SPATIO-TEMPORAL DYNAMICS OF MALARIA EPIDEMIOLOGY IN ONDO STATE, SOUTHWESTERN NIGERIA

Abstract

Malaria is an infectious disease that poses threats to many countries and it is the major causes of morbidity and mortality in tropical countries including Nigeria. Thus, this study has examined the spatio-temporal dynamics of malaria epidemiology pattern in Ondo State. ArcGIS 10.4 and QGIS software were used to analyse malaria spatial pattern from 2013 to 2017 and malaria influencing factors (the Land use/land cover, slope and elevation) of Ondo state. A statistical analysis using SPSS was adopted for multiple linear regression analysis in examine the relationship between meteorological variables and malaria incidence thereby finding the most significant malaria determinant (temperature). A multi-criteria analysis using Analytical Hierarchical Process (AHP) was employed in analysing the factors influencing malaria transmission in Ondo state. This basically reveals the dynamics of the malaria incidence among pregnant women and children (age ≤9) from 2013 to 2017. The finding shows that children had the highest percentage of infection and they are considered to be the first category of people vulnerable to malaria in Ondo state and this is in agreement with the world Health Organisation annual global findings on malaria. The finding indicates that there was a steady increase of the disease among the children overtime, particularly in Akoko South West, Odigbo, Okitipupa, Ondo East, and Owo LGAs but there was rapid significant variation in Akoko South West, Owo and Ondo East. While among the pregnant women the incidence rate was not increasing constantly but minimal compare to the children. The general trend analysis of the disease incidence reveals that in 2016 and 2017 there was a rapid increase of malaria occurrence virtually in all the LGAs with the exception of Akure South. From the finding temperature was the most significant meteorological variables influencing malaria proliferation in Ondo state and other environmental factors causing the transmission include vegetation, waterbodies, slope, elevation among others. The study identified the high-risk areas and the hot spots were virtually found in most of the LGAs with the exception of Okitipupa, while Ondo East, Akure South, Akoko South west and Owo LGAs appeared to be the most susceptible areas. The recommendations drawn out of the study include that more in-depth epidemiological studies on malaria should be conducted in Ondo State and other parts of Nigeria so as to consider more environmental factors influencing malaria incidence, the hospital management boards should improve on disease data quality for access to quality data, also researchers should adopt Remote Sensing and GIS Technologies in future malaria research for thorough studies. Keywords: Spatio-temporal, Malaria, Dynamics, Epidemiology