ABSTRACT
At present, there is a significant lack of knowledge of the complex interactions between human, socio-economic structures, the environment and pattern of malaria infections in urban centers. The central aim is to compare the influence of socio-economic variables and environmental variables on the incidence of malaria in Lokoja and Anyigba from the year 2001 to 2010. Remote sensing and GIS techniques were employed to determine the environmental parameters that results in the modification of the landscape. Hospital records of Patients and questionnaire were developed to generate the needed socioeconomic variables for the study. Multiple regression analysis and Z test were employed to ascertain the contributory relationship of these variables to incidence of malaria and to test for significant difference among these variables in Lokoja and Anyigba. The study revealed that malaria incidence of 185 per 1000 persons in lokoja and 616 per 1000 persons in Anyigba is far higher than the global annual incidence of 2 3. 6 per 1000 persons that defines the endemicity of malaria. These relationships are accounted for as the coefficient of determination (R2) of 59.2% in Lokoja and 81.5% in Anyigba at 0.05 level of significance justifies the influence of socioeconomic factors on the high incidence of malaria in the region. The rates of change in built up areas at 23. OJ km2/yr in Lokoja and 2.93km2/yr in Anyigba have greater influence on the rates of change in the Land Surface Temperature and Normalized Difference in Vegetation index of the entire environments thereby making the towns favorable for the breeding of mosquitos’ larvae and the blood feeding of adult mosquitoes. However, a significant difference in the malaria incidence and in the socioeconomic factors within the two towns as accounted for by the different levels of poverty influence on the attitude of the respondents towards seeking treatments and adoption of preventive measures. However, effective enlightenment on the control of malaria and habitats of the vector may fast track the achievement of targets sets by government in reducing malaria incidence by 50% in 2013.
OLUSEYI, I (2022). An Assessment of Malaria Risk Factors in Parts of Kogi State, North Central Nigeria.. Afribary. Retrieved from https://afribary.com/works/an-assessment-of-malaria-risk-factors-in-parts-of-kogi-state-north-central-nigeria-2
OLUSEYI, IFATIMEHIN "An Assessment of Malaria Risk Factors in Parts of Kogi State, North Central Nigeria." Afribary. Afribary, 17 Jun. 2022, https://afribary.com/works/an-assessment-of-malaria-risk-factors-in-parts-of-kogi-state-north-central-nigeria-2. Accessed 23 Dec. 2024.
OLUSEYI, IFATIMEHIN . "An Assessment of Malaria Risk Factors in Parts of Kogi State, North Central Nigeria.". Afribary, Afribary, 17 Jun. 2022. Web. 23 Dec. 2024. < https://afribary.com/works/an-assessment-of-malaria-risk-factors-in-parts-of-kogi-state-north-central-nigeria-2 >.
OLUSEYI, IFATIMEHIN . "An Assessment of Malaria Risk Factors in Parts of Kogi State, North Central Nigeria." Afribary (2022). Accessed December 23, 2024. https://afribary.com/works/an-assessment-of-malaria-risk-factors-in-parts-of-kogi-state-north-central-nigeria-2