Dengue on islands: a Bayesian approach to understanding the global ecology of dengue viruses

Trans R Soc Trop Med Hyg. 2015 May;109(5):303-12. doi: 10.1093/trstmh/trv012. Epub 2015 Mar 13.


Background: Transmission of dengue viruses (DENV), the most common arboviral pathogens globally, is influenced by many climatic and socioeconomic factors. However, the relative contributions of these factors on a global scale are unclear.

Methods: We randomly selected 94 islands stratified by socioeconomic and geographic characteristics. With a Bayesian model, we assessed factors contributing to the probability of islands having a history of any dengue outbreaks and of having frequent outbreaks.

Results: Minimum temperature was strongly associated with suitability for DENV transmission. Islands with a minimum monthly temperature of greater than 14.8°C (95% CI: 12.4-16.6°C) were predicted to be suitable for DENV transmission. Increased population size and precipitation were associated with increased outbreak frequency, but did not capture all of the variability. Predictions for 48 testing islands verified these findings.

Conclusions: This analysis clarified two key components of DENV ecology: minimum temperature was the most important determinant of suitability; and endemicity was more likely in areas with high precipitation and large, but not necessarily dense, populations. Wealth and connectivity, in contrast, had no discernable effects. This model adds to our knowledge of global determinants of dengue risk and provides a basis for understanding the ecology of dengue endemicity.

Keywords: Dengue; Ecology; Epidemiology; Islands; Transmission dynamics.

Publication types

  • Randomized Controlled Trial
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Validation Study

MeSH terms

  • Aedes
  • Animals
  • Bayes Theorem*
  • Climate
  • Dengue / prevention & control
  • Dengue / transmission*
  • Dengue Virus / pathogenicity*
  • Disease Outbreaks
  • Humans
  • Islands
  • Molecular Epidemiology*
  • Phylogeography