The development of predictive tools for pre-emptive dengue vector control: a study of Aedes aegypti abundance and meteorological variables in North Queensland, Australia

Azill, Aishah H., Long, Sharron A., Ritchie, Scott A., and Williams, Craig R. (2010) The development of predictive tools for pre-emptive dengue vector control: a study of Aedes aegypti abundance and meteorological variables in North Queensland, Australia. Tropical Medicine and International Health , 15 (10). pp. 1190-1197.

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Abstract

Objectives To describe the meteorological influences on adult dengue vector abundance in Australia for the development of predictive models to trigger pre-emptive control operation.

Methods Multiple linear regression analyses were performed using meteorological data and female Aedes aegypti collection data from BG-Sentinel Mosquito traps placed at 11 monitoring sites in Cairns, north Queensland.

Results Considerable regression coefficients (R2 = 0.64 and 0.61) for longer- and shorter-term factor models respectively were derived. Longer-term factors significantly associated with abundance of adult vectors were mean minimum temperature (lagged 6 month) and mean daily temperature (lagged 4 month), explaining the predictable increase in abundance during the wet season. Factors explaining fluctuation in abundance in the shorter term were mean relative humidity over the previous 2 week and current daily average temperature. Rainfall variables were not found to be strong predictors of A. aegypti abundance in either longer- or shorter-term models.

Conclusions The implications of these findings for the development of useful predictive models for vector abundance risks are discussed. Such models can be used to guide the application of pre-emptive dengue vector control, and thereby enhance disease management.

Item ID: 15932
Item Type: Article (Refereed Research - C1)
Keywords: dengue; Aedes aegypti; surveillance; vector control; predictive models
ISSN: 1365-3156
Date Deposited: 27 Apr 2011 06:42
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111799 Public Health and Health Services not elsewhere classified @ 60%
11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 40%
SEO Codes: 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920499 Public Health (excl. Specific Population Health) not elsewhere classified @ 100%
Citation Count from Web of Science Web of Science 21
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