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

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease
Creator	Chowell, Gerardo Daszak, Peter Morin, Benjamin Castillo-Chavez, Carlos Perrings, Charles Finnoff, David Levin, Simon Springborn, Michael Kinzig, Ann Smith, Katherine Horan, Richard Fenichel, Eli Kilpatrick, A Kuminoff, Nicolai
Source	PMC
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.
has issue date	2014-09-19(xsd:dateTime)
bibo:doi	10.1007/s10393-014-0963-6
bibo:pmid	25233829
has license	no-cc
sha1sum (hex)	2bfa631d66f7e59bd7de5316ecc45b9f44352f1b
schema:url	https://doi.org/10.1007/s10393-014-0963-6
resource representing a document's title	Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease
has PubMed Central identifier	PMC4366543
has PubMed identifier	25233829
schema:publication	Ecohealth
resource representing a document's body	covid:2bfa631d66f7e59bd7de5316ecc45b9f44352f1b#body_text
is schema:about of	named entity 'MANAGEMENT' named entity 'INFECTIOUS DISEASE' named entity 'depend' named entity 'epidemiological' named entity 'behavioral' named entity 'Original' named entity 'ECONOMICS' named entity 'EMERGE' named entity 'PATHOGENS' named entity 'ENHANCED' named entity 'POTENTIAL' named entity 'APPROACH' named entity 'DEVELOPMENT' named entity 'MATHEMATICAL BIOLOGY' named entity 'MANAGING' named entity 'CLASSICAL' named entity 'DEPEND' named entity 'HOW' named entity 'PREDICTING' named entity 'INFECTIOUS DISEASE' named entity 'METHODS' named entity 'BEHAVIORAL' named entity 'TYPE' named entity 'POPULATION' named entity 'CONTACTS' named entity 'ADDRESSES' named entity 'INSIGHTS' named entity 'SPREAD' named entity 'CONTRIBUTION' named entity 'ONE OF' named entity 'RATES' named entity 'GENERALLY' named entity 'EPIDEMIOLOGY' named entity 'DETERMINANTS' named entity 'INFECTIOUS' named entity 'SUSCEPTIBLE' named entity 'UNDERSTANDING' named entity 'NOVEL' named entity 'NUMBER' named entity 'DISEASE DYNAMICS' named entity 'COURSE' named entity 'EVOLVE' named entity 'ORIGINAL' named entity 'PREDICTION' named entity 'MERGING' named entity 'EPIDEMIOLOGY' named entity 'CONTACT' named entity 'PREDICTIONS' named entity 'USING' named entity 'DISEASE MANAGEMENT' named entity 'HOST' named entity 'OUR' named entity 'RELATIVE FREQUENCY' named entity 'STANDARD' named entity 'DRIVING' named entity 'FEEDBACKS' named entity 'TO SUPPORT' named entity 'ABOUT' named entity 'A CLASS' named entity 'APPROACHES' named entity 'REFERRED TO' named entity 'MODELS' named entity 'THEIR' named entity 'DECISIONS' named entity 'AREAS' named entity 'INDIVIDUALS' named entity 'MATHEMATICAL' named entity 'ECONOMICS'

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