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Modelling dengue epidemic spreading with human mobility

Author

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  • Barmak, D.H.
  • Dorso, C.O.
  • Otero, M.

Abstract

We explored the effect of human mobility on the spatio-temporal dynamics of Dengue with a stochastic model that takes into account the epidemiological dynamics of the infected mosquitoes and humans, with different mobility patterns of the human population. We observed that human mobility strongly affects the spread of infection by increasing the final size and by changing the morphology of the epidemic outbreaks. When the spreading of the disease is driven only by mosquito dispersal (flight), a main central focus expands diffusively. On the contrary, when human mobility is taken into account, multiple foci appear throughout the evolution of the outbreaks. These secondary foci generated throughout the outbreaks could be of little importance according to their mass or size compared with the largest main focus. However, the coalescence of these foci with the main one generates an effect, through which the latter develops a size greater than the one obtained in the case driven only by mosquito dispersal. This increase in growth rate due to human mobility and the coalescence of the foci are particularly relevant in temperate cities such as the city of Buenos Aires, since they give more possibilities to the outbreak to grow before the arrival of the low-temperature season. The findings of this work indicate that human mobility could be the main driving force in the dynamics of vector epidemics.

Suggested Citation

  • Barmak, D.H. & Dorso, C.O. & Otero, M., 2016. "Modelling dengue epidemic spreading with human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 129-140.
  • Handle: RePEc:eee:phsmap:v:447:y:2016:i:c:p:129-140
    DOI: 10.1016/j.physa.2015.12.015
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    References listed on IDEAS

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    Cited by:

    1. Cornes, F.E. & Frank, G.A. & Dorso, C.O., 2022. "COVID-19 spreading under containment actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(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. Wang, Liping & Zhao, Hongyong, 2019. "Dynamics analysis of a Zika–dengue co-infection model with dengue vaccine and antibody-dependent enhancement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 248-273.

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