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10.3390/ijerph19063628

http://scihub22266oqcxt.onion/10.3390/ijerph19063628
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35329313!8955756!35329313
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suck abstract from ncbi


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pmid35329313      Int+J+Environ+Res+Public+Health 2022 ; 19 (6): ä
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  • Non-Pharmacological Preventive Measures Had an Impact on COVID-19 in Healthcare Workers before the Vaccination Effect: A Cohort Study #MMPMID35329313
  • Utzet M; Benavides FG; Villar R; Buron A; Sala M; Lopez LE; Gomar P; Castells X; Diaz P; Ramada JM; Serra C
  • Int J Environ Res Public Health 2022[Mar]; 19 (6): ä PMID35329313show ga
  • Healthcare workers have been and still are at the forefront of COVID-19 patient care. Their infection had direct implications and caused important challenges for healthcare performance. The aim of this study is to assess the impact of non-pharmacological preventive measures against COVID-19 among healthcare workers. This study is based on a dynamic cohort of healthcare workers (n = 5543) who had been hired by a Spanish hospital for at least one week during 2020. Negative binomial regression models were used to estimate the incidence rate and the rate ratio (RR) between the two waves (defined from 15 March to 21 June and from 22 June to 31 December), considering natural immunity during the first wave and contextual variables. All models were stratified by socio-occupational variables. The average COVID-19 incidence rate per 1000 worker-days showed a significant reduction between the two waves, dropping from 0.82 (CI95%: 0.73-0.91) to 0.39 (0.35-0.44). The adjusted RR was 0.54 (0.48-0.87) when natural immunity was acquired during the first wave, and contextual variables were considered. The significant reduction of the COVID-19 incidence rate could be explained mainly by improvement in the non-pharmacological preventive interventions. It is needed to identify which measures were more effective. Young workers and those with a replacement contract were identified as vulnerable groups that need greater preventive efforts. Future preparedness plans would benefit from these results.
  • |*COVID-19/epidemiology/prevention & control[MESH]
  • |Cohort Studies[MESH]
  • |Health Personnel[MESH]
  • |Humans[MESH]
  • |Models, Statistical[MESH]


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  • suck abstract from ncbi

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