Modeling The Climatic And Socio-Demographic Influence On Malaria Transmission In Accra

Abstract Climate change and variability affect the suitability of environmental conditions for malaria transmission. Although malaria transmission is place-specific, existing assessments of malaria transmission have largely focused on large-scale changes in malaria transmission and overlooked the socio-demographic factors that modulate climate and malaria nexus with the result largely indicating widespread increase in areas suitable for malaria transmission. In its recent assessment report, the Intergovernmental Panel on Climate Change (IPCC) observed the lack of models that incorporate modulating factors in malaria transmission and emphasizes the need for such models to adequately account for local level transmissions. In the context of climate change and variability, and population dynamics, the present study modelled malaria transmission over Accra, accounting not only for the climatic but actual socio-demographic factors for current and different future climatic scenarios at the macro level. The study also assessed socio-demographic and environmental factors influencing malaria incidence at the micro level. The main sources of data used include time series rainfall and temperature data for Accra (1970-2010) from the Ghana Meteorological Agency (GMeT) and census-based demographic data (1970-2010). In addition, cross-sectional household data from three selected coastal communities (James Town, Ussher Town and Agbogbloshie) in Accra were also used. To facilitate future assessment of malaria transmission, both climatic and demographic data were projected using Bergen Climate Model Version 2 and Spectrum respectively. While the VECTRI was used in analysing the climatic and demographic data, Binary Logistic Regression was employed to estimate malaria incidence and coping/adaptation strategies in the household. The results indicated increasing and temporal variability of rainfall and temperature while population also shows an increasing trend in spite of the declining population growth rate. Moreover, similar trend was observed for the future scenario (climatic and demographic factors). At the macro level, compared with the un-adjusted estimation, the population adjusted models show relatively lower malaria transmission levels presently and in the future. Annual malaria transmission shows significantly declining trend over time. There is also observed seasonal shift in the significant malaria transmission months. Results of the micro level analyses showed that socio-demographic factors significantly have far-reaching influence on malaria incidence than climatic factors. In the multiple regression analyses, experience of flooding did not have a significant influence on malaria incidence. The type of toilet facility used, malaria risk perception, the age of household head and the use of coping/adaptation measures were significant predictors of malaria incidence. Particularly, age of household head was positively related with malaria incidence. Comparatively, households that used flush toilet facility had higher risk of malaria incidence. The use of coping/adaptation measures was also significantly related with malaria incidence. The findings suggest the need to account for actual socio-demographic effects besides the climatic conditions for more accurate malaria transmission estimations to guarantee acceptable transmission levels for appropriate and effective interventions to sustain decline in malaria transmission. There is also the need to intensify and scale up the use of household coping/adaptation strategies to minimise malaria incidence. Key words: Climate, Population, Malaria, transmission, Coping/adaptation.