What is it about?
EWM is influenced by temperature, latitude, age, gender, ethnicity, and winter infectious outbreaks including influenza. Winter outbreaks are made worse by lower temperature than normal. EWM also shows high within-country variation and this variation seems to be highest during infectious outbreaks, which are known to show high spatial granularity.
Featured Image
Photo by Vidar Nordli-Mathisen on Unsplash
Why is it important?
Historically EWM was used to demonstrate the role of maintaining indoor temperature during winter as a means of reducing winter mortality. However, due to the multitude of factors involved in EWM it cannot be used as a metric to demonstrate the success of warm home initiatives.
Perspectives
This was a novel adaptation of EWM in which the EWM calculation was turned from a static to a rolling calculation. The rolling calculation allows detection of peaks in EWM outside the usual static time frame. It shows that EWM is a highly nuanced measure of the wider environment.
Dr Rodney P Jones
Healthcare Analysis & Forecasting
Read the Original
This page is a summary of: Excess Winter Mortality (EWM) as a Dynamic Forensic Tool: Where, When, Which Conditions, Gender, Ethnicity and Age, International Journal of Environmental Research and Public Health, February 2021, MDPI AG,
DOI: 10.3390/ijerph18042161.
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