Analysing the generality of spatially predictive mosquito habitat models

Li, Li, Bian, Ling, Yakob, Laith, Zhou, Guofa and Yan, Guiyun (2011) Analysing the generality of spatially predictive mosquito habitat models. Acta Tropica, 119 1: 30-37. doi:10.1016/j.actatropica.2011.04.003

Author Li, Li
Bian, Ling
Yakob, Laith
Zhou, Guofa
Yan, Guiyun
Title Analysing the generality of spatially predictive mosquito habitat models
Journal name Acta Tropica   Check publisher's open access policy
ISSN 0001-706X
Publication date 2011-07
Sub-type Article (original research)
DOI 10.1016/j.actatropica.2011.04.003
Volume 119
Issue 1
Start page 30
End page 37
Total pages 8
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2012
Language eng
Formatted abstract
The increasing spread of multi-drug resistant malaria in African highlands has highlighted the importance of malaria suppression through vector control. Its historical success has meant that larval control has been proposed as part of an integrated malaria vector control program. Due to high operation costs, larval control activities would benefit greatly if the locations of mosquito habitats could be identified quickly and easily, allowing for focal habitat source suppression. Several mosquito habitat models have been developed to predict the location of mosquito habitats. However, to what extent these models can be generalised across time and space to predict the distribution of dynamic mosquito habitats remains largely unexplored. This study used mosquito habitat data collected in six different time periods and four different modelling approaches to establish 24 mosquito habitat models. We systematically tested the generality of these 24 mosquito habitat models. We found that although habitat–environment relationships change temporally, a modest level of performance was attained when validating the models using data collected from different time periods. We also describe flexible approaches to the predictive modelling of mosquito habitats, that provide novel modelling architecture for future research efforts.

Highlights: ► There are temporal variabilities in mosquito habitat–environment relationships. ► Habitat models developed using data collected at wet seasons have good performance in predicting dry season habitats. ► Models developed using different modelling approaches have different performance. ► In our study, the flexibility of modelling approaches and spatial autocorrelation have limited impact on the accuracy of habitat models.
Keyword Model generality
Spatial predictive habitat models
Temporal generality
Spatial generality
Larval habitat
African malaria vectors
Western Kenya
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
School of Biological Sciences Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 02 Sep 2011, 10:35:04 EST by Gail Walter on behalf of School of Biological Sciences