ArticlePLoS neglected tropical diseases2009
Predicting the timing and magnitude of tropical mosquito population peaks for maximizing control efficiency.
Article in PLoS neglected tropical diseases, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Hydrometeorological drivers of mosquito (Diptera: Culicidae) abundance in an urbanized region of central Oklahoma.Journal of medical entomology · 2026Article
- Comparative resilience and precision of digitized optical counting using ImageJ during routine mosquito (Diptera: Culicidae) sample processing.Journal of insect science (Online) · 2025Article
- Invasive mosquito surveillance in the United Kingdom 2020 to 2024: First detection of Aedes aegypti eggs in the UK and further detection of Aedes albopictus.PLOS global public health · 2025Article
- Comparative analysis of subsampling methods for large mosquito samples.Parasites & vectors · 2019Article
- Aedes aegypti (Diptera: Culicidae) Abundance Model Improved With Relative Humidity and Precipitation-Driven Egg Hatching.Journal of medical entomology · 2017Article
- Modeling Occurrence of Urban Mosquitos Based on Land Use Types and Meteorological Factors in Korea.International journal of environmental research and public health · 2015Article
- Persistent oscillations and backward bifurcation in a malaria model with varying human and mosquito populations: implications for control.Journal of mathematical biology · 2015Article
- Early warning of West Nile virus mosquito vector: climate and land use models successfully explain phenology and abundance of Culex pipiens mosquitoes in north-western Italy.Parasites & vectors · 2014Article
- Relative roles of weather variables and change in human population in malaria: comparison over different states of India.PloS one · 2014Article
- Assessing the effects of variables and background selection on the capture of the tick climate niche.International journal of health geographics · 2013Article
- A model of malaria epidemiology involving weather, exposure and transmission applied to north East India.PloS one · 2012Article
- Strategies for introducing Wolbachia to reduce transmission of mosquito-borne diseases.PLoS neglected tropical diseases · 2011Article
- Vector-control response in a post-flood disaster setting, Honiara, Solomon Islands, 2014.Western Pacific surveillance and response journal : WPSARArticle
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
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 (N(peak)) 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 N(peak). Model weights, estimated using AIC(c), 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.
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