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Man Bites Mosquito: Understanding the Contribution of Human Movement to Vector-Borne Disease Dynamics

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  • Ben Adams
  • Durrell D Kapan

Abstract

In metropolitan areas people travel frequently and extensively but often in highly structured commuting patterns. We investigate the role of this type of human movement in the epidemiology of vector-borne pathogens such as dengue. Analysis is based on a metapopulation model where mobile humans connect static mosquito subpopulations. We find that, due to frequency dependent biting, infection incidence in the human and mosquito populations is almost independent of the duration of contact. If the mosquito population is not uniformly distributed between patches the transmission potential of the pathogen at the metapopulation level, as summarized by the basic reproductive number, is determined by the size of the largest subpopulation and reduced by stronger connectivity. Global extinction of the pathogen is less likely when increased human movement enhances the rescue effect but, in contrast to classical theory, it is not minimized at an intermediate level of connectivity. We conclude that hubs and reservoirs of infection can be places people visit frequently but briefly and the relative importance of human and mosquito populations in maintaining the pathogen depends on the distribution of the mosquito population and the variability in human travel patterns. These results offer an insight in to the paradoxical observation of resurgent urban vector-borne disease despite increased investment in vector control and suggest that successful public health intervention may require a dual approach. Prospective studies can be used to identify areas with large mosquito populations that are also visited by a large fraction of the human population. Retrospective studies can be used to map recent movements of infected people, pinpointing the mosquito subpopulation from which they acquired the infection and others to which they may have transmitted it.

Suggested Citation

  • Ben Adams & Durrell D Kapan, 2009. "Man Bites Mosquito: Understanding the Contribution of Human Movement to Vector-Borne Disease Dynamics," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-10, August.
  • Handle: RePEc:plo:pone00:0006763
    DOI: 10.1371/journal.pone.0006763
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    Cited by:

    1. Zhang, Ruixia, 2020. "Global dynamic analysis of a model for vector-borne diseases on bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Renaud Marti & Zhichao Li & Thibault Catry & Emmanuel Roux & Morgan Mangeas & Pascal Handschumacher & Jean Gaudart & Annelise Tran & Laurent Demagistri & Jean-François Faure & José Joaquín Carvajal & , 2020. "A Mapping Review on Urban Landscape Factors of Dengue Retrieved from Earth Observation Data, GIS Techniques, and Survey Questionnaires," Post-Print hal-02682042, HAL.
    3. Jue Wang & Mei-Po Kwan & Yanwei Chai, 2018. "An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago," IJERPH, MDPI, vol. 15(4), pages 1-24, April.
    4. Laperrière, Vincent & Brugger, Katharina & Rubel, Franz, 2016. "Cross-scale modeling of a vector-borne disease, from the individual to the metapopulation: The seasonal dynamics of sylvatic plague in Kazakhstan," Ecological Modelling, Elsevier, vol. 342(C), pages 34-48.
    5. Yuqi Zhang & Hongyan Ren & Runhe Shi, 2022. "Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    6. Shuli Zhou & Suhong Zhou & Lin Liu & Meng Zhang & Min Kang & Jianpeng Xiao & Tie Song, 2019. "Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    7. Tiago França Melo De Lima & Raquel Martins Lana & Tiago Garcia De Senna Carneiro & Cláudia Torres Codeço & Gabriel Souza Machado & Lucas Saraiva Ferreira & Líliam César De Castro Medeiros & Clodoveu A, 2016. "DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics," IJERPH, MDPI, vol. 13(9), pages 1-21, September.

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