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• W3108492083 abstract "Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified 1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave." @default.
• W3108492083 created "2020-12-07" @default.
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• W3108492083 date "2020-11-22" @default.
• W3108492083 modified "2023-09-29" @default.
• W3108492083 title "Community factors and excess mortality in first wave of the COVID-19 pandemic" @default.
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• W3108492083 doi "https://doi.org/10.1101/2020.11.19.20234849" @default.
• W3108492083 hasPublicationYear "2020" @default.
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