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

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      1 , * , 2
      PLoS ONE
      Public Library of Science

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          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.

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          Most cited references30

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          How should pathogen transmission be modelled?

          Host-pathogen models are essential for designing strategies for managing disease threats to humans, wild animals and domestic animals. The behaviour of these models is greatly affected by the way in which transmission between infected and susceptible hosts is modelled. Since host-pathogen models were first developed at the beginning of the 20th century, the 'mass action' assumption has almost always been used for transmission. Recently, however, it has been suggested that mass action has often been modelled wrongly. Alternative models of transmission are beginning to appear, as are empirical tests of transmission dynamics.
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            Dispersal of the dengue vector Aedes aegypti within and between rural communities.

            Knowledge of mosquito dispersal is critical for vector-borne disease control and prevention strategies and for understanding population structure and pathogen dissemination. We determined Aedes aegypti flight range and dispersal patterns from 21 mark-release-recapture experiments conducted over 11 years (1991-2002) in Puerto Rico and Thailand. Dispersal was compared by release location, sex, age, season, and village. For all experiments, the majority of mosquitoes were collected from their release house or adjacent house. Inter-village movement was detected rarely, with a few mosquitoes moving a maximum of 512 meters from one Thai village to the next. Average dispersal distances were similar for males and females and females released indoors versus outdoors. The movement of Ae. aegypti was not influenced by season or age, but differed by village. Results demonstrate that adult Ae. aegypti disperse relatively short distances, suggesting that people rather than mosquitoes are the primary mode of dengue virus dissemination within and among communities.
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              Prediction and predictability of global epidemics: the role of the airline transportation network

              The systematic study of large-scale networks has unveiled the ubiquitous presence of connectivity patterns characterized by large scale heterogeneities and unbounded statistical fluctuations. These features affect dramatically the behavior of the diffusion processes occurring on networks, determining the ensuing statistical properties of their evolution pattern and dynamics. In this paper, we investigate the role of the large scale properties of the airline transportation network in determining the global evolution of emerging disease. We present a stochastic computational framework for the forecast of global epidemics that considers the complete world-wide air travel infrastructure complemented with census population data. We address two basic issues in global epidemic modeling: i) We study the role of the large scale properties of the airline transportation network in determining the global diffusion pattern of emerging diseases; ii) We evaluate the reliability of forecasts and outbreak scenarios with respect to the intrinsic stochasticity of disease transmission and traffic flows. In order to address these issues we define a set of novel quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern. These measures may be used for the analysis of containment policies and epidemic risk assessment.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                26 August 2009
                : 4
                : 8
                : e6763
                Affiliations
                [1 ]Department of Biology, Kyushu University, Fukuoka, Japan
                [2 ]Center for Conservation and Research Training, Pacific Biosciences Research Center, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
                Yale University, United States of America
                Author notes

                Conceived and designed the experiments: BA DDK. Performed the experiments: BA DDK. Analyzed the data: BA DDK. Wrote the paper: BA DDK.

                [¤]

                Current address: Department of Mathematical Sciences, University of Bath, Bath, United Kingdom

                Article
                09-PONE-RA-09172R1
                10.1371/journal.pone.0006763
                2727792
                19707544
                03abf0d3-b0e0-4349-b7c0-52e86e34785f
                Adams, Kapan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 11 March 2009
                : 27 July 2009
                Page count
                Pages: 10
                Categories
                Research Article
                Computational Biology/Ecosystem Modeling
                Ecology/Theoretical Ecology
                Infectious Diseases/Epidemiology and Control of Infectious Diseases

                Uncategorized
                Uncategorized

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