Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

  • Ulrik B. Pedersen | ubpedersen@hotmail.com Department of Disease Biology, Faculty of Health Sciences and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark. http://orcid.org/0000-0001-7256-2115
  • Dimitrios-Alexios Karagiannis-Voules Department of Public Health and Epidemiology, Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland.
  • Nicholas Midzi Department of Biochemistry, University of Zimbabwe, Harare, Zimbabwe.
  • Tkafira Mduluza Department of Medical Microbiology, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe.
  • Samson Mukaratirwa School of Life Sciences, University of KwaZulu-Natal, Westville, South Africa.
  • Rasmus Fensholt Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
  • Birgitte J. Vennervald Department of Disease Biology, Faculty of Health Sciences and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark.
  • Thomas K. Kristensen Department of Disease Biology, Faculty of Health Sciences and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark; School of Life Sciences, University of KwaZulu-Natal, Westville, South Africa.
  • Penelope Vounatsou Department of Public Health and Epidemiology, Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland.
  • Anna-Sofie Stensgaard Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark.

Abstract

Temperature, precipitation and humidity are known to be important factors for the development of schistosome parasites as well as their intermediate snail hosts. Climate therefore plays an important role in determining the geographical distribution of schistosomiasis and it is expected that climate change will alter distribution and transmission patterns. Reliable predictions of distribution changes and likely transmission scenarios are key to efficient schistosomiasis intervention-planning. However, it is often difficult to assess the direction and magnitude of the impact on schistosomiasis induced by climate change, as well as the temporal transferability and predictive accuracy of the models, as prevalence data is often only available from one point in time. We evaluated potential climate-induced changes on the geographical distribution of schistosomiasis in Zimbabwe using prevalence data from two points in time, 29 years apart; to our knowledge, this is the first study investigating this over such a long time period. We applied historical weather data and matched prevalence data of two schistosome species (Schistosoma haematobium and S. mansoni). For each time period studied, a Bayesian geostatistical model was fitted to a range of climatic, environmental and other potential risk factors to identify significant predictors that could help us to obtain spatially explicit schistosomiasis risk estimates for Zimbabwe. The observed general downward trend in schistosomiasis prevalence for Zimbabwe from 1981 and the period preceding a survey and control campaign in 2010 parallels a shift towards a drier and warmer climate. However, a statistically significant relationship between climate change and the change in prevalence could not be established.

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Author Biography

Ulrik B. Pedersen, Department of Disease Biology, Faculty of Health Sciences and Medical Sciences, University of Copenhagen, Frederiksberg
PhD
Published
2017-05-08
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Section
Original Articles
Keywords:
Schistosomiasis, Climate change, Zimbabwe, Geospatial prediction
Statistics
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How to Cite
Pedersen, U. B., Karagiannis-Voules, D.-A., Midzi, N., Mduluza, T., Mukaratirwa, S., Fensholt, R., Vennervald, B. J., Kristensen, T. K., Vounatsou, P., & Stensgaard, A.-S. (2017). Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?. Geospatial Health, 12(1). https://doi.org/10.4081/gh.2017.505