidemiological economics

KW - incentives

KW - infectious disease

UR - http://www.scopus.com/inward/record.url?scp=84925392514&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84925392514&partnerID=8YFLogxK

U2 - 10.1007/s10393-014-0963-6

DO - 10.1007/s10393-014-0963-6

M3 - Article

VL - 11

SP - 464

EP - 475

JO - EcoHealth

JF - EcoHealth

SN - 1612-9202

IS - 4

ER -