Bett, B.; Lindahl, J.F.; Wanyoike, S.; Grace, D.
Rift Valley fever virus seroprevalence data from cattle, sheep and goats sampled in a cross sectional survey in Tana River County, Kenya (2013)
Cite this dataset as:
Bett, B.; Lindahl, J.F.; Wanyoike, S.; Grace, D. (2017). Rift Valley fever virus seroprevalence data from cattle, sheep and goats sampled in a cross sectional survey in Tana River County, Kenya (2013). NERC Environmental Information Data Centre. https://doi.org/10.5285/b9756c4c-9894-4147-a260-a79067604a06
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© International Livestock Research Institute (Kenya)
This dataset is made available under the terms of the Open Government Licence
https://doi.org/10.5285/b9756c4c-9894-4147-a260-a79067604a06
These data provide results from serological analysis carried out on serum collected from cattle (sample number = 460), goats (sample number = 949) and sheep (Sample number = 574) combined with data collected at the household and subject/animal levels at the time of serum sampling. The data collected at the household and subject/animal levels were: the total number of livestock owned by a household, altitude, geographical coordinates of the sampling sites; and breed, age, sex and body condition score of an animal. The research was carried out in irrigated and non-irrigated areas in Tana River County, Kenya. Field surveys were implemented in August to November 2013 and laboratory analyses were completed in June 2015. Serum samples were harvested from blood samples obtained from animals and screened for anti-Rift Valley Fever (RVF) virus immunoglobulin G using inhibition (enzyme-linked immunosorbent assay) ELISA immunoassay. The household data was collected using Open Data Kit (ODK) loaded into smart phones. The serological analysis was performed to determine the risk of Rift Valley Fever virus exposure in cattle, sheep and goats. The aim of the survey was to investigate whether land use change, specifically the conversion of rangeland into cropland, affected RVF exposure pattern in livestock.
The data were collected by experienced researchers from the Ministry of Livestock Development Nairobi, Kenya and the International Livestock Research Institute (Kenya).
This dataset is part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC project no NE-J001570-1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Additional funding was provided by Consultative Group on International Agricultural Research (CGIAR) Research Program Agriculture for Nutrition and Health led by International Food Policy Research Institute (IFPRI).
The data were collected by experienced researchers from the Ministry of Livestock Development Nairobi, Kenya and the International Livestock Research Institute (Kenya).
This dataset is part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC project no NE-J001570-1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Additional funding was provided by Consultative Group on International Agricultural Research (CGIAR) Research Program Agriculture for Nutrition and Health led by International Food Policy Research Institute (IFPRI).
Publication date: 2017-03-08
View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)
Format
Comma-separated values (CSV)
Spatial information
Study area
Spatial representation type
Tabular (text)
Spatial reference system
WGS 84
Provenance & quality
Households and subsequently livestock within the households were randomly selected and recruited into the study. Household data were collected using a short questionnaire that was administered to the household head or his/her representative. Animal characteristics (e.g. age, sex, species, breed, etc.) were obtained using a checklist at the time of blood sampling. These data was uploaded to a server at the International Livestock Research Institute (ILRI) at the end of each day. The data were stored in an on-line database as Microsoft Excel files.
Blood samples were collected from recruited animals through jugular venipuncture. Serum samples were prepared in the field and preserved in dry ice until they were transferred into liquid nitrogen tanks on arrival at the research laboratories at ILRI. These samples were screened for anti-(Rift Valley Fever) RVF virus immunoglobulin G using inhibition ELISA (enzyme-linked immunosorbent assay) immunoassay with the results being kept in a database designed in Microsoft Excel. The final dataset was created by merging field and laboratory data and the merged data were converted into a csv file for ingestion.
Records from each of the files have not been transformed or altered in any way.
Blood samples were collected from recruited animals through jugular venipuncture. Serum samples were prepared in the field and preserved in dry ice until they were transferred into liquid nitrogen tanks on arrival at the research laboratories at ILRI. These samples were screened for anti-(Rift Valley Fever) RVF virus immunoglobulin G using inhibition ELISA (enzyme-linked immunosorbent assay) immunoassay with the results being kept in a database designed in Microsoft Excel. The final dataset was created by merging field and laboratory data and the merged data were converted into a csv file for ingestion.
Records from each of the files have not been transformed or altered in any way.
Licensing and constraints
This dataset is made available under the terms of the Open Government Licence
Cite this dataset as:
Bett, B.; Lindahl, J.F.; Wanyoike, S.; Grace, D. (2017). Rift Valley fever virus seroprevalence data from cattle, sheep and goats sampled in a cross sectional survey in Tana River County, Kenya (2013). NERC Environmental Information Data Centre. https://doi.org/10.5285/b9756c4c-9894-4147-a260-a79067604a06
© International Livestock Research Institute (Kenya)
Related
This dataset is included in the following collections
Dynamic drivers of disease in Africa (DDDAC)
Correspondence/contact details
Bett, B.
International Livestock Research Institute (ILRI) Kenya
30709 Naivasha Rd
Nairobi
00100
KENYA
b.bett@cgiar.org
Nairobi
00100
KENYA
Authors
Bett, B.
International Livestock Research Institute (ILRI) Kenya
Lindahl, J.F.
International Livestock Research Institute (ILRI) Kenya
Grace, D.
International Livestock Research Institute (ILRI) Kenya
Other contacts
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk