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Endemic malaria in most of the hot and humid African climates is the leading cause of morbidity and mortality. In the last twenty or so years the incidence of malaria has been aggravated by the resurgence of highland malaria epidemics which hitherto had been rare. A close association between malaria epidemics and climate variability has been reported but not universally accepted. Similarly, the relationship between climate variability, intensity of disease mortality and morbidity coupled with socio-economic factors has been mooted. Analyses of past climate (temperature and precipitation), hydrological and health data , and socio-economics status of communities from the East African highlands confirm the link between climate variability and the incidence and severity of malaria epidemics. The communities in the highlands that have had less exposure to malaria are more vulnerable than their counterparts in the lowlands due to lack of clinical immunity. However, the vulnerability of human health to climate variability is influenced by the coping and adaptive capacities of an individual or community. Surveys conducted among three communities in the East African highlands reveal that the interplay of poverty and other socio-economic variables have intensified the vulnerability of these communities to the impacts of malaria.

This study investigated the trends and variability of seasonal and annual rainfall and temperature data over southern Ethiopia using time series analysis for the period 1983–2016. Standard Anomaly Index (SAI), Coefficient of Variation (CV), Precipitations Concentration Index (PCI), and Standard Precipitation Index (SPI) were used to examine rainfall variability and develop drought indices over southern Ethiopia. Temporal changes of rainfall trends over the study period were detected using Mann Kendall (MK) trend test and Sen’s slope estimator. The results showed that the region experienced considerable rainfall variability and change that resulted in extended periods of drought and flood events within the study period. Results from SAI and SPI indicated an inter-annual rainfall variability with the proportions of years with below and above normal rainfall being estimated at 56% and 44% respectively. Results from the Mann Kendall trend test indicated an increasing trend of annual rainfall, Kiremt (summer) and Bega (dry) seasons whereas the Belg (spring) season rainfall showed a significant decreasing trend (p < 0.05). The annual rate of change for mean, maximum and minimum temperatures was found to be 0.042 °C, 0.027 °C, and 0.056 °C respectively. The findings from this study can be used by decision-makers in taking appropriate measures and interventions to avert the risks posed by changes in rainfall and temperature variability including extremes in order to enhance community adaptation and mitigation strategies in southern Ethiopia.

Rivers in the Lake Victoria Basin support a multitude of ecosystem services, and the economies of the riparian countries (Kenya, Tanzania, Uganda, Rwanda, and Burundi) rely on their discharge, but projections of their future discharges under various climate change scenarios are not available. Here, we apply Vector Autoregressive Moving Average models with eXogenous variables (VARMAX) statistical models to project hydrological discharge for 23 river catchments for the 2015-2100 period, under three representative concentration pathways (RCPs), namely RCPs 2.6, 4.5, and 8.5. We show an intensification of future annual rainfall by 25% in the eastern and 5-10% in the western part of the basin. At higher emission scenarios, the October to December season receives more rainfall than the March to May season. Temperature projections show a substantial increase in the mean annual minimum temperature by 1.3-4.5 • C and warming in the colder season (June to September) by 1.7-2.9 • C under RCP 4.5 and 4.9 • C under RCP 8.5 by 2085. Variability in future river discharge ranges from 5-267%, increases with emission intensity, and is the highest in rivers in the southern and south eastern parts of the basin. The flow trajectories reveal no systematic trends but suggest marked inter-annual variation, primarily in the timing and magnitude of discharge peaks and lows. The projections imply the need for coordinated transboundary river management in the future.is anticipated that climate change will continue to affect river hydrology and ecology through changes in rainfall distribution, soil moisture, river flows, and groundwater levels [11,12]. Recent fluctuations in river levels have had adverse impacts on the social, economic, and environmental well-being of many African communities [13,14]. Major changes in mean river discharge can have devastating impacts, particularly in Africa.Rainfall deficits of between 7% and 29% in East Africa between 1961 to 2010 led to sharp reductions in agricultural output and employment and also resulted in significant losses in Gross Domestic Product (GDP) [15]. Similar economic losses associated with drought conditions have occurred in West Africa, Australia, California, and Southern Africa [16][17][18][19][20]. Such losses emphasize the economic connection of climate and hydrology to water and sanitation, agriculture, fisheries, and energy sectors. Consequently, multiscalar present and future climate change studies are valuable for advancing scientific understanding and providing information for decision making in adaptation and mitigation strategies to deal with widening variability in river flows [21,22].Other threats to freshwater that are exacerbated by climate change include increased river siltation resulting from high soil erosion in the basin, recurrent destructive floods in the low-lying areas, riparian land encroachment, degradation of river banks, eutrophication, and proliferation of the invasive water hyacinth [23,24]. Increasing intensity and frequency of extreme climatic events pose ad...

BackgroundRift Valley fever (RVF) is a vector-borne zoonotic disease that has an impact on human health and animal productivity. Here, we explore the use of vector presence modelling to predict the distribution of RVF vector species under climate change scenario to demonstrate the potential for geographic spread of Rift Valley fever virus (RVFV).ObjectivesTo evaluate the effect of climate change on RVF vector distribution in Baringo County, Kenya, with an aim of developing a risk map for spatial prediction of RVF outbreaks.MethodologyThe study used data on vector presence and ecological niche modelling (MaxEnt) algorithm to predict the effect of climatic change on habitat suitability and the spatial distribution of RVF vectors in Baringo County. Data on species occurrence were obtained from longitudinal sampling of adult mosquitoes and larvae in the study area. We used present (2000) and future (2050) Bioclim climate databases to model the vector distribution.ResultsModel results predicted potential suitable areas with high success rates for Culex quinquefasciatus, Culex univitattus, Mansonia africana, and Mansonia uniformis. Under the present climatic conditions, the lowlands were found to be highly suitable for all the species. Future climatic conditions indicate an increase in the spatial distribution of Cx. quinquefasciatus and M. africana. Model performance was statistically significant.ConclusionSoil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.