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| Currently, two broad types of approach for predicting the impact of
climate change on vector-borne diseases can be distinguished: i)
empirical-statistical (correlative) approaches that use statistical models
of relationships between vector and/or pathogen presence and
environmental factors; and ii) process-based (mechanistic) approaches
that seek to simulate detailed biological or epidemiological processes
that explicitly describe system behavior. Both have advantages and
disadvantages, but it is generally acknowledged that both approaches
have value in assessing the response of species in general to climate
change. Here, we combine a previously developed dynamic, agentbased
model of the temperature-sensitive stages of the Schistosoma
mansoni and intermediate host snail lifecycles, with a statistical model
of snail habitat suitability for eastern Africa. Baseline model output
compared to empirical prevalence data suggest that the combined
model performs better than a temperature-driven model alone, and
highlights the importance of including snail habitat suitability when
modeling schistosomiasis risk. There was general agreement among
models in predicting changes in risk, with 24-36% of the eastern Africa
region predicted to experience an increase in risk of up-to 20% as a
result of increasing temperatures over the next 50 years. Vice versa
the models predicted a general decrease in risk in 30-37% of the study
area. The snail habitat suitability models also suggest that anthropogenically
altered habitat play a vital role for the current distribution
of the intermediate snail host, and hence we stress the importance of
accounting for land use changes in models of future changes in schistosomiasis
risk. | |
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