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预测英格兰和威尔士 COVID-19 医疗需求的空间、社会经济和人口统计学变化。

Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales.

机构信息

Leverhulme Centre for Demographic Science, University of Oxford & Nuffield College, Oxford, UK.

Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark.

出版信息

BMC Med. 2020 Jun 29;18(1):203. doi: 10.1186/s12916-020-01646-2.

Abstract

BACKGROUND

COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in Europe, second in the world only to the USA. Hospitalization and death from COVID-19 have been linked to demographic and socioeconomic variation. Since this varies strongly by location, there is an urgent need to analyse the mismatch between health care demand and supply at the local level. As lockdown measures ease, reinfection may vary by area, necessitating a real-time tool for local and regional authorities to anticipate demand.

METHODS

Combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial County (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales, we calculate the number of individuals at risk of COVID-19 hospitalization. Combining multiple sources, we produce geospatial risk maps on an online dashboard that dynamically illustrate how the pre-crisis health system capacity matches local variations in hospitalization risk related to age, social deprivation, population density and ethnicity, also adjusting for the overall infection rate and hospital capacity.

RESULTS

By providing fine-grained estimates of expected hospitalization, we identify areas that face higher disproportionate health care burdens due to COVID-19, with respect to pre-crisis levels of hospital bed capacity. Including additional risks beyond age-composition of the area such as social deprivation, race/ethnic composition and population density offers a further nuanced identification of areas with disproportionate health care demands.

CONCLUSIONS

Areas face disproportionate risks for COVID-19 hospitalization pressures due to their socioeconomic differences and the demographic composition of their populations. Our flexible online dashboard allows policy-makers and health officials to monitor and evaluate potential health care demand at a granular level as the infection rate and hospital capacity changes throughout the course of this pandemic. This agile knowledge is invaluable to tackle the enormous logistical challenges to re-allocate resources and target susceptible areas for aggressive testing and tracing to mitigate transmission.

摘要

背景

COVID-19 是百年来最严重的公共卫生危机之一。截至 2020 年 5 月中旬,全球已登记死亡近 30 万人,确诊病例超过 400 万。截至 5 月初,英国的死亡人数达到 3 万多,是欧洲记录死亡人数最多的国家,仅次于美国。COVID-19 的住院和死亡与人口统计学和社会经济差异有关。由于这种差异在地理位置上差异很大,因此迫切需要分析当地卫生保健需求与供给之间的不匹配。随着封锁措施的放宽,再次感染的情况可能因地区而异,这就需要地方和地区当局使用实时工具来预测需求。

方法

我们结合英格兰和威尔士的人口普查估计数和来自 ONS 和 NHS 的医院容量数据,使用行政区域、礼仪郡(CC)、临床委托组(CCG)和低级别超级输出区(LSOA)级别的数据,计算出有 COVID-19 住院风险的人数。通过综合多个来源,我们在一个在线仪表板上生成了地理空间风险图,该图可以动态地说明危机前的卫生系统容量与与年龄、社会贫困、人口密度和种族相关的住院风险的当地变化如何匹配,同时还考虑了整体感染率和医院容量。

结果

通过提供对预期住院人数的详细估计,我们确定了由于 COVID-19 而面临更高不成比例的医疗保健负担的地区,与危机前的医院床位容量相比。除了年龄构成之外,还包括社会贫困、种族/族裔构成和人口密度等其他风险,进一步细致地确定了不成比例的医疗保健需求地区。

结论

由于社会经济差异和人口结构,某些地区面临不成比例的 COVID-19 住院压力风险。我们灵活的在线仪表板允许决策者和卫生官员在感染率和医院容量在整个大流行过程中发生变化时,以精细的粒度监测和评估潜在的医疗保健需求。这种敏捷的知识对于应对重新分配资源和针对易感染地区进行积极检测和追踪以减轻传播的巨大后勤挑战非常宝贵。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35ca/7322877/26c0bea4eeea/12916_2020_1646_Fig1_HTML.jpg

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