The Frontline War: A Case-control study of risk factors for COVID-19 among health care workers

DOI record: { "DOI": "10.12688/f1000research.109023.1", "ISSN": [ "2046-1402" ], "URL": "http://dx.doi.org/10.12688/f1000research.109023.1", "abstract": "<ns4:p>Purpose:</ns4:p><ns4:p> The global pandemic of COVID-19 has infected several people worldwide. World Health Organization(WHO) has reported that an alarming number of health care workers (HCWs) have been affected and have also succumbed to this disease. Though health infrastructure can be boosted in a short period, the number of HCWs cannot. Hence understanding the risk factors that the HCWs are exposed to and strategically protecting them is of paramount importance.</ns4:p><ns4:p> Methods:</ns4:p><ns4:p> A case-control retrospective study was carried out on 116 HCWs at a tertiary care hospital treating COVID-19 patients in South India. We attempted to investigate and stratify the specific risk factors for COVID-19 transmission among HCWs. Data was collected regarding their exposure to COVID-19 patients, infection control precautions used, possible breaches in the protocol, and details of Hydroxychloroquine (HCQ) prophylaxis.</ns4:p><ns4:p> Results:</ns4:p><ns4:p> The demographics were equally distributed among the cases and controls. Exposure to surgical procedures on suspected/positive COVID patients was also found to affect contracting the COVID-19 illness. HCWs who wore face shields instead of eye goggles along with the use of scrubs and hospital gowns were found to have a lesser incidence of COVID-19 illness.</ns4:p><ns4:p> Conclusion:</ns4:p><ns4:p> This study helped us understand the varied risk factors that health care workers are exposed to while treating COVID-19 patients. It helped us contextualize and strategize our infection control practices to prevent further morbidity and mortality due to COVID-19.</ns4:p>", "assertion": [ { "URL": "https://f1000research.com/articles/11-1298/v1#article-reports", "group": { "label": "Current Referee Status", "name": "current-referee-status" }, "label": "Referee status", "name": "referee-status", "order": 0, "value": "Awaiting Peer Review" }, { "label": "Grant Information", "name": "grant-information", "order": 0, "value": "The author(s) declared that no grants were involved in supporting this work" }, { "label": "Copyright", "name": "copyright-info", "order": 0, "value": "This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited." } ], "author": [ { "ORCID": "http://orcid.org/0000-0002-7026-2474", "affiliation": [], "authenticated-orcid": false, "family": "Sukumar", "given": "Cynthia Amrutha", "sequence": "first" }, { "affiliation": [], "family": "Bolanthakodi", "given": "Nandakrishna", "sequence": "additional" }, { "affiliation": [], "family": "Venkatramanan", "given": "Aarthi", "sequence": "additional" }, { "affiliation": [], "family": "Nagraj", "given": "Ravishankar", "sequence": "additional" }, { "affiliation": [], "family": "Vidyasagar", "given": "Sudha", "sequence": "additional" } ], "container-title": "F1000Research", "container-title-short": "F1000Res", "content-domain": { "crossmark-restriction": false, "domain": [ "f1000research.com" ] }, "created": { "date-parts": [ [ 2022, 11, 14 ] ], "date-time": "2022-11-14T14:30:16Z", "timestamp": 1668436216000 }, "deposited": { "date-parts": [ [ 2022, 11, 14 ] ], "date-time": "2022-11-14T14:30:28Z", "timestamp": 1668436228000 }, "indexed": { "date-parts": [ [ 2022, 11, 15 ] ], "date-time": "2022-11-15T06:05:13Z", "timestamp": 1668492313393 }, "is-referenced-by-count": 0, "issued": { "date-parts": [ [ 2022, 11, 14 ] ] }, "language": "en", "license": [ { "URL": "http://creativecommons.org/licenses/by/4.0/", "content-version": "tdm", "delay-in-days": 0, "start": { "date-parts": [ [ 2022, 11, 14 ] ], "date-time": "2022-11-14T00:00:00Z", "timestamp": 1668384000000 } } ], "link": [ { "URL": "https://f1000research.com/articles/11-1298/v1/xml", "content-type": "application/xml", "content-version": "vor", "intended-application": "text-mining" }, { "URL": "https://f1000research.com/articles/11-1298/v1/pdf", "content-type": "application/pdf", "content-version": "vor", "intended-application": "text-mining" }, { "URL": "https://f1000research.com/articles/11-1298/v1/iparadigms", "content-type": "unspecified", "content-version": "vor", "intended-application": "similarity-checking" } ], "member": "2560", "original-title": [], "page": "1298", "prefix": "10.12688", "published": { "date-parts": [ [ 2022, 11, 14 ] ] }, "published-online": { "date-parts": [ [ 2022, 11, 14 ] ] }, "publisher": "F1000 Research Ltd", "reference": [ { "DOI": "10.1016/S1473-3099(20)30120-1", "article-title": "An interactive web-based dashboard to track COVID-19 in real-time.", "author": "E Dong", "doi-asserted-by": "publisher", "first-page": "533-534", "journal-title": "Lancet Infect. 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