Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile
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 timingof that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chil...
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| Format: | Article |
| Language: | English |
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AIMS Press
2015-09-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.43 |
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| author | Raimund Bürger Gerardo Chowell Pep Mulet Luis M. Villada |
| author_facet | Raimund Bürger Gerardo Chowell Pep Mulet Luis M. Villada |
| author_sort | Raimund Bürger |
| collection | DOAJ |
| description | 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 timingof that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chilean regions, andthe putative location of introduction of the novel virus into the country. Specifically, ametapopulation SEIR (susceptible-exposed-infected-removed) compartmental model that tracks the transmissiondynamics of influenza in 15 Chilean regions is calibrated. The model incorporates population mobility among neighboringregions and indirect mobility to and from other regions via themetropolitan central region (``hub region''). The stability of the disease-freeequilibrium of this model is analyzed and compared with thecorresponding stability in each region, concluding that stability mayoccur even with some regions having basic reproduction numbersabove 1.The transmission model is used along with epidemiological data to explorepotential factors that could have driventhe spatial-temporal progression of the pandemic. Simulations and sensitivity analyses indicate that thisrelatively 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. |
| format | Article |
| id | doaj-art-345dae1e0dd14e419625ace37af89198 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-345dae1e0dd14e419625ace37af891982025-01-24T02:34:05ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-09-01131436510.3934/mbe.2016.13.43Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in ChileRaimund Bürger0Gerardo Chowell1Pep Mulet2Luis M. Villada3CI2MA and Departamento de Ingeniería Matemática, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Casilla 160-C, ConcepciónSchool of Public Health, Georgia State University, Atlanta, GeorgiaDepartament de Matemàtica Aplicada, Universitat de València, Av. Dr. Moliner 50, E-46100 BurjassotGIMNAP-Departamento de Matemáticas, Universidad del Bío-Bío, Casilla 5-C, ConcepciónA 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 timingof that pandemic as a function of local transmission rates, spatial connectivity assumptions for Chilean regions, andthe putative location of introduction of the novel virus into the country. Specifically, ametapopulation SEIR (susceptible-exposed-infected-removed) compartmental model that tracks the transmissiondynamics of influenza in 15 Chilean regions is calibrated. The model incorporates population mobility among neighboringregions and indirect mobility to and from other regions via themetropolitan central region (``hub region''). The stability of the disease-freeequilibrium of this model is analyzed and compared with thecorresponding stability in each region, concluding that stability mayoccur even with some regions having basic reproduction numbersabove 1.The transmission model is used along with epidemiological data to explorepotential factors that could have driventhe spatial-temporal progression of the pandemic. Simulations and sensitivity analyses indicate that thisrelatively 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.https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.43stability of disease-free equilibrium.spatial-temporal seir modelpandemicmetapopulation model |
| spellingShingle | Raimund Bürger Gerardo Chowell Pep Mulet Luis M. Villada Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile Mathematical Biosciences and Engineering stability of disease-free equilibrium. spatial-temporal seir model pandemic metapopulation model |
| title | Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile |
| title_full | Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile |
| title_fullStr | Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile |
| title_full_unstemmed | Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile |
| title_short | Modelling the spatial-temporal progression of the 2009 A/H1N1 influenza pandemic in Chile |
| title_sort | modelling the spatial temporal progression of the 2009 a h1n1 influenza pandemic in chile |
| topic | stability of disease-free equilibrium. spatial-temporal seir model pandemic metapopulation model |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.43 |
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