Mapping Potential Malaria Vector Larval Habitats for Larval Source Management in Western Kenya: Introduction to Multimodel Ensembling Approaches

Guofa Zhou Program in Public Health, University of California, Irvine, California;

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Ming-Chieh Lee Program in Public Health, University of California, Irvine, California;

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Xiaoming Wang Program in Public Health, University of California, Irvine, California;

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Daibin Zhong Program in Public Health, University of California, Irvine, California;

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Andrew K. Githeko Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya

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Guiyun Yan Program in Public Health, University of California, Irvine, California;

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ABSTRACT.

Identification and mapping of larval sources are a prerequisite for effective planning and implementing mosquito larval source management (LSM). Ensemble modeling is increasingly used for prediction modeling, but it lacks standard procedures. We proposed a detailed framework to predict potential malaria vector larval habitats by using multimodel ensemble modeling, which includes selection of models, ensembling method, and predictors, evaluation of variable importance, prediction of potential larval habitats, and assessment of prediction uncertainty. The models were built and validated based on multisite, multiyear field observations and climatic/environmental variables. Model performance was tested using independent field observations. Overall, we found that the ensembled model predicted larval habitats with about 20% more accuracy than the average of the individual models ensembled. Key larval habitat predictors in western Kenya were elevation, geomorphon class, and precipitation for the 2 months prior. Additional predictors may be required to increase the predictive accuracy of the larva-positive habitats. This is the first study to provide a detailed framework for the process of multimodel ensemble modeling for malaria vector habitats. Mapping of potential habitats will be helpful in LSM planning.

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Author Notes

Financial support: This study was funded by the National Institutes of Health (grant numbers D43 TW001505 and U19 AI129326).

Disclosure: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Authors’ addresses: Guofa Zhou, Ming-Chieh Lee, Xiaoming Wang, Daibin Zhong, and Guiyun Yan, Program in Public Health, University of California, Irvine, CA, E-mails: zhoug@hs.uci.edu, mingchil@uci.edu, xiaomiw1@uci.edu, xiaomiw1@hs.uci.edu, xiaomiw1@uci.edu, and guiyuny@uci.edu. Andrew K. Githeko, Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya, E-mail: githeko@yahoo.com.

Address correspondence to Guofa Zhou, 3501 Hewitt Hall, Irvine, CA 92697. E-mail: zhoug@hs.uci.edu
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