PHD-Department of Geography

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Browsing PHD-Department of Geography by Subject "Altitudes of Lower Lake Victoria Basin"

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    Climate Variability and Malaria Transmission Trends in Different Altitudes of Lower Lake Victoria Basin, Kenya.
    (Kenyatta University, 2023-11) Odhiambo, Samwel Olela; George L. Makokha; Kennedy Obiero
    Consequences of global climate variability and change are some of the biggest environmental challenges the world is facing. Impacts include increased frequency of extreme weather events. The impacts vary, Africa being the most vulnerable due to her high dependence on natural resources. One of the issues most associated with the challenges is malaria prevalence. Half of the world’s population, (3.4 billion people in 92 countries), is at risk, 1.1 billion at high risk. Malaria burden is greatest in the developing countries of the tropics such as Africa which has 91% of the related deaths, 60% being children under five years. Climate extremes have increased in East Africa, which is predicted to add 75.9 million people to the risk bracket. In Kenya, malaria is blamed on high rainfall, temperature and relative humidity. This study evaluated climate variability and malaria transmission trends in different altitudes of Lower Lake Victoria Basin (LLVB), Kenya where malaria prevalence rate was 27% despite varying between 4% - 8% in other parts of the country. Descriptive and correlational designs with quantitative methods were used to analyze spatiotemporal variability of selected climate elements and malaria transmission trends. Target population was flooded malaria morbidity cases recorded at Sub – County Hospitals. Meteorological data was obtained per sampled county and sub - county i.e. Migori - SONY Central Meteorological Station, Kisumu - Kisumu Airport Meteorological Station and Kakamega -MSC Meteorological Station. Data for the selected climate parameters were collected for twenty years except Relative Humidity from Kisumu Airport which was only available for 12 years (2009-2020). Health data was obtained from the Kenya Health Information System (KHIS) for ten years (2011 to 2020) through sampled Sub-County Level 4 Hospitals. ANOVA was used to analyze variability among climate and malaria transmission variables, Pearson’s Correlation Coefficient tested relationships while Descriptive Time Series and “ARIMA regression models” were respectively used to give trends and to predict future climate and malaria scenarios. Results revealed that Malaria transmission and climatic variables significantly varied in space and time. Mean annual malaria transmission in Kisumu was 3902.87, Kakamega 3385.53 and Migori 2130.33. Mean annual temperature was 23.770C in Kisumu, 22.610C in Kakamega and 22.520C in Migori. The two had insignificant monthly and annual correlations. However, climate elements insignificantly defined transmission differently at different altitudes. In a further analysis, stepwise linear regression dropped all climatic variables and left only altitude as the significant determinant of malaria transmission variability in the LLVB. This made the study use altitude and transmission levels to zone LLVB as follows: 1001m to 1200m – high transmission; 1201 to 1400 - medium transmission; 1401 to 1600 – low transmission. The study predicted that malaria transmission would increase in high and medium transmission zones while decreasing in low transmission zones. This meant that malaria prevalence would still vary depending on altitude. The revelations were used to inform experts in policy decision making on reduction of malaria transmission. This was to enhance malaria eradication processes in the LLVB, Kenya, and hence promote the realization of Kenya’s vision 2030.