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2020 年法国第一波大流行期间因 COVID-19 导致的病假。

Sick leave due to COVID-19 during the first pandemic wave in France, 2020.

机构信息

Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris 75003, France

Epidemiology & Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris-Cité, Paris 75015, France.

出版信息

Occup Environ Med. 2023 May;80(5):268-272. doi: 10.1136/oemed-2022-108451. Epub 2023 Mar 13.

Abstract

OBJECTIVES

To quantify the burden of COVID-19-related sick leave during the first pandemic wave in France, accounting for sick leaves due to symptomatic COVID-19 ('symptomatic sick leaves') and those due to close contact with COVID-19 cases ('contact sick leaves').

METHODS

We combined data from a national demographic database, an occupational health survey, a social behaviour survey and a dynamic SARS-CoV-2 transmission model. Sick leave incidence from 1 March 2020 to 31 May 2020 was estimated by summing daily probabilities of symptomatic and contact sick leaves, stratified by age and administrative region.

RESULTS

There were an estimated 1.70M COVID-19-related sick leaves among France's 40M working-age adults during the first pandemic wave, including 0.42M due to COVID-19 symptoms and 1.28M due to COVID-19 contacts. There was great geographical variation, with peak daily sick leave incidence ranging from 230 in Corse (Corsica) to 33 000 in Île-de-France (the greater Paris region), and greatest overall burden in regions of north-eastern France. Regional sick leave burden was generally proportional to local COVID-19 prevalence, but age-adjusted employment rates and contact behaviours also contributed. For instance, 37% of symptomatic infections occurred in Île-de-France, but 45% of sick leaves. Middle-aged workers bore disproportionately high sick leave burden, owing predominantly to greater incidence of contact sick leaves.

CONCLUSIONS

France was heavily impacted by sick leave during the first pandemic wave, with COVID-19 contacts accounting for approximately three-quarters of COVID-19-related sick leaves. In the absence of representative sick leave registry data, local demography, employment patterns, epidemiological trends and contact behaviours can be synthesised to quantify sick leave burden and, in turn, predict economic consequences of infectious disease epidemics.

摘要

目的

量化法国第一波大流行期间与 COVID-19 相关的病假负担,包括因有症状 COVID-19(“有症状病假”)和因与 COVID-19 病例密切接触(“接触病假”)而请的病假。

方法

我们结合了国家人口数据库、职业健康调查、社会行为调查和 SARS-CoV-2 传播动态模型的数据。通过汇总每日有症状和接触病假的概率来估计 2020 年 3 月 1 日至 5 月 31 日期间的病假发生率,按年龄和行政区域分层。

结果

在第一波大流行期间,法国 4000 万劳动年龄成年人中约有 170 万与 COVID-19 相关的病假,其中 42 万是由于 COVID-19 症状,128 万是由于 COVID-19 接触。地理差异很大,波峰时每日病假发病率从科西嘉岛(科西嘉)的 230 例到法兰西岛(大巴黎地区)的 33000 例不等,东北部地区的总体负担最大。区域病假负担通常与当地 COVID-19 的流行程度成正比,但也与调整后的就业率和接触行为有关。例如,有 37%的有症状感染发生在法兰西岛,但病假却有 45%。中年工人承担的病假负担不成比例地高,这主要是由于接触病假的发病率较高。

结论

法国在第一波大流行期间病假负担沉重,COVID-19 接触者约占 COVID-19 相关病假的四分之三。在没有代表性的病假登记数据的情况下,可以综合当地人口统计学、就业模式、流行病学趋势和接触行为来量化病假负担,并相应地预测传染病流行对经济的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d7/10176331/b3ea3fbc62aa/oemed-2022-108451f01.jpg

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