A Geo-Statistical Analysis of the Impact of Ecological and Environmental Risks on Epidemiology in the South-west, Nigeria

Kehinde Adekunle Bashiru; Taiwo Adetola  Ojurongbe; Olusola  Fadipe; Joshua  Okeke; Habeeb  Abiodun Afolabi; Nureni Olawale  Adeboye; Iwa Abiola  Akanni

doi:10.18502/jehsd.v8i1.12320

Kehinde Adekunle Bashiru Department of Statistics, Osun State University, Osogbo, Nigeria.
Taiwo Adetola Ojurongbe Department of Statistics, Osun State University, Osogbo, Nigeria.
Olusola Fadipe Department of Civil Engineering, Osun State University, Osogbo, Nigeria.
Joshua Okeke Department of Mathematical and Statistics, University of New Mexico, Albuquerque NMUSA.
Habeeb Abiodun Afolabi Department of Statistics, Osun State University, Osogbo, Nigeria.
Nureni Olawale Adeboye Department of Statistics, Osun State University, Osogbo, Nigeria.
Iwa Abiola Akanni Department of Physics, Osun State University, Osogbo, Nigeria.

DOI: https://doi.org/10.18502/jehsd.v8i1.12320

Keywords: Sanitation, Biological Factors, Fuzzy Logic, Epidemiology.

Abstract

Introduction: The probability of contamination is frequently elevated in scenarios where a well and pit latrine coexist, or in situations where heavy rain causes the overflow of open excreta dumps, which in turn flush into wells and surface water. Many possible negative health effects might arise from exposure to various ecological and biological agents in the environment. Therefore, there is a need to examine the risk of disease transmission in Ife North Local Government Area (LGA) of Osun state, using epidemiological, environmental, and ecological factors.

Materials and Methods: Geostatistical analysis was used to examine the epidemiological risk, based on various environmental, biological, and ecological variables. The technique employed demonstrated the complexity and multiple parameters that raise the probability of an epidemic. The Shapiro-Wilk test was used to determine whether or not the data were normally distributed. Fuzzy logic, correlation, and spline surface interpolation analysis were conducted using ArcGIS 10.3 and ENVI 5.0 software. Three levels of epidemic risk were used to construct the disease surveillance and projection maps.

Results: According to the final susceptibility map, 8.08 km² of 460.12 km² of the research area were considered to be at very low risk for an epidemic, followed by 364.98km² of low risk and 87.06km² of moderate risk areas, with percentages of 1.75%, 79.32%, and 18.92%, respectively.

Conclusion: A very substantial correlation was observed between biological and ecological components and water-borne diseases. It is, therefore, advised that all water sources be treated before consumption, and community involvement be encouraged in environmental sanitation programs.