Guest Editorial: Weather conditions and population level mortality in resource-poor settings – understanding the past before projecting the future

T his supplement of Global Health Action shows how retrospective, longitudinal, population-based health data from several resource poor settings in Africa and Asia can enhance the understanding of the impact of the variability extremes of weather on mortality. This information is key to our understanding of the local impacts following from climate change, and to the development of adaptation strategies to mitigate such impacts. While the editors realize the strength of the empirical evidence generated, they also emphasize that this is merely a first step in the right direction ‘a proof of principle’ and that there are obvious needs to continue this work by widening and deepening the research efforts. Severe and sometimes devastating consequences are considered to be associated with future climate change, with the largest potential impacts occurring in areas with the least means to adapt. Impacts on health range from those related to malnutrition, fresh water scarcity, and changes in the range and transmission of many infectious diseases to those directly related to weather or climate extremes, such as those caused by tropical storms, floods or heat waves (1). Understanding future hazards and their health impacts is important for adaptation and mitigation policies. The former seeks to build climate change resilience into health systems; the latter brings the information on adverse health impacts into the climate policy debate as a further motivation to reduce net emissions (2). The current understanding of health impacts from climate and weather is much better in high-income countries, while there is a strong belief that the impacts will be much more severe in lowand middle-income countries (LMICs). Although this belief is likely to be true, it still relies on limited empirical evidence. At present there is a lack of studies on the current health impacts from climate and weather on the population health in LMICs, particularly in rural Africa and Asia (1, 3, 4). This gap has immediate consequences for the understanding of the future local impacts on public health in these regions. One important factor related to the scarce evidence is the limited knowledge of even the simplest demographic and health statistics, such as the number of people living in a defined geographical area, the number of people that are born or deceased each year and the actual cause of death. The INDEPTH network has collected high-quality standardized data on demographics and mortality for geographically defined populations over many years, particularly in regions of Africa and Asia (5). This effort has resulted in retrospective high-quality registers representative for regions where such information is rarely known (5). In addition to existing usage and implementation of health policies developed in collaboration with the INDEPTH network, this information can also provide a valuable basis for sound policy and decision-making with respect to climate change mitigation and adaptation. The papers in this supplement of Global Health Action describe the complex relationships between weather conditions and mortality in resource-poor settings of Africa and Asia. This is a first step in the process of learning from the past to understanding the future impacts of climate change. In high-income areas, many studies have focused on the relationship between variability in weather, mortality and health, identifying stressors such as extreme heat and humidity (4, 6) and heavy downpours and floodings (7 10) as highly related to population health. Census and well-established retrospective health register data are commonly used. Analyses have been conducted to study, for example, the severe health impacts caused by extreme heat waves (11), susceptibility and vulnerability factors to temperature extremes (12), years of life lost due to heat and cold exposure (13), health impacts from drinking contaminated water associated with floodings and heavy rainfalls (7, 8), and the evaluation of adaptation measures such as warning systems and related action plans. Many of these studies have analysed the temporal relationship within time series of health conditions and weather exposures (14, 15). The rationale behind these studies is to estimate an expected event rate at a specific time of the year for a specific year, and then compare the observed event rate during specific weather conditions to the expected event rate forming a relative risk. In doing so, these studies incorporate trends and other time-varying factors known to be influential on the outcome necessary for predicting the expected event rates at specific time points, as well as variables related to weather conditions GUEST EDITORIAL