Modeling dengue outbreaks
We introduce a dengue model (SEIR) where the human individuals are treated on an individual basis (IBM) while the mosquito population, produced by an independent model, is treated by compartments (SEI). We study the spread of epidemics by the sole action of the mosquito. Exponential, deterministic a...
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2011
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00255564_v232_n2_p87_Otero http://hdl.handle.net/20.500.12110/paper_00255564_v232_n2_p87_Otero |
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paper:paper_00255564_v232_n2_p87_Otero2023-06-08T14:53:10Z Modeling dengue outbreaks Otero, Marcelo Javier Dorso, Claudio Oscar Solari, Hernán Gustavo Natiello, Mario Alberto Compartmental model Dengue Epidemiology Individual based model Stochastic Compartmental model Dengue IBM Models Independent model Individual based model Stochastic Temperate climate Tropical climates Climatology Epidemiology Viruses Stochastic models dengue fever epidemiology numerical model tropical meteorology Aedes aegypti article breeding compartment model computer simulation dengue Dengue virus disease model disease transmission egg laying epidemic evolution human incubation time individual based model mosquito nonhuman probability temperature weather Aedes Animals Climate Computer Simulation Dengue Dengue Virus Disease Outbreaks Humans Insect Vectors Models, Biological Stochastic Processes We introduce a dengue model (SEIR) where the human individuals are treated on an individual basis (IBM) while the mosquito population, produced by an independent model, is treated by compartments (SEI). We study the spread of epidemics by the sole action of the mosquito. Exponential, deterministic and experimental distributions for the (human) exposed period are considered in two weather scenarios, one corresponding to temperate climate and the other to tropical climate. Virus circulation, final epidemic size and duration of outbreaks are considered showing that the results present little sensitivity to the statistics followed by the exposed period provided the median of the distributions are in coincidence. Only the time between an introduced (imported) case and the appearance of the first symptomatic secondary case is sensitive to this distribution. We finally show that the IBM model introduced is precisely a realization of a compartmental model, and that at least in this case, the choice between compartmental models or IBM is only a matter of convenience. © 2011 Elsevier Inc. Fil:Otero, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Dorso, C.O. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Solari, H.G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Natiello, M.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2011 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00255564_v232_n2_p87_Otero http://hdl.handle.net/20.500.12110/paper_00255564_v232_n2_p87_Otero |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Compartmental model Dengue Epidemiology Individual based model Stochastic Compartmental model Dengue IBM Models Independent model Individual based model Stochastic Temperate climate Tropical climates Climatology Epidemiology Viruses Stochastic models dengue fever epidemiology numerical model tropical meteorology Aedes aegypti article breeding compartment model computer simulation dengue Dengue virus disease model disease transmission egg laying epidemic evolution human incubation time individual based model mosquito nonhuman probability temperature weather Aedes Animals Climate Computer Simulation Dengue Dengue Virus Disease Outbreaks Humans Insect Vectors Models, Biological Stochastic Processes |
| spellingShingle |
Compartmental model Dengue Epidemiology Individual based model Stochastic Compartmental model Dengue IBM Models Independent model Individual based model Stochastic Temperate climate Tropical climates Climatology Epidemiology Viruses Stochastic models dengue fever epidemiology numerical model tropical meteorology Aedes aegypti article breeding compartment model computer simulation dengue Dengue virus disease model disease transmission egg laying epidemic evolution human incubation time individual based model mosquito nonhuman probability temperature weather Aedes Animals Climate Computer Simulation Dengue Dengue Virus Disease Outbreaks Humans Insect Vectors Models, Biological Stochastic Processes Otero, Marcelo Javier Dorso, Claudio Oscar Solari, Hernán Gustavo Natiello, Mario Alberto Modeling dengue outbreaks |
| topic_facet |
Compartmental model Dengue Epidemiology Individual based model Stochastic Compartmental model Dengue IBM Models Independent model Individual based model Stochastic Temperate climate Tropical climates Climatology Epidemiology Viruses Stochastic models dengue fever epidemiology numerical model tropical meteorology Aedes aegypti article breeding compartment model computer simulation dengue Dengue virus disease model disease transmission egg laying epidemic evolution human incubation time individual based model mosquito nonhuman probability temperature weather Aedes Animals Climate Computer Simulation Dengue Dengue Virus Disease Outbreaks Humans Insect Vectors Models, Biological Stochastic Processes |
| description |
We introduce a dengue model (SEIR) where the human individuals are treated on an individual basis (IBM) while the mosquito population, produced by an independent model, is treated by compartments (SEI). We study the spread of epidemics by the sole action of the mosquito. Exponential, deterministic and experimental distributions for the (human) exposed period are considered in two weather scenarios, one corresponding to temperate climate and the other to tropical climate. Virus circulation, final epidemic size and duration of outbreaks are considered showing that the results present little sensitivity to the statistics followed by the exposed period provided the median of the distributions are in coincidence. Only the time between an introduced (imported) case and the appearance of the first symptomatic secondary case is sensitive to this distribution. We finally show that the IBM model introduced is precisely a realization of a compartmental model, and that at least in this case, the choice between compartmental models or IBM is only a matter of convenience. © 2011 Elsevier Inc. |
| author |
Otero, Marcelo Javier Dorso, Claudio Oscar Solari, Hernán Gustavo Natiello, Mario Alberto |
| author_facet |
Otero, Marcelo Javier Dorso, Claudio Oscar Solari, Hernán Gustavo Natiello, Mario Alberto |
| author_sort |
Otero, Marcelo Javier |
| title |
Modeling dengue outbreaks |
| title_short |
Modeling dengue outbreaks |
| title_full |
Modeling dengue outbreaks |
| title_fullStr |
Modeling dengue outbreaks |
| title_full_unstemmed |
Modeling dengue outbreaks |
| title_sort |
modeling dengue outbreaks |
| publishDate |
2011 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00255564_v232_n2_p87_Otero http://hdl.handle.net/20.500.12110/paper_00255564_v232_n2_p87_Otero |
| work_keys_str_mv |
AT oteromarcelojavier modelingdengueoutbreaks AT dorsoclaudiooscar modelingdengueoutbreaks AT solarihernangustavo modelingdengueoutbreaks AT natiellomarioalberto modelingdengueoutbreaks |
| _version_ |
1768544674537013248 |