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

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.

Assessing Climate Driven Malaria Variability in Ghana Using a Regional Scale Dynamical Model

“…Recently, Asare et al [35] developed a simplified but comprehensive prognostic surface hydrology scheme based on power-law geometrical relation that accounts for direct rainfall, pond overflow, evaporation and nonlinearities of infiltration and surface run-off terms to predict surface water area of small spatial scale mosquito developmental habitats. The scheme was further generalised to simulate, instead of individual ponds, the temporal evolution of fractional water coverage of all breeding sites within each grid-cell (Equation (2)).…”

“…For example, between 2000 and 2011, malaria alone accounted for an average of about 40% of all out-patient attendance (OPD) in public health facilities [1][2][3]. Similarly, in 2011, the Ghana Health Service (GHS) [3] report indicated that suspected malaria cases accounted for about 40.2% outpatient morbidity, 35.2% hospital admissions and 18.1% of all recorded death at public hospitals. Most importantly, actual malaria cases are likely to be higher than the reported cases since private health facilities and home treatment (self medication) of the disease using both orthodox and traditional medicine are not taken into account.…”

“…For instance, rainfall in addition to local scale hydrological conditions control mosquito developmental habitat dynamics and, to some extent, its productivity [34,35]. More importantly, in Ghana, studies linking climate fluctuations and malaria transmission across the various agro-ecological zones are limited.…”

Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models

“…The malaria model used in this study is the VECTRI model (Tompkins and Ermert, 2013), a gridded mathematical model for malaria transmission that accounts for temperature in the larvae and adult life cycles, while rainfall drives a model for surface pond coverage that has been improved and evaluated (Asare et al, 2016a;. The model has been applied to seasonal forecasting tasks (Tompkins and Di Giuseppe, 2015) and has been evaluated using sentinel site and district case data from Uganda and Rwanda , as well as applied to climate change problems (Caminade et al, 2014).…”

Health, environmental change and adaptive capacity; mapping, examining and anticipating future risks of water-related vector-borne diseases in eastern Africa

“…Such results were integrated in a new agent-based migration model, with a view to providing better estimations, within the new generation of dynamic disease models, of short-term migration patterns of populations potentially affected by VBDs. Rather than the host, the habitat of vectors of infectious disease is the focus of the article by Asare et al (2016a), the research for which was conducted in Ghana due to the availability of a unique, long-term set of in situ observations of small-scale mosquito breeding sites. Evolution of pond area over time was modeled, taking into account rainfall, evaporation and infiltration.…”