About: Estimating Force of Infection from Serologic Surveys with Imperfect Tests

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Estimating Force of Infection from Serologic Surveys with Imperfect Tests
Creator	Carabali, Mabel Alexander, Neal Lim, Jacqueline
source	MedRxiv
abstract	The force of infection, or the rate at which susceptible individuals become infected, is an important public health measure for assessing the extent of outbreaks and the impact of control programs. Here we present methods for estimating force of infection from serological surveys of infections which produce lasting immunity, taking into account imperfections in the test used, and uncertainty in such imperfections. The methods cover both single serological surveys, in which age is a proxy for time at risk, and repeat surveys in the same people, in which the force of infection is estimated more directly. Fixed values can be used for the sensitivity and specificity of the tests, or existing methods for belief elicitation can be used to include uncertainty in these values. The latter may be applicable, for example, when the specificity of a test depends on co-circulating pathogens, which may not have been well characterized in the setting of interest. We illustrate the methods using data from two published serological studies of dengue.
has issue date	2020-06-11(xsd:dateTime)
bibo:doi	10.1101/2020.06.09.20125724
has license	medrxiv
sha1sum (hex)	8cc35789446cf0ef61a2f24d0eee3a85a53f9340
schema:url	https://doi.org/10.1101/2020.06.09.20125724
resource representing a document's title	Estimating Force of Infection from Serologic Surveys with Imperfect Tests
resource representing a document's body	covid:8cc35789446cf0ef61a2f24d0eee3a85a53f9340#body_text
is schema:about of	named entity 'programs' named entity 'impact' named entity 'test' named entity 'values' named entity 'risk' »more»

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