Episodic outbreaks bias estimates of age-specific force of infection: a corrected method using measles as an example.

Hdl Handle:
http://hdl.handle.net/10144/98914
Title:
Episodic outbreaks bias estimates of age-specific force of infection: a corrected method using measles as an example.
Authors:
Ferrari, M J; Djibo, A; Grais, R F; Grenfell, B T; Bjørnstad, O N
Journal:
Epidemiology and Infection
Abstract:
Understanding age-specific differences in infection rates can be important in predicting the magnitude of and mortality in outbreaks and targeting age groups for vaccination programmes. Standard methods to estimate age-specific rates assume that the age-specific force of infection is constant in time. However, this assumption may easily be violated in the face of a highly variable outbreak history, as recently observed for acute immunizing infections like measles, in strongly seasonal settings. Here we investigate the biases that result from ignoring such fluctuations in incidence and present a correction based on the epidemic history. We apply the method to data from a measles outbreak in Niamey, Niger and show that, despite a bimodal age distribution of cases, the estimated age-specific force of infection is unimodal and concentrated in young children (<5 years) consistent with previous analyses of age-specific rates in the region.
Affiliation:
Center for Infectious Disease Dynamics, Penn State University, PA 16802, USA. mferrari@psu.edu
Publisher:
Cambridge University Press
Issue Date:
Jan-2010
URI:
http://hdl.handle.net/10144/98914
DOI:
10.1017/S0950268809990173
PubMed ID:
19538818
Language:
en
ISSN:
1469-4409
Appears in Collections:
Research Methods

Full metadata record

DC FieldValue Language
dc.contributor.authorFerrari, M Jen
dc.contributor.authorDjibo, Aen
dc.contributor.authorGrais, R Fen
dc.contributor.authorGrenfell, B Ten
dc.contributor.authorBjørnstad, O Nen
dc.date.accessioned2010-05-15T16:30:52Z-
dc.date.available2010-05-15T16:30:52Z-
dc.date.issued2010-01-
dc.identifier.citationEpisodic outbreaks bias estimates of age-specific force of infection: a corrected method using measles as an example. 2010, 138 (1):108-16 Epidemiol. Infect.en
dc.identifier.issn1469-4409-
dc.identifier.pmid19538818-
dc.identifier.doi10.1017/S0950268809990173-
dc.identifier.urihttp://hdl.handle.net/10144/98914-
dc.description.abstractUnderstanding age-specific differences in infection rates can be important in predicting the magnitude of and mortality in outbreaks and targeting age groups for vaccination programmes. Standard methods to estimate age-specific rates assume that the age-specific force of infection is constant in time. However, this assumption may easily be violated in the face of a highly variable outbreak history, as recently observed for acute immunizing infections like measles, in strongly seasonal settings. Here we investigate the biases that result from ignoring such fluctuations in incidence and present a correction based on the epidemic history. We apply the method to data from a measles outbreak in Niamey, Niger and show that, despite a bimodal age distribution of cases, the estimated age-specific force of infection is unimodal and concentrated in young children (<5 years) consistent with previous analyses of age-specific rates in the region.en
dc.language.isoenen
dc.publisherCambridge University Pressen
dc.rightsArchived with thanks to Epidemiology and Infection and Cambridge University Pressen
dc.subject.meshAdolescenten
dc.subject.meshAge Distributionen
dc.subject.meshBias (Epidemiology)en
dc.subject.meshChilden
dc.subject.meshChild, Preschoolen
dc.subject.meshDisease Outbreaksen
dc.subject.meshFemaleen
dc.subject.meshHumansen
dc.subject.meshIncidenceen
dc.subject.meshInfanten
dc.subject.meshInfant, Newbornen
dc.subject.meshMaleen
dc.subject.meshMeaslesen
dc.subject.meshModels, Biologicalen
dc.subject.meshNigeren
dc.titleEpisodic outbreaks bias estimates of age-specific force of infection: a corrected method using measles as an example.en
dc.contributor.departmentCenter for Infectious Disease Dynamics, Penn State University, PA 16802, USA. mferrari@psu.eduen
dc.identifier.journalEpidemiology and Infectionen

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