Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/189
Title: BURULI ULCER MORBIDITY AND SOIL ARSESENIC LINKAGESIN THE AMANSIE WEST DISTRICT OF GHANA: A GEOSTATISTICAL APPROACH
Authors: Bonyah, E.
Owusu-Sekyere, E.
Harris, E.
Keywords: Geostatistics
Kriging
Risk semivariogram
Buruli ulcer
Weighted least-square regression
Correlation
Issue Date: 2013
Publisher: Asian Journal of Science and Technology
Series/Report no.: Vol. 4;Issue 03
Abstract: Buruli ulcer, a disease caused by infection with Mycobacterium ulcerans, is one of the most neglected but treatable tropical diseases. The causative organism is from the family of bacteria which causes tuberculosis and leprosy but knowledge gaps exist on the exact mode of transmission. The aim of this paper is to examine the link between the Buruli ulcer morbidity and Soil Arsenic concentration in the Amansie Wes t District of Ghana using kriging method. This paper provides the application of kriging to the spatial interpolation of local disease rates on the district boundary and soil map, resulting in continuous maps of disease rate estimate. It again provides the application of kriging to arsenic sample data in Amansie West District as a covariates variable. The spatial analysis was confined to settlements located within 60 kilometers from the Amansie West District to avoid underestimating the risk of the disease incidence. Semivariogram models revealed a range of autocorrelation of 1.9 km for the Buruli ulcer disease and 17.9 km for arsenic risk. There are large patches in both southern and northeastern part of the kriged map indicating that all the soil types are susceptible to BU disease. However, the entire area has high level of arsenic concentration than recommended level by World Health Organization. The geographically weighted correlation between arsenic and Buruli ulcer estimated was 0.9 and below. The approach presented in this paper enables researchers to incorporate the pattern of spatial dependence of incidence rates into the mapping of risk values and the quantification of the associated uncertainty.
URI: http://hdl.handle.net/123456789/189
ISSN: 0976-3376
Appears in Collections:Faculty of Integrated Development Studies

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