Temperature-related morbidity and mortality in Sub-Saharan Africa: a systematic review of the empirical evidence

Abstract

Abstract Background Sub-Saharan Africa (SSA) contributes very little to overall climate change and yet it is estimated to bear the highest burden of climate change, with 34% of the global DALYs attributable to the effects of climate change found in SSA. With the exception of vector-borne diseases, particularly malaria, there is very limited research on human health effects of climate change in SSA, in spite of growing awareness of the region's vulnerability to climate change. Objectives Our objective is to systematically review all studies investigating temperature variability and non-vector borne morbidity and mortality in SSA to establish the state and quality of available evidence, identify gaps in knowledge, and propose future research priorities. Methods PubMed, Ovid Medline and Scopus were searched from their inception to the end of December 2014. We modified the GRADE guidelines to rate the quality of the body of evidence. Results Of 6745 studies screened, 23 studies satisfied the inclusion criteria. Moderate evidence exists to associate temperature variability with cholera outbreaks, cardiovascular disease hospitalization and deaths, and all-cause deaths in the region. The quality of evidence on child undernutrition is low, and for diarrhea occurrence, meningitis, Ebola, asthma and respiratory diseases, and skin diseases, very low. Conclusions The evidence base is somehow weakened by the limited number of studies uncovered, methodological limitations of the studies, and notable inconsistencies in the study findings. Further research with robust study designs and standardized analytical methods is thus needed to produce more credible evidence base to inform climate change preparedness plans and public health policies for improved adaptive capacity in SSA. Investment in meteorological services, and strengthening of health information systems is also required to guarantee timely, up-to-date and reliable data.