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Spatio-temporal two-stage models for environmental health studies

Novel big data resources offer exceptional opportunities for environmental research, allowing linkage of health data with high-resolution exposure measurements in large populations and study areas. However, this new setting presents important analytical and computational issues, including: (i) issues in modelling potentially complex associations varying over spatial and temporal units; (ii) consideration of confounders and effect modifiers measured at different geographical levels; (iii) the exceptional computational burden of performing analyses spanning entire countries and several decades.

In this contribution, we present a novel spatio-temporal two-stage design to perform small-area analyses in environment-health epidemiological investigations. This framework will be illustrated in a small-area analysis of temperature-mortality associations using data collected in 34,753 Lower Layer Super Output Areas (LSOAs) in England and Wales in the period 1981-2018, including 9,697,753 deaths. Different designs are defined and applied to investigate geographical differences in the increased risks associated to heat and cold, to explore potential temporal variations, and to assess spatially and time-varying characteristics that can potentially modify the relationships.



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