Khedmati Morasae Esmaeil, Derbyshire Daniel W, Amini Payam, Ebrahimi Tahera
Research Fellow in Operational Research, Exeter University Business School, University of Exeter, UK.
Department of Public Health and Sports Science, Faculty of Health and Life Science, University of Exeter, UK.
SSM Popul Health. 2024 Feb 7;25:101621. doi: 10.1016/j.ssmph.2024.101621. eCollection 2024 Mar.
A variety of factors are associated with greater COVID-19 morbidity or mortality, due to how these factors influence exposure to (in the case of morbidity) or severity of (in the case of mortality) COVID-19 infections. We use multiscale geographically weighted regression to study spatial variation in the factors associated with COVID-19 morbidity and mortality rates at the local authority level across England (UK). We investigate the period between March 2020 and March 2021, prior to the rollout of the COVID-19 vaccination program. We consider a variety of factors including demographic (e.g. age, gender, and ethnicity), health (e.g. rates of smoking, obesity, and diabetes), social (e.g. Index of Multiple Deprivation), and economic (e.g. the Gini coefficient and economic complexity index) factors that have previously been found to impact COVID-19 morbidity and mortality. The Index of Multiple Deprivation has a significant impact on COVID-19 cases and deaths in all local authorities, although the effect is the strongest in the south of England. Higher proportions of ethnic minorities are associated with higher levels of COVID-19 mortality, with the strongest effect being found in the west of England. There is again a similar pattern in terms of cases, but strongest in the north of the country. Other factors including age and gender are also found to have significant effects on COVID-19 morbidity and mortality, with differential spatial effects across the country. The results provide insights into how national and local policymakers can take account of localized factors to address spatial health inequalities and address future infectious disease pandemics.
由于这些因素会影响感染新冠病毒的几率（就发病率而言）或感染的严重程度（就死亡率而言），多种因素与更高的新冠发病率或死亡率相关。我们使用多尺度地理加权回归来研究英国英格兰地方当局层面与新冠发病率和死亡率相关的因素的空间变化。我们调查了2020年3月至2021年3月期间，即新冠疫苗接种计划推出之前的这段时间。我们考虑了多种因素，包括人口统计学因素（如年龄、性别和种族）、健康因素（如吸烟率、肥胖率和糖尿病率）、社会因素（如多重剥夺指数）以及经济因素（如基尼系数和经济复杂度指数），这些因素此前已被发现会影响新冠发病率和死亡率。多重剥夺指数对所有地方当局的新冠病例和死亡都有显著影响，尽管在英格兰南部影响最为强烈。少数族裔比例较高与新冠死亡率较高相关，在英格兰西部这种影响最为明显。在病例方面也有类似模式，但在该国北部最为强烈。包括年龄和性别在内的其他因素也被发现对新冠发病率和死亡率有显著影响，且在全国范围内存在不同的空间效应。研究结果为国家和地方政策制定者如何考虑局部因素以解决空间健康不平等问题以及应对未来的传染病大流行提供了见解。
