Literature DB >> 18590749

Describing the geographic spread of dengue disease by traveling waves.

Norberto Aníbal Maidana1, Hyun Mo Yang.   

Abstract

Dengue is a human disease transmitted by the mosquito Aedes aegypti. For this reason geographical regions infested by this mosquito species are under the risk of dengue outbreaks. In this work, we propose a mathematical model to study the spatial dissemination of dengue using a system of partial differential reaction-diffusion equations. With respect to the human and mosquito populations, we take into account their respective subclasses of infected and uninfected individuals. The dynamics of the mosquito population considers only two subpopulations: the winged form (mature female mosquitoes), and an aquatic population (comprising eggs, larvae and pupae). We disregard the long-distance movement by transportation facilities, for which reason the diffusion is considered restricted only to the winged form. The human population is considered homogeneously distributed in space, in order to describe localized dengue dissemination during a short period of epidemics. The cross-infection is modeled by the law of mass action. A threshold value as a function of the model's parameters is obtained, which determines the rate of dengue dissemination and the risk of dengue outbreaks. Assuming that an area was previously colonized by the mosquitoes, the rate of disease dissemination is determined as a function of the model's parameters. This rate of dissemination of dengue disease is determined by applying the traveling wave solutions to the corresponding system of partial differential equations.

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Year:  2008        PMID: 18590749     DOI: 10.1016/j.mbs.2008.05.008

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  12 in total

1.  Mathematical modeling of dengue epidemic: control methods and vaccination strategies.

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2.  Modeling the impact of genetically modified male mosquitoes in the spatial population dynamics of Aedes aegypti.

Authors:  Monalisa R da Silva; Pedro H G Lugão; Fábio Prezoto; Grigori Chapiro
Journal:  Sci Rep       Date:  2022-06-01       Impact factor: 4.996

3.  Ecologic and sociodemographic risk determinants for dengue transmission in urban areas in Thailand.

Authors:  Surachart Koyadun; Piyarat Butraporn; Pattamaporn Kittayapong
Journal:  Interdiscip Perspect Infect Dis       Date:  2012-09-26

4.  Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand.

Authors:  Phaisarn Jeefoo; Nitin Kumar Tripathi; Marc Souris
Journal:  Int J Environ Res Public Health       Date:  2010-12-29       Impact factor: 3.390

5.  Modeling the dynamic transmission of dengue fever: investigating disease persistence.

Authors:  Líliam César de Castro Medeiros; César Augusto Rodrigues Castilho; Cynthia Braga; Wayner Vieira de Souza; Leda Regis; Antonio Miguel Vieira Monteiro
Journal:  PLoS Negl Trop Dis       Date:  2011-01-11

6.  Diffusion pattern and hotspot detection of dengue in belo horizonte, minas gerais, Brazil.

Authors:  José Eduardo Marques Pessanha Pessanha; Waleska Teixeira Caiaffa; Maria Cristina de Mattos Almeida; Silvana Tecles Brandão; Fernando Augusto Proietti
Journal:  J Trop Med       Date:  2012-03-12

7.  Numerical modeling of mosquito population dynamics of Aedes aegypti.

Authors:  William M S Yamashita; Shyam S Das; Grigori Chapiro
Journal:  Parasit Vectors       Date:  2018-04-16       Impact factor: 3.876

8.  Dengue-like illness surveillance: a two-year longitudinal survey in suburban and rural communities in the Lao People's Democratic Republic and in Thailand.

Authors:  Nanthasane Vannavong; Razak Seidu; Thor Axel Stenström; Nsa Dada; Hans Jørgen Overgaard
Journal:  Western Pac Surveill Response J       Date:  2019-02-19

Review 9.  Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches.

Authors:  Mathieu Andraud; Niel Hens; Christiaan Marais; Philippe Beutels
Journal:  PLoS One       Date:  2012-11-06       Impact factor: 3.240

10.  A probabilistic spatial dengue fever risk assessment by a threshold-based-quantile regression method.

Authors:  Chuan-Hung Chiu; Tzai-Hung Wen; Lung-Chang Chien; Hwa-Lung Yu
Journal:  PLoS One       Date:  2014-10-10       Impact factor: 3.240

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