Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 413483
Title Predicting the effect of climate change on African trypanosomiasis: integrating epidemiology with parasite and vector biology
Author(s) Moore, S.; Shrestha, S.; Tomlinson, K.W.; Vuong, H.
Source Journal of the Royal Society, Interface 9 (2012)70. - ISSN 1742-5689 - p. 817 - 830.
DOI http://dx.doi.org/10.1098/rsif.2011.0654
Department(s) Resource Ecology
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) rhodesiense sleeping sickness - morsitans morsitans diptera - sensed vegetation data - south-eastern uganda - common fly belt - infectious-diseases - glossina-morsitans - brucei-rhodesiense - tsetse-flies - population-dynamics
Abstract Climate warming over the next century is expected to have a large impact on the interactions between pathogens and their animal and human hosts. Vector-borne diseases are particularly sensitive to warming because temperature changes can alter vector development rates, shift their geographical distribution and alter transmission dynamics. For this reason, African trypanosomiasis (sleeping sickness), a vector-borne disease of humans and animals, was recently identified as one of the 12 infectious diseases likely to spread owing to climate change. We combine a variety of direct effects of temperature on vector ecology, vector biology and vector–parasite interactions via a disease transmission model and extrapolate the potential compounding effects of projected warming on the epidemiology of African trypanosomiasis. The model predicts that epidemics can occur when mean temperatures are between 20.78C and 26.18C. Our model does not predict a large-range expansion, but rather a large shift of up to 60 per cent in the geographical extent of the range. The model also predicts that 46–77 million additional people may be at risk of exposure by 2090. Future research could expand our analysis to include other environmental factors that influence tsetse populations and disease transmission such as humidity, as well as changes to human, livestock and wildlife distributions. The modelling approach presented here provides a framework for using the climate-sensitive aspects of vector and pathogen biology to predict changes in disease prevalence and risk owing to climate change.
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