A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations

Submitted: 17 June 2015
Accepted: 4 February 2016
Published: 31 March 2016
Abstract Views: 2300
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Daily observations of potential mosquito developmental habitats in a suburb of Kumasi in central Ghana reveal a strong variability in their water persistence times, which ranged between 11 and 81 days. The persistence of the ponds was strongly tied with rainfall, location and size of the puddles. A simple power-law relationship is found to fit the relationship between the average pond depth and area well. A prognostic water balance model is derived that describes the temporal evolution of the pond area and depth, incorporating the power-law geometrical relation. Pond area increases in response to rainfall, while evaporation and infiltration act as sink terms. Based on a range of evaluation metrics, the prognostic model is judged to provide a good representation of the pond coverage evolution at most sites. Finally, we demonstrate that the prognostic equation can be generalised and equally applied to a grid-cell to derive a fractional pond coverage, and thus can be implemented in spatially distributed models for relevant vector- borne diseases such as malaria.



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Supporting Agencies

EOA was generously funded by two International Centre of Theoretical Physics (ICTP) programmes, namely the Italian government's funds-in-trust programme and the ICTP PhD Sandwich Training and Educational Programme (STEP), The study was funded by two Eu

How to Cite

Asare, E. O., Tompkins, A. M., Amekudzi, L. K., & Ermert, V. (2016). A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations. Geospatial Health, 11(s1). https://doi.org/10.4081/gh.2016.390

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