Risk Stratification tool for Healthcare workers during the CoViD-19 Pandemic; using published data on demographics, co-morbid disease and clinical domain in order to assign biological risk
Healthcare workers have a greater exposure to individuals with confirmed SARS-novel coronavirus 2, and thus a higher probability of contracting coronavirus disease (CoViD)-19, than the general population. Employers have a duty of care to minimise the risk for their employees. Several bodies including the Faculty of Occupational Medicine, NHS Employers, and Public Health England have published a requirement to perform risk assessments for all health care workers, however, with the absence of an objective risk stratification tool, comparing assessments between individuals is difficult if not impossible. Using published data, we explored the predictive role of basic demographics such as age, sex, ethnicity and comorbidities in order to establish an objective risk stratification tool that could help risk allocate duties to health care workers. We developed an objective risk stratification tool using a Caucasian female <50years of age with no comorbidities as a reference. Each point allocated to risk factors was associated with an approximate doubling in risk. This tool was then validated against the primary care-based analysis. This tool provides objective support for employers when determining which healthcare workers should be allocated to high-risk vs. lower risk patient facing clinical duties or to remote supportive roles.
- Downloaded 8,853 times
- Download rankings, all-time:
- Site-wide: 1,209
- In health policy: 10
- Year to date:
- Site-wide: 5,452
- Since beginning of last month:
- Site-wide: 5,524
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!