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Predicting the Timing and Magnitude of Tropical Mosquito Population Peaks for Maximizing Control Efficiency

Yang, Guo-Jing, Brook, Barry W. and Bradshaw, Corey J. A. (2009). Predicting the Timing and Magnitude of Tropical Mosquito Population Peaks for Maximizing Control Efficiency. PLoS Neglected Tropical Diseases,3(2):e385.

Document type: Journal Article
Citation counts: Altmetric Score Altmetric Score is 9
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Title Predicting the Timing and Magnitude of Tropical Mosquito Population Peaks for Maximizing Control Efficiency
Author Yang, Guo-Jing
Brook, Barry W.
Bradshaw, Corey J. A.
Journal Name PLoS Neglected Tropical Diseases
Publication Date 2009
Volume Number 3
Issue Number 2
ISSN 1935-2735   (check CDU catalogue open catalogue search in new window)
Start Page e385
Total Pages 9
Place of Publication San Francisco, CA, United States
Publisher Public Library of Science
HERDC Category C1 - Journal Article (DEST)
Abstract The transmission of mosquito-borne diseases is strongly linked to the abundance of the host vector. Identifying the environmental and biological precursors which herald the onset of peaks in mosquito abundance would give health and land-use managers the capacity to predict the timing and distribution of the most efficient and cost-effective mosquito control. We analysed a 15-year time series of monthly abundance of Aedes vigilax, a tropical mosquito species from northern Australia, to determine periodicity and drivers of population peaks (high-density outbreaks). Two sets of density-dependent models were used to examine the correlation between mosquito abundance peaks and the environmental drivers of peaks or troughs (low-density periods). The seasonal peaks of reproduction (r) and abundance () occur at the beginning of September and early November, respectively. The combination of low mosquito abundance and a low frequency of a high tide exceeding 7 m in the previous low-abundance (trough) period were the most parsimonious predictors of a peak's magnitude, with this model explaining over 50% of the deviance in . Model weights, estimated using AICc, were also relatively high for those including monthly maximum tide height, monthly accumulated tide height or total rainfall per month in the trough, with high values in the trough correlating negatively with the onset of a high-abundance peak. These findings illustrate that basic environmental monitoring data can be coupled with relatively simple density feedback models to predict the timing and magnitude of mosquito abundance peaks. Decision-makers can use these methods to determine optimal levels of control (i.e., least-cost measures yielding the largest decline in mosquito abundance) and so reduce the risk of disease outbreaks in human populations.
Keywords tropical
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