Stochastic Multitype SIR Epidemics among a Population Partitioned into Households
We consider a stochastic model for the spread of an SIR (susceptible → infective → removed) epidemic among a closed, finite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting an...
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Veröffentlicht in: | Advances in applied probability 2001-03, Vol.33 (1), p.99-123 |
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description | We consider a stochastic model for the spread of an SIR (susceptible → infective → removed) epidemic among a closed, finite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the final outcome of epidemics which take off is derived, by exploiting an embedding representation. |
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The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. 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The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the final outcome of epidemics which take off is derived, by exploiting an embedding representation.</description><subject>Approximation</subject><subject>Central limit theorem</subject><subject>Disease models</subject><subject>Epidemics</subject><subject>General Applied Probability</subject><subject>Infections</subject><subject>Mathematical theorems</subject><subject>Mathematics</subject><subject>Perceptron convergence procedure</subject><subject>Random variables</subject><subject>Stochastic models</subject><issn>0001-8678</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNotjDtPwzAYRT2ARGkZ2Rj8B0L9Sm2PqCq0UhEt7V59foQ6SuIodob-eyLBdM89uroIPVPyShnXS4B-qbWmSiqt79CMEEILtZLqAT2mVE-VS0Vm6HjK0V4h5WDx59jkkG-9x6fdN970wfk22IShjd0PBnyI_dhADrHDBxim6UTe4dDliLdxTP4aG5cW6L6CJvmn_5yj8_vmvN4W-6-P3fptX9RK50J6UjlqbalcuQIjhWWGa1sy4JWnkpXcEc-YV5aAobQEyYWZhHFyQmv4HL383dYpx-HSD6GF4XahgikhOP8FuaVN4w</recordid><startdate>20010301</startdate><enddate>20010301</enddate><creator>Ball, Frank</creator><creator>Lyne, Owen D.</creator><general>Applied Probability Trust</general><scope/></search><sort><creationdate>20010301</creationdate><title>Stochastic Multitype SIR Epidemics among a Population Partitioned into Households</title><author>Ball, Frank ; Lyne, Owen D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j89t-7e0fd1cc58d56ab74c2b39c52a3fe17253d0e22e8c0ab115a734be22bd7a73cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Approximation</topic><topic>Central limit theorem</topic><topic>Disease models</topic><topic>Epidemics</topic><topic>General Applied Probability</topic><topic>Infections</topic><topic>Mathematical theorems</topic><topic>Mathematics</topic><topic>Perceptron convergence procedure</topic><topic>Random variables</topic><topic>Stochastic models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ball, Frank</creatorcontrib><creatorcontrib>Lyne, Owen D.</creatorcontrib><jtitle>Advances in applied probability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ball, Frank</au><au>Lyne, Owen D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stochastic Multitype SIR Epidemics among a Population Partitioned into Households</atitle><jtitle>Advances in applied probability</jtitle><date>2001-03-01</date><risdate>2001</risdate><volume>33</volume><issue>1</issue><spage>99</spage><epage>123</epage><pages>99-123</pages><issn>0001-8678</issn><abstract>We consider a stochastic model for the spread of an SIR (susceptible → infective → removed) epidemic among a closed, finite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the final outcome of epidemics which take off is derived, by exploiting an embedding representation.</abstract><pub>Applied Probability Trust</pub><doi>10.1239/aap/999187899</doi><tpages>25</tpages></addata></record> |
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subjects | Approximation Central limit theorem Disease models Epidemics General Applied Probability Infections Mathematical theorems Mathematics Perceptron convergence procedure Random variables Stochastic models |
title | Stochastic Multitype SIR Epidemics among a Population Partitioned into Households |
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