4.3 Article

Spatiotemporal patterns of Aedes aegypti populations in Cairns, Australia: assessing drivers of dengue transmission

Journal

TROPICAL MEDICINE & INTERNATIONAL HEALTH
Volume 18, Issue 7, Pages 839-849

Publisher

WILEY-BLACKWELL
DOI: 10.1111/tmi.12115

Keywords

dengue; Aedes aegypti; spatial; temporal; Cairns

Funding

  1. Australian National Health and Medical Research Council

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Objectives To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia. Methods Weekly adult female Ae.aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns. Results Ae.aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6weeks) and long (0-30weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach. Conclusion Spatiotemporal patterns of Ae.aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.

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