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 ¹û¶³´«Ã½Ó°Òô 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.
Speakers
- Antonio Gasparrini
- Matteo Scortichini
Please note that the time listed is Greenwich Mean Time (GMT)
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