Dataset Information

Italian Workers at Risk During the COVID-19 Epidemic

ABSTRACT: We analyze the task-content of occupations operating in about 600 sectors of the economy with a focus on the dimensions that expose workers to contagion risks during the COVID-19 epidemic. We do so in the Italian context, leveraging extremely detailed and granular information from ICP, the Italian equivalent of O*Net (the survey that describes the task content of US occupations). We find that several sectors need physical proximity to operate, mainly in services and retail trade. Workers at risk of complications from COVID-19 (mainly males above the age of 50) are concentrated in sectors characterized by little physical proximity or where working from home is feasible. We then study the sectoral lockdowns put in place by the Italian Government in March 2020. We find that governmental restrictions hit the sectors where the risk of contagion in the workplace was more widespread: the effect is stronger for proximity to the public than that with co-workers. The share of workers who have the possibility to work from home is higher in sectors that were not forced to close. The evidence we provide is useful to identify which activities pose larger risks for contagion among workers in the workplace and where to reinforce safety measures.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40797-021-00164-1.

SUBMITTER: Barbieri T

PROVIDER: S-EPMC8298199 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Older people living in nursing homes (NHs) are particularly vulnerable in the ongoing COVID-19 pandemic, due to the high prevalence of chronic diseases and disabilities (e.g., dementia). The phenomenon of adverse events (AEs), intended as any harm or injury resulting from medical care or to the failure to provide care, has not yet been investigated in NHs during the pandemic. We performed a national survey on 3,292 NHs, either public or providing services both privately and within the national health system, out of the 3,417 NHs covering the whole Italian territory. An online questionnaire was addressed to the directors of each facility between March 24 and April 27, 2020. The list of NHs was provided by the Dementia Observatory, an online map of Italian services for people with dementia, which was one of the objectives of the implementation of the Italian National Dementia Plan. About 26% of residents in the Italian NHs for older people listed within the Dementia Observatory site had dementia. The objective of our study was to report the frequency of AEs that occurred during the months when SARS-CoV-2 spreading rate was at its highest in the Italian NHs and to identify which conditions and attributes were most associated with the occurrence of AEs by means of multivariate regression logistic analysis. Data are referred to 1,356 NHs that participated in the survey. The overall response rate was 41.2% over a time-period of six weeks (from March 24 to May 5). About one third of the facilities (444 out of 1,334) (33.3%) reported at least 1 adverse event, with a total of 2,000 events. Among the included NHs, having a bed capacity higher than the median of 60 beds (OR=1.57, CI95% 1.17-2.09; p=0.002), an observed increased in the use of psychiatric drugs (OR=1.80, CI95% 1.05-3.07; p=0.032), adopting physical restraint measures (OR=1.97, CI95% 1.47-2.64; p<0.001), residents hospitalized due to flu-like symptoms (OR =1.73, CI95% 1.28-2.32; p<0.001), and being located in specific geographic areas (OR=3.59, CI95% 1.81-7.08; OR = 2.90, CI95% 1.45-5.81 and OR = 4.02, CI05% 2.01-8.04 for, respectively, North-West, North-East and Centre vs South, p<0.001) were all factors positively associated to the occurrence of adverse events in the facility. Future recommendations for the management and care of residents in NHs during the COVID-19 pandemic should include specific statements for the most vulnerable populations, such as people with dementia.

Dataset Information

Italian Workers at Risk During the COVID-19 Epidemic

Supplementary Information

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets