| Literature DB >> 32758438 |
Kasper Iversen1, Henning Bundgaard2, Rasmus B Hasselbalch3, Jonas H Kristensen3, Pernille B Nielsen3, Mia Pries-Heje2, Andreas D Knudsen4, Casper E Christensen5, Kamille Fogh3, Jakob B Norsk3, Ove Andersen6, Thea K Fischer7, Claus Antonio Juul Jensen8, Margit Larsen9, Christian Torp-Pedersen7, Jørgen Rungby10, Sisse B Ditlev11, Ida Hageman12, Rasmus Møgelvang2, Christoffer E Hother9, Mikkel Gybel-Brask9, Erik Sørensen9, Lene Harritshøj9, Fredrik Folke13, Curt Sten14, Thomas Benfield15, Susanne Dam Nielsen16, Henrik Ullum9.
Abstract
BACKGROUND: Health-care workers are thought to be highly exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We aimed to investigate the prevalence of antibodies against SARS-CoV-2 in health-care workers and the proportion of seroconverted health-care workers with previous symptoms of COVID-19.Entities:
Mesh:
Substances:
Year: 2020 PMID: 32758438 PMCID: PMC7398038 DOI: 10.1016/S1473-3099(20)30589-2
Source DB: PubMed Journal: Lancet Infect Dis ISSN: 1473-3099 Impact factor: 25.071
Baseline characteristics
| Age, years | 44·5 (12·5) | 43·3 (13·5) | |
| Sex | |||
| Female | 21 883 (79·2%) | 832 (71·5%) | |
| Male | 5746 (20·8%) | 331 (28·5%) | |
| Body-mass index | 25·06 (4·69) | 24·83 (4·17) | |
| Any symptom of COVID-19 | 14 587 (52·8%) | 908 (78·1%) | |
| Diagnosed COVID-19 | 129 (0·5%) | 231 (19·9%) | |
Data are n (%) or mean (SD).
Frequencies of positive antibody tests stratified according to categories of professions
| Physicians | 4698 | 137 (2·92%) | 112 (2·38%) | 58 (1·23%) | 191 (4·07%) |
| Nurses | 9963 | 283 (2·84%) | 265 (2·66%) | 146 (1·47%) | 402 (4·03%) |
| Assisting nurses | 1786 | 66 (3·70%) | 45 (2·52%) | 28 (1·57%) | 83 (4·65%) |
| Midwives | 501 | 9 (1·80%) | 6 (1·20%) | 4 (0·80%) | 11 (2·20%) |
| Radiographers | 342 | 9 (2·63%) | 9 (2·63%) | 6 (1·75%) | 12 (3·51%) |
| Laboratory personnel | 1292 | 18 (1·39%) | 15 (1·16%) | 8 (0·62%) | 25 (1·93%) |
| Medical students | 688 | 41 (5·96%) | 94 (13·66%) | 32 (4·65%) | 103 (14·97%) |
| Paramedics | 323 | 7 (2·17%) | 12 (3·72%) | 3 (0·93%) | 16 (4·95%) |
| Administrative staff | 2631 | 51 (1·94%) | 47 (1·79%) | 27 (1·03%) | 71 (2·70%) |
| Other | 6568 | 187 (2·79%) | 163 (2·72%) | 101 (1·40%) | 249 (4·11%) |
| All | 28 792 | 808 (2·81%) | 768 (2·67%) | 413 (1·43%) | 1163 (4·04%) |
Data are n or n (%).
Figure 1Seroprevalence according to job assignment compared with blood donors
Purple indicates blood donors serving as a proxy for the general population (n=4672). Blue indicates health-care workers not working on dedicated COVID-19 wards or frontline (n=11 488). Red indicates frontline health-care workers not working on dedicated COVID-19 wards (n=15 983). Green indicates health-care workers working on dedicated COVID-19 wards (n=1321). NS=not significant.
Figure 2Seroprevalence stratified according to specialty for doctors, nurses, and assisting nurses
Figure shows specialties with at least 100 participants.
Frequencies of positive antibody tests stratified according to symptoms of COVID-19
| Any symptom | 908 (5·86%) | 14 587 (94·14%) | <0·0001 |
| Fever | 480 (14·99%) | 2723 (85·01%) | <0·0001 |
| Loss of smell or taste | 377 (32·39%) | 787 (67·61%) | <0·0001 |
| ≥3 symptoms | 727 (7·39%) | 9113 (92·61%) | <0·0001 |
Data are n (%), unless otherwise indicated. p values were calculated using Fisher's exact test, comparing seropositivity with the factors listed.