Identifying extreme COVID-19 mortality risks in English small areas: a disease cluster approach

The COVID-19 pandemic is having a huge impact worldwide and has highlighted the extent of health inequalities between countries but also in small areas within a country. Identifying areas with high mortality is important both of public health mitigation in COVID-19 outbreaks, and of longer term effo...

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Bibliographic Details
Published in:Stochastic environmental research and risk assessment 2022-10, Vol.36 (10), p.2995-3010
Main Authors: Adin, A., Congdon, P., Santafé, G., Ugarte, M. D.
Format: Article
Language:English
Subjects:
Air quality
Aquatic Pollution
Chemistry and Earth Sciences
Clustering
Computational Intelligence
Computer Science
Coronaviruses
COVID-19
Disease hot spots
Earth and Environmental Science
Earth Sciences
Environment
Epidemics
Health risks
Math. Appl. in Environmental Science
Mathematical models
Morbidity
Mortality
Mortality risk
Original Paper
Pandemics
Physics
Probability Theory and Stochastic Processes
Public health
Statistical analysis
Statistical models
Statistics for Engineering
Viral diseases
Waste Water Technology
Water Management
Water Pollution Control
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Summary:The COVID-19 pandemic is having a huge impact worldwide and has highlighted the extent of health inequalities between countries but also in small areas within a country. Identifying areas with high mortality is important both of public health mitigation in COVID-19 outbreaks, and of longer term efforts to tackle social inequalities in health. In this paper we consider different statistical models and an extension of a recent method to analyze COVID-19 related mortality in English small areas during the first wave of the epidemic in the first half of 2020. We seek to identify hotspots, and where they are most geographically concentrated, taking account of observed area factors as well as spatial correlation and clustering in regression residuals, while also allowing for spatial discontinuities. Results show an excess of COVID-19 mortality cases in small areas surrounding London and in other small areas in North-East and and North-West of England. Models alleviating spatial confounding show ethnic isolation, air quality and area morbidity covariates having a significant and broadly similar impact on COVID-19 mortality, whereas nursing home location seems to be slightly less important.
ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-022-02175-5