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Geospatial Assessment of Potential Areas for Arthropod-Vectors of Rift Valley Fever Virus (RVFV) Across Nigeria Using Modis-Ndvi Dataset

Author

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  • Sadiq Abdullahi Yelwa

    (Department of Environmental and Resources Management, Usmanu Danfodiyo University, P.M.B 2346, Sokoto, Nigeria)

  • Salawu Onoruoiza Ganiyu

    (Department of Geography, Nigerian Defence Academy, P.M.B. 2109, Kaduna)

  • Abubakar Umar

    (Department of Geography, Nigerian Defence Academy, P.M.B. 2109, Kaduna)

Abstract

Rift Valley Fever Virus (RVFV) is an arthropod-borne viral disease that affects both domestic animals as well as human beings. The outbreaks of such disease especially in Africa are reported to be closely related to areas of above or below normal rainfall that is associated with the warm phase of El-Niňo Southern Oscillations (ENSO) phenomenon. This ENSO event is as a result of abnormal change in sea surface temperature that affects global precipitation and in other areas, vegetation biomass. For a sustainable healthy environment and healthy livestock production in Nigeria under the present economic circumstances, this study therefore, suggests a cost-effective technique for mapping out spatial patterns of likely RVFV and other vector-borne disease habitats across Nigeria. Remote Sensing and GIS can be a cost-effective component of disease control campaign for mapping out potential areas at risk of such diseases. Principal Component Analysis (PCA) technique was used where Standardised Principal Components images and their corresponding loading scores were derived from Normalised Difference Vegetation Index (MODIS-NDVI) dataset acquired from USGS-EROS Data Center for the ENSO event of September 2014 to December 2015 covering Nigeria and parts of surrounding countries. The results on the first principal component image showed a characteristic vegetation biomass pattern across Nigeria over the entire time-series. The second component shows a cyclic trend related to climatic variations and vegetation across the country. A threshold in the PCA was used to isolate and produce a potential risk areas map primarily considered to have potential of RVFV and other arthropod-borne disease across the country. For sustainable ecological environment and healthy livestock production in Nigeria the results derived from this study would provide public health authorities like epidemiological departments and other stakeholders with a working document for animal disease reporting system which would also cut down operational costs.

Suggested Citation

  • Sadiq Abdullahi Yelwa & Salawu Onoruoiza Ganiyu & Abubakar Umar, 2024. "Geospatial Assessment of Potential Areas for Arthropod-Vectors of Rift Valley Fever Virus (RVFV) Across Nigeria Using Modis-Ndvi Dataset," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(15), pages 116-123, August.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:15:p:116-123
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    References listed on IDEAS

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    1. Jörn P W Scharlemann & David Benz & Simon I Hay & Bethan V Purse & Andrew J Tatem & G R William Wint & David J Rogers, 2008. "Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-13, January.
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