The short-term association between environmental variables and mortality: evidence from Europe

Using fine-grained, publicly available data, this paper studies the short-term association between environmental factors, i.e., weather and air pollution characteristics, and weekly mortality rates in small geographical regions in Europe. Hereto, we develop a mortality modeling framework where a baseline model describes a region-specific, seasonal trend observed within the historical weekly mortality rates. Using a machine learning algorithm, we then explain deviations from this baseline using features constructed from environmental data that capture anomalies and extreme events. We illustrate our proposed modeling framework through a case study on more than 550 NUTS 3 regions (Nomenclature of Territorial Units for Statistics, level 3) in 20 European countries. Using interpretation tools, we unravel insights into which environmental features are most important when estimating excess or deficit mortality relative to the baseline and explore how these features interact. Moreover, we investigate harvesting effects through our constructed weekly mortality modeling framework. Our findings show that temperature-related features are most influential in explaining mortality deviations from the baseline over short time periods. Furthermore, we find that environmental features prove particularly beneficial in southern regions for explaining elevated levels of mortality, and we observe evidence of a harvesting effect related to heat waves.