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|Title: ||A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations|
|Authors: ||Amekudzi, L.K.|
|Issue Date: ||2016|
|Publisher: ||Geospatial HealthOpen Access|
|Citation: ||Geospatial HealthOpen Access, Volume 11, Issue 1S, 2016, 66p|
|Abstract: ||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.|
|Description: ||This article is published in Geospatial HealthbOpen Access and also available at DOI: 10.4081/gh.2016.390|
|Appears in Collections:||College of Science|
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