Millions of dollars have been spent in fighting malaria in Namibia. However, malaria remains a major public health concern in Namibia, mostly in Kavango West and East, Ohangwena and Zambezi region. The primary goal of this study was to fit a spatio-temporal model that profiles spatial variation in malaria risk areas and investigate possible associations between disease risk and environmental factors at the constituency level in highly risk northern regions of Namibia. METHODS: Malaria data, climatic data, and population data were merged and Global spatial autocorrelation statistics (Moran’s I) was used to detect the spatial autocorrelation of malaria cases while malaria occurrence clusters were identified using local Moran statistics. A hierarchical Bayesian CAR model (Besag, York and Mollie’s model “BYM”) known to be the best model for modelling the spatial and temporal effects was then fitted to examine climatic factors that might explain spatial/temporal variation of malaria infection in Namibia. RESULTS: Average rainfall received on an annual basis and maximum temperature were found to have a significant spatial and temporal variation on malaria infection. Every mm increase in annual rainfall in a specific constituency in each year increases annual mean malaria cases by 0.6%, same to average maximum temperature. The posterior means of the time main effect (year t) showed a visible slightly increase in global trend from 2018 to 2020. CONCLUSION: The study discovered that the spatial temporal model with both random and fixed effects best fit the model, which demonstrated a strong spatial and temporal heterogeneity distribution of malaria cases (spatial pattern) with high risk in most of the Kavango West and East outskirt constituencies, posterior relative risk (RR: 1.57 to 1.78).
The scale of climate migration across the Global South is expected to increase during this century. By 2050, millions of Africans are likely to consider, or be pushed into, migration because of climate hazards contributing to agricultural disruption, water and food scarcity, desertification, flooding, drought, coastal erosion, and heat waves. However, the migration-climate nexus is complex, as is the question of whether migration can be considered a climate change adaptation strategy across both the rural and urban space. Combining data from household surveys, key informant interviews, and secondary sources related to regional disaster, demographic, resource, and economic trends between 1990 and 2020 from north central and central dryland Namibia, we investigate (i) human migration flows and the influence of climate hazards on these flows and (ii) the benefits and dis-benefits of migration in supporting climate change adaptation, from the perspective of migrants (personal factors and intervening obstacles), areas of origin, and areas of destination. Our analysis suggests an increase in climate-related push factors that could be driving rural out-migration from the north central region to peri-urban settlements in the central region of the country. While push factors play a role in rural-urban migration, there are also several pull factors (many of which have been long-term drivers of urban migration) such as perceived higher wages, diversity of livelihoods, water, health and energy provisioning, remittances, better education opportunities, and the exchange of non-marketed products. Migration to peri-urban settlements can reduce some risks (e.g. loss of crops and income due to climate extremes) but amplify others (e.g. heat stress and insecure land tenure). Adaptation at both ends of the rural-urban continuum is supported by deeply embedded linkages in a model of circular rural-urban-rural migration and interdependencies. Results empirically inform current and future policy debates around climate mobilities in Namibia, with wider implications across Africa.
