Searching for Superspreaders: Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models
Identifieur interne : 000813 ( Main/Exploration ); précédent : 000812; suivant : 000814Searching for Superspreaders: Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models
Auteurs :Source :
- Understanding Complex Biological Systems with Mathematics ; 2018.
Abstract
The importance of host transmissibility in disease emergence has been demonstrated in historical and recent pandemics that involve infectious individuals, known as superspreaders, who are capable of transmitting the infection to a large number of susceptible individuals. To investigate the impact of superspreaders on epidemic dynamics, we formulate deterministic and stochastic models that incorporate differences in superspreaders versus nonsuperspreaders. In particular, continuous-time Markov chain models are used to investigate epidemic features associated with the presence of superspreaders in a population. We parameterize the models for two case studies, Middle East respiratory syndrome (MERS) and Ebola. Through mathematical analysis and numerical simulations, we find that the probability of outbreaks increases and time to outbreaks decreases as the prevalence of superspreaders increases in the population. In particular, as disease outbreaks occur more rapidly and more frequently when initiated by superspreaders, our results emphasize the need for expeditious public health interventions.
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DOI: 10.1007/978-3-319-98083-6_1
PubMed: NONE
PubMed Central: 7123311
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Searching for Superspreaders: Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models</title></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmc">7123311</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123311</idno><idno type="RBID">PMC:7123311</idno><idno type="doi">10.1007/978-3-319-98083-6_1</idno><idno type="pmid">NONE</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">000220</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000220</idno><idno type="wicri:Area/Pmc/Curation">000220</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000220</idno><idno type="wicri:Area/Pmc/Checkpoint">000468</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000468</idno><idno type="wicri:Area/Ncbi/Merge">002D17</idno><idno type="wicri:Area/Ncbi/Curation">002D17</idno><idno type="wicri:Area/Ncbi/Checkpoint">002D17</idno><idno type="wicri:Area/Main/Merge">000816</idno><idno type="wicri:Area/Main/Curation">000813</idno><idno type="wicri:Area/Main/Exploration">000813</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Searching for Superspreaders: Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models</title></analytic><series><title level="j">Understanding Complex Biological Systems with Mathematics</title><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="Par1">The importance of host transmissibility in disease emergence has been demonstrated in historical and recent pandemics that involve infectious individuals, known as superspreaders, who are capable of transmitting the infection to a large number of susceptible individuals. To investigate the impact of superspreaders on epidemic dynamics, we formulate deterministic and stochastic models that incorporate differences in superspreaders versus nonsuperspreaders. In particular, continuous-time Markov chain models are used to investigate epidemic features associated with the presence of superspreaders in a population. We parameterize the models for two case studies, Middle East respiratory syndrome (MERS) and Ebola. Through mathematical analysis and numerical simulations, we find that the probability of outbreaks increases and time to outbreaks decreases as the prevalence of superspreaders increases in the population. In particular, as disease outbreaks occur more rapidly and more frequently when initiated by superspreaders, our results emphasize the need for expeditious public health interventions.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Allen, Ljs" uniqKey="Allen L">LJS Allen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Allen, Ljs" uniqKey="Allen L">LJS Allen</name></author><author><name sortKey="Lahodny, Ge" uniqKey="Lahodny G">GE Lahodny</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Allen, Ljs" uniqKey="Allen L">LJS Allen</name></author><author><name sortKey="Van Den Driessche, P" uniqKey="Van Den Driessche P">P van den Driessche</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Athreya, Kb" uniqKey="Athreya K">KB Athreya</name></author><author><name sortKey="Ney, Pe" uniqKey="Ney P">PE 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