Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile.
Identifieur interne : 000564 ( PubMed/Curation ); précédent : 000563; suivant : 000565Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile.
Auteurs : Raimund Bürger [Chili] ; Gerardo Chowell ; Pep Mulet ; Luis M. VilladaSource :
- Mathematical biosciences and engineering : MBE [ 1551-0018 ] ; 2016.
Descripteurs français
- KwdFr :
- Analyse spatio-temporelle, Chili (épidémiologie), Grippe humaine (transmission), Grippe humaine (virologie), Grippe humaine (épidémiologie), Hospitalisation (), Humains, Incidence, Pandémies (), Population urbaine (), Sous-type H1N1 du virus de la grippe A, Surveillance de la population (), Évaluation des risques ().
- MESH :
English descriptors
- KwdEn :
- Chile (epidemiology), Hospitalization (statistics & numerical data), Humans, Incidence, Influenza A Virus, H1N1 Subtype, Influenza, Human (epidemiology), Influenza, Human (transmission), Influenza, Human (virology), Pandemics (statistics & numerical data), Population Surveillance (methods), Risk Assessment (methods), Spatio-Temporal Analysis, Urban Population (statistics & numerical data).
- MESH :
- epidemiology : Chile, Influenza, Human.
- methods : Population Surveillance, Risk Assessment.
- statistics & numerical data : Hospitalization, Pandemics, Urban Population.
- transmission : Influenza, Human.
- virology : Influenza, Human.
- Humans, Incidence, Influenza A Virus, H1N1 Subtype, Spatio-Temporal Analysis.
Abstract
A spatial-temporal transmission model of 2009 A/H1N1 pandemic influenza across Chile, a country that spans a large latitudinal range, is developed to characterize the spatial variation in peak timing of that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chilean regions, and the putative location of introduction of the novel virus into the country. Specifically, a metapopulation SEIR (susceptible-exposed-infected-removed) compartmental model that tracks the transmission dynamics of influenza in 15 Chilean regions is calibrated. The model incorporates population mobility among neighboring regions and indirect mobility to and from other regions via the metropolitan central region ('hub region'). The stability of the disease-free equilibrium of this model is analyzed and compared with the corresponding stability in each region, concluding that stability may occur even with some regions having basic reproduction numbers above 1. The transmission model is used along with epidemiological data to explore potential factors that could have driven the spatial-temporal progression of the pandemic. Simulations and sensitivity analyses indicate that this relatively simple model is sufficient to characterize the south-north gradient in peak timing observed during the pandemic, and suggest that south Chile observed the initial spread of the pandemic virus, which is in line with a retrospective epidemiological study. The 'hub region' in our model significantly enhanced population mixing in a short time scale.
DOI: 10.3934/mbe.2016.13.43
PubMed: 26776260
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Villada</name></author></analytic><series><title level="j">Mathematical biosciences and engineering : MBE</title><idno type="eISSN">1551-0018</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Chile (epidemiology)</term><term>Hospitalization (statistics & numerical data)</term><term>Humans</term><term>Incidence</term><term>Influenza A Virus, H1N1 Subtype</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (transmission)</term><term>Influenza, Human (virology)</term><term>Pandemics (statistics & numerical data)</term><term>Population Surveillance (methods)</term><term>Risk Assessment (methods)</term><term>Spatio-Temporal Analysis</term><term>Urban Population (statistics & numerical data)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse spatio-temporelle</term><term>Chili (épidémiologie)</term><term>Grippe humaine (transmission)</term><term>Grippe humaine (virologie)</term><term>Grippe humaine (épidémiologie)</term><term>Hospitalisation ()</term><term>Humains</term><term>Incidence</term><term>Pandémies ()</term><term>Population urbaine ()</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population ()</term><term>Évaluation des risques ()</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Chile</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Population Surveillance</term><term>Risk Assessment</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Hospitalization</term><term>Pandemics</term><term>Urban Population</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Chili</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Humans</term><term>Incidence</term><term>Influenza A Virus, H1N1 Subtype</term><term>Spatio-Temporal Analysis</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse spatio-temporelle</term><term>Hospitalisation</term><term>Humains</term><term>Incidence</term><term>Pandémies</term><term>Population urbaine</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Surveillance de la population</term><term>Évaluation des risques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A spatial-temporal transmission model of 2009 A/H1N1 pandemic influenza across Chile, a country that spans a large latitudinal range, is developed to characterize the spatial variation in peak timing of that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chilean regions, and the putative location of introduction of the novel virus into the country. Specifically, a metapopulation SEIR (susceptible-exposed-infected-removed) compartmental model that tracks the transmission dynamics of influenza in 15 Chilean regions is calibrated. The model incorporates population mobility among neighboring regions and indirect mobility to and from other regions via the metropolitan central region ('hub region'). The stability of the disease-free equilibrium of this model is analyzed and compared with the corresponding stability in each region, concluding that stability may occur even with some regions having basic reproduction numbers above 1. The transmission model is used along with epidemiological data to explore potential factors that could have driven the spatial-temporal progression of the pandemic. Simulations and sensitivity analyses indicate that this relatively simple model is sufficient to characterize the south-north gradient in peak timing observed during the pandemic, and suggest that south Chile observed the initial spread of the pandemic virus, which is in line with a retrospective epidemiological study. The 'hub region' in our model significantly enhanced population mixing in a short time scale. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26776260</PMID><DateCompleted><Year>2016</Year><Month>10</Month><Day>17</Day></DateCompleted><DateRevised><Year>2018</Year><Month>10</Month><Day>23</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1551-0018</ISSN><JournalIssue CitedMedium="Internet"><Volume>13</Volume><Issue>1</Issue><PubDate><Year>2016</Year><Month>Feb</Month></PubDate></JournalIssue><Title>Mathematical biosciences and engineering : MBE</Title><ISOAbbreviation>Math Biosci Eng</ISOAbbreviation></Journal><ArticleTitle>Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile.</ArticleTitle><Pagination><MedlinePgn>43-65</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3934/mbe.2016.13.43</ELocationID><Abstract><AbstractText>A spatial-temporal transmission model of 2009 A/H1N1 pandemic influenza across Chile, a country that spans a large latitudinal range, is developed to characterize the spatial variation in peak timing of that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chilean regions, and the putative location of introduction of the novel virus into the country. Specifically, a metapopulation SEIR (susceptible-exposed-infected-removed) compartmental model that tracks the transmission dynamics of influenza in 15 Chilean regions is calibrated. The model incorporates population mobility among neighboring regions and indirect mobility to and from other regions via the metropolitan central region ('hub region'). The stability of the disease-free equilibrium of this model is analyzed and compared with the corresponding stability in each region, concluding that stability may occur even with some regions having basic reproduction numbers above 1. The transmission model is used along with epidemiological data to explore potential factors that could have driven the spatial-temporal progression of the pandemic. Simulations and sensitivity analyses indicate that this relatively simple model is sufficient to characterize the south-north gradient in peak timing observed during the pandemic, and suggest that south Chile observed the initial spread of the pandemic virus, which is in line with a retrospective epidemiological study. 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