Human movement, cooperation and the effectiveness of coordinated vector control strategies

Chris M. Stone, Samantha R. Schwab, Dina M. Fonseca, Nina H. Fefferman

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Vector-borne disease transmission is often typified by highly focal transmission and influenced by movement of hosts and vectors across different scales. The ecological and environmental conditions (including those created by humans through vector control programmes) that result in metapopulation dynamics remain poorly understood. The development of control strategies that would most effectively limit outbreaks given such dynamics is particularly urgent given the recent epidemics of dengue, chikungunya and Zika viruses. We developed a stochastic, spatial model of vectorborne disease transmission, allowing for movement of hosts between patches. Our model is applicable to arbovirus transmission by Aedes aegypti in urban settings and was parametrized to capture Zika virus transmission in particular. Using simulations, we investigated the extent to which two aspects of vector control strategies are affected by human commuting patterns: the extent of coordination and cooperation between neighbouring communities. We find that transmission intensity is highest at intermediate levels of host movement. The extent to which coordination of control activities among neighbouring patches decreases the prevalence of infection is affected by both how frequently humans commute and the proportion of neighbouring patches that commits to vector surveillance and control activities. At high levels of host movement, patches that do not contribute to vector control may act as sources of infection in the landscape, yet have comparable levels of prevalence as patches that do cooperate. This result suggests that real cooperation among neighbours will be critical to the development of effective pro-active strategies for vector-borne disease control in today's commuter-linked communities.

Original languageEnglish (US)
Article number20170336
JournalJournal of the Royal Society Interface
Volume14
Issue number133
DOIs
StatePublished - Aug 1 2017

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biomaterials
  • Biochemistry
  • Biomedical Engineering

Keywords

  • Aedes aegypti
  • Commuting patterns
  • Larval control
  • Metapopulation
  • Zika virus

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