Two Critical Issues in Quantitative Modeling of Communicable Diseases: Inference of Unobservables and Dependent Happening
Identifieur interne : 002C67 ( Main/Exploration ); précédent : 002C66; suivant : 002C68Two Critical Issues in Quantitative Modeling of Communicable Diseases: Inference of Unobservables and Dependent Happening
Auteurs : Hiroshi Nishiura [Pays-Bas] ; Masayuki Kakehashi [Japon] ; Hisashi Inaba [Japon]Source :
Abstract
Abstract: In this chapter, we discuss two critical issues which must be remembered whenever we examine epidemiologic data of directly transmitted infectious diseases. Firstly, we would like the readers to recognize the difference between observable and unobservable events in infectious disease epidemiology. Since both infection event and acquisition of infectiousness are generally not directly observable, the total number of infected individuals could not be counted at a point of time, unless very rigorous contact tracing and microbiological examinations were performed. Directly observable intrinsic parameters, such as the incubation period and serial interval, play key roles in translating observable to unobservable information. Secondly, the concept of dependent happening must be remembered to identify a risk of an infectious disease or to assess vaccine efficacy. Observation of a single infected individual is not independent of observing other individuals. A simple solution for dependent happening is to employ the transmission probability which is conditioned on an exposure to infection.
Url:
DOI: 10.1007/978-90-481-2313-1_3
Affiliations:
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Firstly, we would like the readers to recognize the difference between observable and unobservable events in infectious disease epidemiology. Since both infection event and acquisition of infectiousness are generally not directly observable, the total number of infected individuals could not be counted at a point of time, unless very rigorous contact tracing and microbiological examinations were performed. Directly observable intrinsic parameters, such as the incubation period and serial interval, play key roles in translating observable to unobservable information. Secondly, the concept of dependent happening must be remembered to identify a risk of an infectious disease or to assess vaccine efficacy. Observation of a single infected individual is not independent of observing other individuals. A simple solution for dependent happening is to employ the transmission probability which is conditioned on an exposure to infection.</div></front></TEI><affiliations><list><country><li>Japon</li><li>Pays-Bas</li></country><region><li>Région de Kantō</li></region><settlement><li>Tokyo</li></settlement><orgName><li>Université de Tokyo</li></orgName></list><tree><country name="Pays-Bas"><noRegion><name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name></noRegion><name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name></country><country name="Japon"><noRegion><name sortKey="Kakehashi, Masayuki" sort="Kakehashi, Masayuki" uniqKey="Kakehashi M" first="Masayuki" last="Kakehashi">Masayuki Kakehashi</name></noRegion><name sortKey="Inaba, Hisashi" sort="Inaba, Hisashi" uniqKey="Inaba H" first="Hisashi" last="Inaba">Hisashi Inaba</name><name sortKey="Kakehashi, Masayuki" sort="Kakehashi, Masayuki" uniqKey="Kakehashi M" first="Masayuki" last="Kakehashi">Masayuki Kakehashi</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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