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Mapping Transmission Risk of Lassa Fever in West Africa: The Importance of Quality Control, Sampling Bias, and Error Weighting

Overview of attention for article published in PLOS ONE, August 2014
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Title
Mapping Transmission Risk of Lassa Fever in West Africa: The Importance of Quality Control, Sampling Bias, and Error Weighting
Published in
PLOS ONE, August 2014
DOI 10.1371/journal.pone.0100711
Pubmed ID
Authors

A. Townsend Peterson, Lina M. Moses, Daniel G. Bausch

Abstract

Lassa fever is a disease that has been reported from sites across West Africa; it is caused by an arenavirus that is hosted by the rodent M. natalensis. Although it is confined to West Africa, and has been documented in detail in some well-studied areas, the details of the distribution of risk of Lassa virus infection remain poorly known at the level of the broader region. In this paper, we explored the effects of certainty of diagnosis, oversampling in well-studied region, and error balance on results of mapping exercises. Each of the three factors assessed in this study had clear and consistent influences on model results, overestimating risk in southern, humid zones in West Africa, and underestimating risk in drier and more northern areas. The final, adjusted risk map indicates broad risk areas across much of West Africa. Although risk maps are increasingly easy to develop from disease occurrence data and raster data sets summarizing aspects of environments and landscapes, this process is highly sensitive to issues of data quality, sampling design, and design of analysis, with macrogeographic implications of each of these issues and the potential for misrepresenting real patterns of risk.

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Geographical breakdown

Country Count As %
Italy 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Nigeria 1 <1%
Unknown 134 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 19%
Student > Master 26 19%
Student > Ph. D. Student 17 12%
Student > Bachelor 12 9%
Other 9 6%
Other 23 17%
Unknown 25 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 23%
Medicine and Dentistry 21 15%
Biochemistry, Genetics and Molecular Biology 11 8%
Environmental Science 9 6%
Nursing and Health Professions 8 6%
Other 24 17%
Unknown 34 24%