key: cord-0978222-613y1lyy
authors: Al-Maani, Amal; Al Wahaibi, Adil; Al-Sooti, Jabir; Al Abri, Bader; Al Shukri, Intisar; AlRisi, Elham; AL Abri, Laila; AlDaghari, Khalid; AL Subhi, Mahmood; AlMaqbali, Salima; AlBurtamani, Salim; AlAbri, Asma; AL Salami, Ahmed; Al-Beloushi, Iman; Al-Zadjali, Najla; Alqayoudhi, Abdullah; Al-Kindi, Hanan; Al Shaqsi, Khalifa; Al-Jardani, Amina; Al-Abri, Seif
title: The role of supporting services in driving SARS-CoV-2 transmission within healthcare settings: a multicenter seroprevalence study
date: 2021-04-27
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2021.04.071
sha: 88f0227b99c72b46d5c36379ca2ba2e9eac5e688
doc_id: 978222
cord_uid: 613y1lyy

Objective Determining the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in health care workers (HCWs) based on risk of exposure to COVID-19 patients. Methods SARS-CoV-2 seroprevalence cross-sectional study in risk-stratified HCWs randomly selected from 3 main district hospitals in Oman. Results 1,078 HCWs included with an overall SARS-CoV-2 seroprevalence of 21%. The seropositivity in low, variable, and high risk groups were 29%, 18%, and 17%, respectively (P-value <0.001). The study found higher positivity in males [crude odds ratio (COR) 1.71, 95% confidence interval (CI) 1.28–2.3], and workers residing in high prevalence areas (COR 2.09, 95% CI 1.42–3.07). Compared to doctors, workers from supporting services, administration and nurses were more likely to have positive SARS-CoV-2 antibodies (COR 9.81, 95% CI 5.26–18.27; 2.37, 95% CI 1.23–4.58; 2.08 95% CI 1.14–3.81). The overall rate of previously undetected infection was 12% with higher values in low-risk HCWs. High district prevalence is a driving factor for seropositivity in the low-risk group [adjusted odds ratio (AOR) 2.36 (95% CI 1.0–5.59)]. Conclusion The low risk supporting services workers can drive SARS-CoV-2 transmission in hospitals. More attention and innovation within this opportunity will enhance the safety of health care during epidemics/pandemics.

The emergence of SARS-CoV-2 causing COVID-19 in December 2019 has rapidly evolved into a pandemic with cumulative numbers of more than 83 million confirmed cases and 1.8 million deaths globally according to WHO (2021a) . During the lengthy course of this pandemic, The Lancet reported that workers within health care facilities have been working at maximum capacity for many hours and shifts and in some settings, with limited protection (2020). Being a frontline health care worker was found to be one of the risk factors for acquiring COVID-19 as shown in many serological studies, such as a 2021 study by Galanis et al. However, exposure in the community in the early phase of local spread has also shown to be the cause of COVID-19 in a substantial proportion of HCWs even before admitting cases to their hospital (Kluytmans-van den Bergh et al., 2020) . The incidence of SARS-CoV-2 infection in HCWs varied across different studies depending on the disease epidemiology, target health care professions, and diagnostic tools. Overall, the studies of SARS-CoV-2 in HCWs using polymerase chain reaction (PCR) showed infection incidence at the range of 0.4% to 49.6%, and serology positivity at the range of 1.6% to 31.6% (WHO, 2020a) .

Oman is located on the south-east coast in the Middle East and has a population of about 4.6 million (Government of Oman, 2021). In each district (or governorate) of Oman, is a primary Ministry of Health hospital which is used as a referral center for all the health care institutions within the governorate including the private sector. Each of the referral hospitals in all governorates are set up to be COVID-19 centers for admitting and managing moderate to severe cases. Aggressive measures aimed at protecting HCWs have been implemented including administrative, engineering, and providing personal protection as per the national guideline J o u r n a l P r e -p r o o f (Ministry of Health, Oman, 2020) . The total number of positive reported cases nationally up to the end of December 2020 was 128,867 with 1,499 deaths (WHO, 2021b) .

The nature and durability of the humoral immune response to SARS-COV-2 infection and clinical utility of serological investigation are still debatable but it has been a great tool for assessing the disease spread in the community and in health care settings (Deeks et al., 2020; Tripathi et al., 2020; WHO, 2020b) . This point prevalence study of SARS-CoV-2 antibodies was conducted before the start of the vaccination program for COVID-19 to determine the disease epidemiology and risk factors within healthcare settings stratified based on exposure risks.

Study setting:

This study was conducted in 3 district COVID-19 management referral hospitals, Nizwa, Sohar, and Rustaq. These are referral secondary care facilities for Al Dakhilia, North Batinah, and South Batinah governorates, respectively. Each hospital covers the population of the governorate where it is found and almost all HCWs reside in the same governorate where they work. The 3 centers had a similar structure and level of care with inpatient bed capacity ranging from 300 to 400 beds. The location of the hospitals and the served population is shown in Figure 1 . The national SARS-CoV-2 serosurvey phase 2 during first 2 weeks of September 2020 showed community prevalence of 18%, 13%, and 9% for South Batinah, North Batinah, and Al Dakhilia governorates, respectively (Manuscript in preparation).

Each of the 3 hospitals started early to prepare for a pandemic following the national preparedness plan and infection control guideline for SARS-CoV-2 (Ministry of Health, Oman, 2020) . There were specific pathways for receiving, investigating and management of suspected/confirmed patients with COVID-19 from community centers and in the emergency department. For the inpatient care, each hospital created a COVID-19 ward and intensive care area ensuring proper isolation precautions implemented. Every entrance to the hospital was provided with active symptomatic screening and temperature check. The hospitals started receiving COVID-19 patients in March 2020 with total inpatients by end of August 2020 reaching 751, 350, and 310 for Sohar hospital, Rustaq hospital, and Nizwa hospital, respectively.

A cross-sectional seroprevalence study was conducted in the period from 14 to 28 of September involving workers in the health care setting from the 3 defined centers. The detailed process of randomization and sample selection from each hospital and for each risk category is provided as supplementary material.

We calculated sample size after grouping all the workers within the 3 hospitals into 3 risk categories based on the potential of being exposed to a suspected or confirmed COVID-19 J o u r n a l P r e -p r o o f patient within the hospital:

i. High exposure risk: HCWs from COVID-19 wards, intensive care units, emergency and internal medicine departments, regardless of their profession category.

ii. Variable exposure risk: HCWs from surgical wards, pediatric/obstetric departments and in laboratory/pharmacy. Workers in this category are not directly involved in the care of suspected or confirmed cases of COVID-19, but may if a patient was unrecognized initially.

iii. Low exposure risk: HCWs working in administration, medical records, engineering, finance, kitchen, laundry, IT and security staff who are not directly involved in the clinical care of suspected or confirmed cases of COVID-19 or other clinical areas.

Each hospital sent its enrolment data sheet classified as indicted into the 3 risk categories to the central study team 2 weeks prior to collecting serology samples. A total number of 3,665 HCWs were included in a list as populations from all participating hospitals. We assigned each HCW with a unique code and risk group label, hospital and professional categories.

The sample size for the 3 hospitals was calculated based on 95% confidence level and 5% margin of error samples and for the estimated prevalence of 1-2% for each risk category. Based on that, the total sample was 400 HCWs per category. A multivariable stratified random An illustration of sampling and enrolment process for the study is provided as supplementary material.

The randomized list of each hospital was sent to the study focal point for participation consent, questionnaire administration and blood testing. Each hospitals' team ensured that the enrolled staff still operated within the allocated risk categories. Exclusion criteria included suspected or had symptoms consistent with COVID-19 infection at the time of the survey and those who did not consent to filling the questionnaire or giving a blood sample for serology study. HCWs who were on leave or covering work in other facilities were excluded. An effort was made during the 2 weeks of the study to replace some of the unavailable or unconsented staff ensuring that they were from the same category and profession.

The questionnaire:

Each enrolled HCW filled a questionnaire which included demographic information, risk assessment, symptoms, and disease history section. Demography included age, sex, nationality and profession. The exposure risk assessment included personal protective equipment (PPE) use, infection prevention and control (IPC) training and contact with the positive case. Clinical data included symptoms, symptom onset, COVID-19 history and presence of any pre-existing comorbidities. The questionnaire was adapted with modification from the World Health Organization (WHO, 2020c) assessment of risk factors for COVID-19 in health workers. The web link to the questionnaire was provided to the enrolled HCWs after consenting for the study to fill in the information and then proceed to take an antibody test when the study team J o u r n a l P r e -p r o o f confirmed submission of the completed questionnaire. The questionnaire is provided as supplementary material.

A serum sample (5-10 ml) using a gel separator tube was collected by the hospital study focal point from all candidates who consented and filled out the questionnaire. At the regional hospitals, samples were centrifuged at 1,000-3,000 RPM for 10 minutes. The separated sample was then transferred to a 5 ml plain tube without a conservative. Samples were transported to the Central Public Health Laboratory and tested using Diasorin Liaison® XL (DiaSorin, Saluggia, Italy) SARS-CoV-2 S1/S2 immunoglobulin (IgG) kit. It is a fully automated serology test that uses chemiluminescence immunoassay technology for the quantitative determination of anti-S1 and anti-S2 specific IgG antibodies to SARS-CoV-2. A sample is considered negative if the IgG is <12 AU/ml. IgG antibodies level range of >12 and <15 AU/ml is equivocal while ≥15 AU/Ml is taken as positive.

The results were uploaded into the hospitals' electronic system for each participant with their hospital ID number after authorization by a virologist in the Central Public Health Laboratory and a laboratory line list with results were sent to the central study team for analysis. For study analysis, results were either positive or negative. The equivocal results were considered negative in the analysis.

Data analyses:

Baseline characteristics were described as percentages from the total. Community prevalence of SARS-CoV-2 to the wilayat (county) level were extracted from the national serosurvey J o u r n a l P r e -p r o o f (manuscript in preparation), the wilayat of residence was classified as having low or high prevalence of SARS-CoV-2 according to the mean wilayat level in the entire data (calculated to be 11.4). Univariate analysis was performed using logistic regression to investigate the relationship between the positivity of serology (response variable) with different demographic and questionnaire responses (explanatory variables). The difference in the presence of recognized infections among HCWs were tabulated and investigated using chi-square analysis.

Recognized infection was defined as an answer of "yes" in the history of an earlier confirmed infection. To highlight the drivers of positive serology within each risk category, a multivariate logistic regression analysis was performed for each risk category using positive serology as a response variable and other studied factors as explanatory variables. All statistical analysis was performed using R software version 4.02 (The R Project, https://cran.r-project.org/).

Out of 1,200, 90% (1,078) targeted HCWs from the 3 enrolled hospitals were included in this study. Based on the risk of exposure classification, of the 1,078 subjects, there were 345 (32%) workers classified as high risk, 373 (35%) as variable risk and 360 (33%) as low risk. Of the participating HCWs, 55% were female, 49% were in the age category of 30-39 years, and the majority were Omani nationals (68%). The distribution, based on hospital and professional categories, is shown in Table 1 . The majority of the HCWs (82%) were living in their family's house while the remaining were living on hospital campus or in private shared accommodation.

Looking into community prevalence of the HCW living areas; 83% were from low prevalence communities (mean=11.4).

J o u r n a l P r e -p r o o f Self-reporting of recent IPC training was provided by 190 (18%). Of the enrolled cohort, 139 (13%) reported that they had a confirmed SARS-CoV-2 infection previously.

Overall, 229 of 1,078 (21%) HCWs tested positive for IgG antibodies against SARS-CoV-2. In the high risk exposure category, 59/345 (17%) tested positive for IgG antibodies against SARS-CoV-2, 66/373 (18%) in the variable risk, while 104/360 (29%) tested positive in the low-risk.

The difference in the serology positivity between the risk categories was statistically significant (P-value <0.001) with 0.51 COR (95% CI; 0.35-0.73) for high risk and 0.53 COR (95% CI; 0.37-0.75) for the variable risk category compared to the low risk category.

The COR (Table 1) showed significantly higher seropositivity in male HCWs (COR 1.71, 95% CI 1.28-2.3), and when the worker resides in a high prevalence area (OR: 2.09, 95% CI 1.42-3.07). Among the professional categories the workers from supporting services, administration and the nurses were significantly more likely to have positive SARS-CoV-2 antibodies compared to doctors with COR; 9.81 (95% CI5.26-18.27), 2.37 (95% CI 1.23-4.58), and 2.08 (95% CI 1.14-3.81), respectively. Among the seropositive HCWs; 39% were not able to recall being symptomatic in the 3 months period before the sample was collected. However, the memory of having fever, myalgia, and/or cough were significantly associated with higher antibodies positivity rate with COR of 7.62 (95% CI 4.99-11.62), 2.3 (95% CI 1.68-3.15), and 1.84 (95% CI 1.31-2.58) respectively. On other hand, lower seropositivity was noted in workers living with family (OR 0.42, 95% CI 0.3-0.6). (Table 1 ). The rate of previously undetected SARS-CoV-2 infection was 15/59 (25%), 36/66 (55%), 60/104 (58%) for high, variable, and low-risk groups, respectively, P-value (<0.001), Table 2 .

The adjusted odds ratios are shown in Figure 2 . Rustaq and Sohar hospitals showed higher seropositivity compared to Nizwa hospital only in the high and low-risk groups. The high district prevalence was a statistically significant driving factor for the seropositivity in the low-risk group [AOR 2.36 (95% CI 1.0-5.59)] compared to the other groups. Living with family is protective in the variable risk group [AOR: 0.31 (95% CI 0.11-0.88)], while it shows a tendency to drive the seropositivity in the high risk group, though it is not statistically significant, [AOR 6.43 (95% CI 0.94-68.56)].

In this prospective cohort of 1,078 HCWs from 3 different districts hospitals in Oman, we had a 21% overall SARS-CoV-2 seroprevalence by the end of September 2020 with interestingly significantly higher (29%) prevalence among the group of workers with a low exposure risk. The odds of having SARS-CoV-2 antibodies was significantly lower for both the workers from high risk (e.g., staff working in COVID-19 intensive care units and wards, and emergency departments) and variable exposure risk (e.g., staff working in pediatric wards, obstetrics and surgical units). This finding is contrary to what was reported in earlier months of the pandemic where seroprevalence was higher among HCWs working in COVID-19 units especially in areas where there has been inadequate infection control measure and interrupted or shortage of PPE supply (Grant et al., 2021; Iversen et al., 2020; Rudberg et al., 2020) . Many of the COVID-19 J o u r n a l P r e -p r o o f units later in the pandemic were more prepared and adherent to IPC measures including the use of PPE among HCWs looking after suspected or confirmed COVID-19 patients in a high risk area.

As community transmission increases, the risk of SARS-CoV-2 infection for HCWs outside health care settings becomes similar or even higher through the household, friends, or other unmitigated transmission encounters (Belingheri et al., 2020; Lui et al., 2020; Muhi et al., 2020) .

At later stages of the pandemic, the healthcare cluster is likely to be due to a lapse in early case detection in a worker or a patient especially with COVID-19 because, as noted by Galanis (2020), they may have mild or atypical symptoms and there could be pre-symptomatic transmission. Similar to our findings, the seropositivity was found in the Grant et.al. study to be lower among intensive care unit HCWs because of enhanced PPE, closed-circuit ventilation of intubated patients and the admission of COVID-19 patients beyond day 10 when the viral shedding is less (Grant et al., 2021; Bullard et al., 2020; Zhou et al., 2020) . Throughout the pandemic, the health care setting remains a high risk area and the overall risk of infection in HCWs is always higher than the background population by combination of community and health care sources.

Many studies have reported infection rates among HCWs utilizing SARS-CoV-2 antibody detection (Moscola et al., 2020; Paderno et al., 2020; Steensels et al., 2020; . It is not surprising the wide range of variation in seroprevalence studies whether in community or healthcare settings due to several reasons like the disease epidemiology, the included population, the type of antibody tests used, design and quality of the study, and the J o u r n a l P r e -p r o o f different timing to the pandemic. A recent meta-analysis study found that overall, 8.7% (95% CI 6.7-10.9%) of HCWs have SARS-CoV-2 antibodies with higher seroprevalence in studies from North America (12.7%) compared to those from Europe (8.5%), Africa (8.2) and Asia (4%) (Galanis et al., 2021) . The prevalence had also been highly variable across different centers in the United States from 23 March to 12 May, 2020, ranging from 1%-6.9% (Havers et al., 2020) .

Previous studies in HCWs were mixed with significant heterogeneity even when only frontline (high risk) HCWs were included, but it mostly correlated with community rates (Self et al., 2020) . The high SARS-CoV-2 prevalence in our study may be explained by the inclusion of low risk workers, use of serology for diagnosis and because the study was done 6 months after the epidemic began nationally when disease spread was more broad than it was earlier.

The heterogeneity of studies was also reflected in the risk of infection based on profession or job title. While some studies showed no difference in the infection rate by profession or job (Steensels D et al., 2020; Vahidy FS et al., 2020) . Others have reported high rates of infection or antibody positivity among nurses compared to doctors (Al Maskari et al., 2021; Barrett ES et al., 2020) . Our finding showed the risk was significantly lower in doctors compared to nurses and workers from other professional categories which may be due to their awareness about risk or low level of contact and time of contact with patients compared to nurses, for example. In some studies, however, clinicians had higher infection rates and lower status was noticed in support roles, such as janitorial staff (Eyre et al., 2020; Lombardi et al., 2020) .

A study by Korth et al. evaluating IgG antibodies to SARS-CoV-2 among HCWs in Germany found the overall rate of unrecognized infection to be 1.6% (2020) . A recent serology study from J o u r n a l P r e -p r o o f the UK by Shields et al. (2020) found a 24.4% seroprevalence in HCWs which is a much higher cumulative infection rate than determined in earlier studies using molecular testing. Comparing our serology study results to previously confirmed COVID-19 cases showed a 12% overall rate of unrecognized infection with the majority of them in the low-risk worker category despite the unified accessibility for testing, quarantine and isolation procedures. This undetectable rate by molecular testing can be explained by existing data demonstrating the relative insensitivity of nasopharyngeal swabs in determining viral carriage (Hains et al., 2020; Wang et al., 2020) .

The difference in undetectable infection rates within our study risk categories may also reflect insight to the infection risk by the high and variable cohorts of HCWs, strict symptomatic screening procedure and sense of responsibility for not transmitting the infection to the sick patients and/or their colleagues in the clinical area. The rate of undetected SARS-CoV-2 infection may also indicate the percentage of mild or asymptomatic (SARS-CoV-2) infection among HCWs which was in 39% of our study positive group and have been reported to be 17.1% in the study by Shields et al. (2020) and a staggering 44% of positive testing HCWs did not realize they were ill a serological study conducted by the Influenza Vaccine Effectiveness in the Critically Ill (IVY) Network (Kuehn et al., 2020) . This high rate of undetected earlier infection in individuals working within a health care setting, whether in direct contact with patients or not, could have driven the spread of the disease via direct or indirect contact with uninfected personnel and/or environmental contamination.

The antibody positivity-driving factors within each risk category showed clear evidence that the hospital as a factor was important for the high and variable risk categories. This could be due to limited protection, especially during health care procedures or reflection of pre-symptomatic J o u r n a l P r e -p r o o f transmission, before universal masking at the national level was mandated at end of May 2020, or non-strict adherence to preventive measures, especially between co-workers (Al Maskari et al., 2021; Heinzerling et al., 2020; Wei et al., 2020) . The low-risk category was influenced mostly by community disease prevalence. Living with family, compared to living on hospital campus or in private shared accommodation, influenced positivity in the high risk worker as this group is mostly protected in the working environment but with family members, close contact risk is hard to be mitigated.

This study's strength is in the segregation and randomization of all individuals working within health care facilities based on their risk of being exposed to suspected or confirmed patients with COVID-19. This allowed a better understanding of healthcare-related transmission versus the impact of disease spread in the community. The use of quantitative measurement for the serology test helped in capturing actual infection prevalence for at least 6 months earlier (Patel et al., 2020) . The recall bias, incomplete filling of the questionnaire, inaccurate information, and/or wrong entries are some inherent limitations with surveys like in our study although its impact in the outcome analysis was minimized by the exclusion of poor-quality information. Given the kinetics of antibody development against SARS-CoV-2, individuals tested shortly after infection may not have mounted an antibody response and analyzing those with equivocal results as negative may have, to a small extent, under-estimated prevalence of COVID-19 in HCWs.

Prevention of infection in the workplace requires a multipronged, integrated approach that includes IPC strategies, occupational health and safety measures, adherence to public health measures and mitigation of social behavioral risk in the community. The finding of the study will influence future health care preparedness for infectious diseases outbreaks, epidemics and J o u r n a l P r e -p r o o f pandemics adding more attention and innovation for control of community-driven spread into health care facilities like universal masking, symptom detection, carrier status identification and environmental decontamination.

The epidemiology of SARS-CoV-2 in a health care setting is driven largely by disease prevalence in the community and workers from supporting services. The current infection control measures have succeeded in managing transmission in the high and variable risk categories; however, more attention is required for low-risk workers. Enforcing symptomatic screening, quarantine of exposed individuals, universal masking, and encouraging innovation in the diagnostic and monitoring tools within the health care setting will enhance the safety of health care during epidemics and pandemics.

Author contributions: AM, AW, JS, BA, and ES handled the conception, design, analysis and interpretation of data. ER, LA, KD, MS, SM, SB, AA, and AS were responsible for conducting the study in the included centers and communication with the study team centrally. EB, NZ, AQ, HK, KS, AJ, and SA participated in the study conception, design and logistics management. All the authors drafted the article or revised it critically for important intellectual content and provided final approval of the version for submission. Ethical Approval: Ethical approval for the study was issued from all the participating hospitals and each included participant signed informed consent to be part of the study.

Competing interests: None declared by any of the authors.

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Support staff includes; information technology, medical engineer, security, medical records # data from national serosurvey conducted the same time of our study as provided by the surveillance department for the included governorate with 11% median to define the high and low prevalence + Reference is the absence of symptoms $ this include nasal congestion or runny nose, chest pain, difficulty breathing, wheezing & this include headache, fatigue, and all others not mentioned in the list as free text entry 

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We are grateful to all the health care workers who are directly or indirectly involved in the prevention and management of SARS-CoV-2 infection during this pandemic. We thank all who participated and supported the conduction of this study from hospitals administration, infection prevention and control teams, quality and patient safety teams, professional development and career guidance departments, nursing departments, laboratory departments, and all the health care workers who agreed to be investigated. Special thanks to Dr Zawan Hamid Al Hasni and Ms Muna Rashid Al Hinai from Rustaq hospital, Ms Shiekha Al Maqbali, and Ms Mitha Al Jabri from Sohar hospital for their assistance to the study team.