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Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence
Rift Valley fever (RVF) is a zoonotic disease affecting humans and animals. It is caused by RVF virus transmitted primarily by Aedes mosquitoes. The data presented in this article propose environmental layers suitable for mapping RVF vector habitat zones and livestock migratory routes. Using species...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738198/ https://www.ncbi.nlm.nih.gov/pubmed/29276743 http://dx.doi.org/10.1016/j.dib.2017.11.097 |
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author | Mosomtai, Gladys Evander, Magnus Mundia, Charles Sandström, Per Ahlm, Clas Hassan, Osama Ahmed Lwande, Olivia Wesula Gachari, Moses K. Landmann, Tobias Sang, Rosemary |
author_facet | Mosomtai, Gladys Evander, Magnus Mundia, Charles Sandström, Per Ahlm, Clas Hassan, Osama Ahmed Lwande, Olivia Wesula Gachari, Moses K. Landmann, Tobias Sang, Rosemary |
author_sort | Mosomtai, Gladys |
collection | PubMed |
description | Rift Valley fever (RVF) is a zoonotic disease affecting humans and animals. It is caused by RVF virus transmitted primarily by Aedes mosquitoes. The data presented in this article propose environmental layers suitable for mapping RVF vector habitat zones and livestock migratory routes. Using species distribution modelling, we used RVF vector occurrence data sampled along livestock migratory routes to identify suitable vector habitats within the study region which is located in the central and the north-eastern part of Kenya. Eleven herds monitored with GPS collars were used to estimate cattle utilization distribution patterns. We used kernel density estimator to produce utilization contours where the 0.5 percentile represents core grazing areas and the 0.99 percentile represents the entire home range. The home ranges were overlaid on the vector suitability map to identify risks zones for possible RVF exposure. Assimilating high spatial and temporal livestock movement and vector distribution datasets generates new knowledge in understanding RVF epidemiology and generates spatially explicit risk maps. The results can be used to guide vector control and vaccination strategies for better disease control. |
format | Online Article Text |
id | pubmed-5738198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-57381982017-12-22 Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence Mosomtai, Gladys Evander, Magnus Mundia, Charles Sandström, Per Ahlm, Clas Hassan, Osama Ahmed Lwande, Olivia Wesula Gachari, Moses K. Landmann, Tobias Sang, Rosemary Data Brief Environmental Science Rift Valley fever (RVF) is a zoonotic disease affecting humans and animals. It is caused by RVF virus transmitted primarily by Aedes mosquitoes. The data presented in this article propose environmental layers suitable for mapping RVF vector habitat zones and livestock migratory routes. Using species distribution modelling, we used RVF vector occurrence data sampled along livestock migratory routes to identify suitable vector habitats within the study region which is located in the central and the north-eastern part of Kenya. Eleven herds monitored with GPS collars were used to estimate cattle utilization distribution patterns. We used kernel density estimator to produce utilization contours where the 0.5 percentile represents core grazing areas and the 0.99 percentile represents the entire home range. The home ranges were overlaid on the vector suitability map to identify risks zones for possible RVF exposure. Assimilating high spatial and temporal livestock movement and vector distribution datasets generates new knowledge in understanding RVF epidemiology and generates spatially explicit risk maps. The results can be used to guide vector control and vaccination strategies for better disease control. Elsevier 2017-12-06 /pmc/articles/PMC5738198/ /pubmed/29276743 http://dx.doi.org/10.1016/j.dib.2017.11.097 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Environmental Science Mosomtai, Gladys Evander, Magnus Mundia, Charles Sandström, Per Ahlm, Clas Hassan, Osama Ahmed Lwande, Olivia Wesula Gachari, Moses K. Landmann, Tobias Sang, Rosemary Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title | Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title_full | Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title_fullStr | Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title_full_unstemmed | Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title_short | Datasets for mapping pastoralist movement patterns and risk zones of Rift Valley fever occurrence |
title_sort | datasets for mapping pastoralist movement patterns and risk zones of rift valley fever occurrence |
topic | Environmental Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738198/ https://www.ncbi.nlm.nih.gov/pubmed/29276743 http://dx.doi.org/10.1016/j.dib.2017.11.097 |
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