| Literature DB >> 36197236 |
Rujipas Sirijatuphat1, Amorn Leelarasamee1,2, Navin Horthongkham3.
Abstract
Globally, healthcare workers (HCWs) have a high risk of SARS-CoV-2 infection, but less is known about healthcare workers in Thailand. We estimated the prevalence and risk factors for COVID-19 among HCWs in Bangkok, Thailand. A retrospective cohort study was conducted at a large tertiary care academic hospital in Thailand from May 2020 to May 2021. HCWs that presented with fever and/or acute respiratory tract symptoms who tested with RT-PCR were identified, and their clinical data were collected. There were 1432 HCWs with fever and/or acute respiratory tract symptoms during May 2020 and May 2021. A total of 167 patients were front-line HCWs and 1265 were non-front-line HCWs. Sixty HCWs (4.2%) developed COVID-19; 2 were front-line and 58 were non-front-line HCWs. The prevalence of COVID-19 in front-line HCWs was 1.7% (2/167), and 4.6% (58/1265) in non-front-line HCWs (P = .04). In addition, non-front-line HCWs, non-medical staffs, history of contact with a confirmed COVID-19 case at home/family, unvaccinated status, fair compliance to personal protective equipment (PPE) standard, and initial presentation with pneumonia were significantly more common in HCWs with COVID-19 than those without COVID-19 (P < .05). Front-line HCWs, history of contact with a confirmed COVID-19 case at the clinical care areas in the hospital, vaccinated status, good compliance to PPE standards, and initial presentation with upper respiratory infection were significantly more common in HCWs without COVID-19 than those with COVID-19 (P < .05). Multivariate analysis revealed history of exposure with confirmed COVID-19 case at home or in family, unvaccinated status, non-frontline-HCWs, non-medical staffs, and fair compliance to PPE standard to be independent factors associated with COVID-19 in HCWs. COVID-19 was more common in non-front-line HCWs at this tertiary hospital. Thai guidelines on infection prevention and control for COVID-19 seem to be effective in preventing SARS-CoV-2 transmission. Therefore, the adherence to these recommendations should be encouraged.Entities:
Mesh:
Year: 2022 PMID: 36197236 PMCID: PMC9508950 DOI: 10.1097/MD.0000000000030837
Source DB: PubMed Journal: Medicine (Baltimore) ISSN: 0025-7974 Impact factor: 1.817
Clinical characteristics of HCWs with or without COVID-19.
| COVID-19 (n = 60) | No COVID-19 (n = 1372) | ||
|---|---|---|---|
| Age (mean ± SD), yr | 35.0 ± 8.4 | 36.2 ± 6.9 | .192 |
| Male | 24 (40.0) | 570 (41.5) | .812 |
| Presence of co-morbidity | 12 (20.0) | 245 (17.9) | .672 |
| Types of underlying co-morbidities | |||
| Diabetes mellitus | 2 (16.7) | 48 (19.6) | .803 |
| Hypertension | 5 (41.7) | 111 (45.3) | .805 |
| Chronic kidney disease | 1 (8.3) | 11 (4.5) | .534 |
| Chronic liver disease | 1 (8.3) | 9 (3.7) | .415 |
| Lung disease | 2 (16.7) | 27 (11.0) | .546 |
| Heart disease | 1 (8.3) | 10 (4.1) | .477 |
| Neurological disease | 0 (0.0) | 0 (0.0) | 1.000 |
| Malignancy | 0 (0.0) | 8 (3.3) | .525 |
| Immunocompromised conditions | 0 (0.0) | 4 (1.6) | .656 |
| Obesity (BMI ≥30 kg/m2) | 3 (25.0) | 41 (16.7) | .458 |
| Occupations | |||
| Physicians | 8 (13.3) | 270 (19.7) | .224 |
| Nurses/nurse assistants | 20 (33.3) | 565 (41.2) | .226 |
| Other medical staffs | 8 (13.3) | 198 (14.4) | .812 |
| Non-medical staffs | 24 (40.0) | 339 (24.7) | .008 |
| Types of HCWs | |||
| Front-line HCWs | 2 (3.3) | 165 (12.0) | .040 |
| Non-front-line HCWs | 58 (96.7) | 1207 (88.0) | .040 |
| Exposure areas of contact with confirmed COVID-19 case | |||
| Home/family | 25 (41.7) | 384 (28.0) | .022 |
| Workplace | 18 (30.0) | 331 (24.1) | .299 |
| Crowed public area (pub/bar/market) | 15 (25.0) | 302 (22.0) | .585 |
| Clinical care area (ED/OPD/Ward) | 2 (3.3) | 280 (20.4) | .001 |
| No history of contact with confirmed COVID-19 case | 0 (0.0) | 75 (5.5) | .062 |
| Previous SARS-CoV-2 infection | 0 (0.0) | 5 (0.4) | .639 |
| Vaccination status | |||
| Vaccinated status | 5 (8.3) | 342 (24.9) | .003 |
| Unvaccinated status | 55 (91.7) | 1030 (75.1) | .003 |
| Self-reported compliance to PPE standard | |||
| Good compliance | 35 (58.3) | 1001 (73.0) | .013 |
| Fair compliance | 25 (41.7) | 371 (27.0) | .013 |
| Initial diagnosis at presentation | |||
| URI | 55 (91.7) | 1354 (98.7) | <.001 |
| Acute bronchitis | 1 (1.7) | 10 (0.7) | .415 |
| Pneumonia | 4 (6.7) | 8 (0.6) | <.001 |
BMI = body mass index, ED = emergency department, HCWs = healthcare workers, OPD = outpatient departments, PPE = personal protective equipment, SD = standard deviation, URI = upper respiratory tract infection.
Clinical characteristics compared between the front-line and non-front-line HCWs.
| Front-line HCWs (n = 167) | Non-front-line HCWs (n = 1265) | ||
|---|---|---|---|
| Age (mean ± SD), yr | 33.3 ± 9.5 | 37.8 ± 8.8 | <.001 |
| Male | 71 (42.5) | 523 (41.3) | .773 |
| Presence of co-morbidity | 15 (9.0) | 242 (19.1) | .001 |
| Types of underlying co-morbidities | |||
| Diabetes mellitus | 3 (20.0) | 47 (19.4) | .956 |
| Hypertension | 7 (46.7) | 109 (45.0) | .902 |
| Chronic kidney disease | 0 (0.0) | 12 (5.0) | .377 |
| Chronic liver disease | 0 (0.0) | 10 (4.1) | .422 |
| Lung disease | 2 (13.3) | 27 (11.2) | .796 |
| Heart disease | 0 (0.0) | 11 (4.5) | .399 |
| Neurological disease | 0 (0.0) | 0 (0.0) | 1.000 |
| Malignancy | 0 (0.0) | 8 (3.3) | .474 |
| Immunocompromised conditions | 0 (0.0) | 4 (1.7) | .616 |
| Obesity (BMI ≥30 kg/m2) | 3 (20.0) | 41 (16.9) | .760 |
| Occupations | |||
| Physicians | 43 (25.7) | 235 (18.6) | .028 |
| Nurses/nurse assistants | 102 (61.1) | 483 (38.2) | <.001 |
| Other medical staffs | 22 (13.2) | 184 (14.5) | .635 |
| Non-medical staffs | 0 (0.0) | 363 (28.7) | <.001 |
| Exposure areas of contact with confirmed COVID-19 case | |||
| Home/family | 15 (9.0) | 394 (31.1) | <.001 |
| Workplace | 45 (26.9) | 304 (24.0) | .423 |
| Crowed public area (pub/bar/market) | 39 (23.4) | 278 (22.0) | .685 |
| Clinical care area (ED/OPD/Ward) | 58 (34.7) | 224 (20.4) | <.001 |
| No history of contact with confirmed COVID-19 case | 10 (6.0) | 65 (5.1) | .643 |
| Previous SARS-CoV-2 infection | 0 (0.0) | 5 (0.4) | .415 |
| Vaccination status | |||
| Vaccinated status | 151 (90.4) | 196 (15.5) | <.001 |
| Unvaccinated status | 16 (9.6) | 1069 (84.5) | <.001 |
| Self-reported compliance to PPE standard | |||
| Good compliance | 167 (100.0) | 869 (68.7) | <.001 |
| Fair compliance | 0 (0.0) | 396 (31.3) | <.001 |
| Initial diagnosis at presentation | |||
| URI | 165 (98.8) | 1244 (98.3) | .655 |
| Acute bronchitis | 1 (0.6) | 10 (0.8) | .789 |
| Pneumonia | 1 (0.6) | 11 (0.9) | .718 |
| Confirmed COVID-19 diagnosis | 2 (1.2) | 58 (4.6) | .040 |
| Severity of COVID-19 | |||
| URI | 2 (100.0) | 53 (98.3) | .664 |
| Acute bronchitis | 0 (0.0) | 1 (1.7) | .861 |
| Pneumonia | 0 (0.0) | 4 (6.9) | .701 |
| Outcome of COVID-19 | |||
| Cure | 2 (100.0) | 58 (100.0) | 1.000 |
BMI = body mass index, ED = emergency department, HCWs = healthcare workers, OPD = outpatient departments, PPE = personal protective equipment, SD = standard deviation, URI = upper respiratory tract infection.
Rate of COVID-19 in HCWs across different countries.[
| Country (numbers of case) | Rate of COVID-19 in HCWs |
|---|---|
| United States (n = 1958) | 14.8% |
| Brazil (n = 775) | 14.7% |
| United Kingdom (n = 266) | 18.0% |
| France (n = 319) | 21.0% |
| Portugal (n = 8037) | 2.6% |
| Saudi Arabia (n = 16,317) | 9.8% |
| India (n = 3711) | 11.0% |
| China (n = 4614) | 0.2% |
| Philippines (n = 324) | 2.5% |
| Malaysia (n = 1174) | 1.4% |
| Indonesia (n = 1201) | 7.9% |
| Thailand (this study, n = 1432) | 4.2% |
HCWs = healthcare workers.