A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations
Authored by Arne Bomblies, Ernest Ohene Asare, Adrian Mark Tompkins
Date Published: 2016
DOI: 10.1371/journal.pone.0150626
Sponsors:
European Union
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Dynamical malaria models can relate precipitation to the availability of
vector breeding sites using simple models of surface hydrology. Here, a
revised scheme is developed for the VECTRI malaria model, which is
evaluated alongside the default scheme using a two year simulation by
HYDREMATS, a 10 metre resolution, village-scale model that explicitly
simulates individual ponds. Despite the simplicity of the two VECTRI
surface hydrology parametrization schemes, they can reproduce the
sub-seasonal evolution of fractional water coverage. Calibration of the
model parameters is required to simulate the mean pond fraction
correctly. The default VECTRI model tended to overestimate water
fraction in periods subject to light rainfall events and underestimate
it during periods of intense rainfall. This systematic error was
improved in the revised scheme by including the a parametrization for
surface run-off, such that light rainfall below the initial abstraction
threshold does not contribute to ponds. After calibration of the pond
model, the VECTRI model was able to simulate vector densities that
compared well to the detailed agent based model contained in HYDREMATS
without further parameter adjustment. Substituting local rain-gauge data
with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data
sparse regions. However, further improvements could be made if a method
can be derived to calibrate the key hydrology parameters of the pond
model in each grid cell location, possibly also incorporating slope and
soil texture.
Tags
transmission
Environmental-factors
Western kenya highlands
Anopheles-gambiae-s.s.
Spatial-distribution
Mosquito larvae
Crust formation
Sandy soils
El-nino
Rainfall