Risk factors for increased risk of death from COVID-19 have been identified, 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 in people aged 40 years and older at the community level during the first wave of the pandemic in England, March-May 2020 compared with 2015–2019. 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 with a non-white ethnicity. We found no association between population density or air pollution and excess mortality. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed to avoid further widening of inequalities in mortality patterns as the pandemic progresses. COVID-19-related mortality in England shows geographical variation but the reasons for this are not well understood. This study estimated excess mortality in the first wave of the pandemic and found associations with higher density of care homes, overcrowding, and economic deprivation, but not with population density or air pollution.
【저자키워드】 SARS-CoV-2, Risk factors, Epidemiology, 【초록키워드】 COVID-19, public health, pandemic, Bayesian, Mortality, Variation, risk, Characteristics, healthcare, Impact, death, Community, England, First wave, Care, association, Deprivation, Support, Older, Factor, increased risk, measure, proportion, applied, less, pandemic progresses, 【제목키워드】 Mortality, COVID-19 pandemic, England, First wave, Factor,