There is an extensive literature describing temperature-mortality associations in developed regions, but research from developing countries, and Africa in particular, is limited. We conducted a time-series analysis using daily temperature data and a national dataset of all 8.8 million recorded deaths in South Africa between 1997 and 2013. Mortality and temperature data were linked at the district municipality level and relationships were estimated with a distributed lag non-linear model with 21 days of lag, and pooled in a multivariate meta-analysis. We found an association between daily maximum temperature and mortality. The relative risk for all-age all-cause mortality on very cold and hot days (1st and 99th percentile of the temperature distribution) was 1.14 (1.10,1.17) and 1.06 (1.03,1.09), respectively, when compared to the minimum mortality temperature. This "U" shaped relationship was evident for every age and cause group investigated, except among 25-44 year olds. The strongest associations were in the youngest (< 5) and oldest (> 64) age groups and for cardiorespiratory causes. Heat effects occurred immediately after exposure but diminished quickly whereas cold effects were delayed but persistent. Overall, 3.4% of deaths (~ 290,000) in South Africa were attributable to non-optimum temperatures over the study period. We also present results for the 52 district municipalities individually. An assessment of the largest-ever dataset for analyzing temperature-mortality associations in (South) Africa indicates mortality burdens associated with cold and heat, and identifies the young and elderly as particularly vulnerable.

In this article, we study the historical temperature and precipitation series for Turin and investigate the origins and effects of the city's urban heat island. The data under study are part of some of the longest meteorological data series for the whole of Italy. The findings detailed here are the result of historical research and the retrieval of data regarding climate parameters and associated metadata. We performed quality control assessments and used a homogenisation process to remove possible errors which may have occurred in the recording of the data. We also analysed changes and trends in climate and climatic index data for a 147‐year period (1870–2016), and compared thermometric data from four rural stations with the Turin series to evaluate the urban heat island effect. Finally, we assessed a number of empirical models based on the number of inhabitants, the extent of urban growth and the increase in private and public transport usage in Turin to identify the urban heat island's evolution.