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

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dc.contributor.authorAsare, Ernest O.
dc.contributor.authorTompkins, Adrian M.
dc.contributor.authorAmekudzi, Leonard K.
dc.contributor.authorErmert, Volker
dc.date.accessioned2019-11-12T13:15:49Z
dc.date.accessioned2023-04-19T01:23:09Z
dc.date.available2019-11-12T13:15:49Z
dc.date.available2023-04-19T01:23:09Z
dc.date.issued2016
dc.descriptionAn article published by Geospatial Health 2016; volume 11(s1):390en_US
dc.description.abstractDaily 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 malariaen_US
dc.identifier.citationGeospatial Health 2016; volume 11(s1):390en_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/11789
dc.language.isoenen_US
dc.publisherGeospatial Healthen_US
dc.titleA breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observationsen_US
dc.typeArticleen_US
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