A branching model for the spread of infectious animal diseases in varying environments
Identifieur interne : 005A06 ( Main/Exploration ); précédent : 005A05; suivant : 005A07A branching model for the spread of infectious animal diseases in varying environments
Auteurs : Pieter Trapman [Pays-Bas] ; Ronald Meester [Pays-Bas] ; Hans Heesterbeek [Pays-Bas]Source :
- Journal of Mathematical Biology [ 0303-6812 ] ; 2004-12-01.
Descripteurs français
- KwdFr :
- MESH :
- médecine vétérinaire : Flambées de maladies.
- épidémiologie : Pays-Bas, Peste porcine classique.
- Animaux, Flambées de maladies, Modèles biologiques, Méthodes épidémiologiques, Peste porcine classique, Processus stochastiques, Suidae.
English descriptors
- KwdEn :
- Animals, Branching process, Classical Swine Fever (epidemiology), Classical Swine Fever (prevention & control), Classical Swine Fever (transmission), Classical Swine Fever Virus (growth & development), Disease Outbreaks (prevention & control), Disease Outbreaks (veterinary), Epidemiologic Methods, Iterative method, Models, Biological, Netherlands (epidemiology), Stochastic Processes, Stochastic epidemic, Swine, Varying environments.
- MESH :
- epidemiology : Classical Swine Fever, Netherlands.
- growth & development : Classical Swine Fever Virus.
- prevention & control : Classical Swine Fever, Disease Outbreaks.
- transmission : Classical Swine Fever.
- veterinary : Disease Outbreaks.
- Animals, Epidemiologic Methods, Models, Biological, Stochastic Processes, Swine.
Abstract
Abstract.: This paper is concerned with a stochastic model, describing outbreaks of infectious diseases that have potentially great animal or human health consequences, and which can result in such severe economic losses that immediate sets of measures need to be taken to curb the spread. During an outbreak of such a disease, the environment that the infectious agent experiences is therefore changing due to the subsequent control measures taken. In our model, we introduce a general branching process in a changing (but not random) environment. With this branching process, we estimate the probability of extinction and the expected number of infected individuals for different control measures. We also use this branching process to calculate the generating function of the number of infected individuals at any given moment. The model and methods are designed using important infections of farmed animals, such as classical swine fever, foot-and-mouth disease and avian influenza as motivating examples, but have a wider application, for example to emerging human infections that lead to strict quarantine of cases and suspected cases (e.g. SARS) and contact and movement restrictions.
Url:
DOI: 10.1007/s00285-004-0267-5
Affiliations:
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Le document en format XML
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Biol.</title><idno type="ISSN">0303-6812</idno><idno type="eISSN">1432-1416</idno><imprint><publisher>Springer-Verlag</publisher><pubPlace>Berlin/Heidelberg</pubPlace><date type="published" when="2004-12-01">2004-12-01</date><biblScope unit="volume">49</biblScope><biblScope unit="issue">6</biblScope><biblScope unit="page" from="553">553</biblScope><biblScope unit="page" to="576">576</biblScope></imprint><idno type="ISSN">0303-6812</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0303-6812</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Branching process</term><term>Classical Swine Fever (epidemiology)</term><term>Classical Swine Fever (prevention & control)</term><term>Classical Swine Fever (transmission)</term><term>Classical Swine Fever Virus (growth & development)</term><term>Disease Outbreaks (prevention & control)</term><term>Disease Outbreaks (veterinary)</term><term>Epidemiologic Methods</term><term>Iterative method</term><term>Models, Biological</term><term>Netherlands (epidemiology)</term><term>Stochastic Processes</term><term>Stochastic epidemic</term><term>Swine</term><term>Varying environments</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Animaux</term><term>Flambées de maladies ()</term><term>Flambées de maladies (médecine vétérinaire)</term><term>Modèles biologiques</term><term>Méthodes épidémiologiques</term><term>Pays-Bas (épidémiologie)</term><term>Peste porcine classique ()</term><term>Peste porcine classique (transmission)</term><term>Peste porcine classique (épidémiologie)</term><term>Processus stochastiques</term><term>Suidae</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Classical Swine Fever</term><term>Netherlands</term></keywords><keywords scheme="MESH" qualifier="growth & development" xml:lang="en"><term>Classical Swine Fever Virus</term></keywords><keywords scheme="MESH" qualifier="médecine vétérinaire" xml:lang="fr"><term>Flambées de maladies</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Classical Swine Fever</term><term>Disease Outbreaks</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Classical Swine Fever</term></keywords><keywords scheme="MESH" qualifier="veterinary" xml:lang="en"><term>Disease Outbreaks</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Pays-Bas</term><term>Peste porcine classique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Epidemiologic Methods</term><term>Models, Biological</term><term>Stochastic Processes</term><term>Swine</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Animaux</term><term>Flambées de maladies</term><term>Modèles biologiques</term><term>Méthodes épidémiologiques</term><term>Peste porcine classique</term><term>Processus stochastiques</term><term>Suidae</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract.: This paper is concerned with a stochastic model, describing outbreaks of infectious diseases that have potentially great animal or human health consequences, and which can result in such severe economic losses that immediate sets of measures need to be taken to curb the spread. During an outbreak of such a disease, the environment that the infectious agent experiences is therefore changing due to the subsequent control measures taken. In our model, we introduce a general branching process in a changing (but not random) environment. With this branching process, we estimate the probability of extinction and the expected number of infected individuals for different control measures. We also use this branching process to calculate the generating function of the number of infected individuals at any given moment. The model and methods are designed using important infections of farmed animals, such as classical swine fever, foot-and-mouth disease and avian influenza as motivating examples, but have a wider application, for example to emerging human infections that lead to strict quarantine of cases and suspected cases (e.g. SARS) and contact and movement restrictions.</div></front></TEI><affiliations><list><country><li>Pays-Bas</li></country><region><li>Utrecht (province)</li></region><settlement><li>Utrecht</li></settlement><orgName><li>Université d'Utrecht</li></orgName></list><tree><country name="Pays-Bas"><region name="Utrecht (province)"><name sortKey="Trapman, Pieter" sort="Trapman, Pieter" uniqKey="Trapman P" first="Pieter" last="Trapman">Pieter Trapman</name></region><name sortKey="Heesterbeek, Hans" sort="Heesterbeek, Hans" uniqKey="Heesterbeek H" first="Hans" last="Heesterbeek">Hans Heesterbeek</name><name sortKey="Meester, Ronald" sort="Meester, Ronald" uniqKey="Meester R" first="Ronald" last="Meester">Ronald Meester</name><name sortKey="Trapman, Pieter" sort="Trapman, Pieter" uniqKey="Trapman P" first="Pieter" last="Trapman">Pieter Trapman</name><name sortKey="Trapman, Pieter" sort="Trapman, Pieter" uniqKey="Trapman P" first="Pieter" last="Trapman">Pieter Trapman</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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