1. Background
In late 2019, East Asia confronted an unexpected fatal respiratory disease that affected thousands of population. This type of severe acute respiratory syndrome (SARS), which was named SARS coronavirus 2 (SARS-CoV-2) or coronavirus disease 2 (COVID-19), spread rapidly and involved many countries with exponential growth (1). Iran was among the first countries involved in this pandemic, so that from the first officially reported case on 20 February 2020 (1) until 28 October 2020, 738,322 confirmed cases of COVID-19 and 40,582 deaths were reported across the country (2).
As known, COVID-19 has a wide range of severity from asymptomatic or mild to severe and rapidly fatal (3-6), while a significant number of these cases remain undetected, which is a challenging epidemiological issue (7). Therefore, detecting mild cases or asymptomatic carriers is important for implementing effective preventive measures in high-risk settings such as hospitals (8). To this aim, serological assays, which can define immunity based on seroprevalence, play a key role in detecting asymptomatic or previously exposed ones (8-10). Indeed, serosurvey has two major benefits; first, it can be used as a tool to determine local transmission and infection risk factors (9, 10), and second, it can be used to estimate protective immunity (9).
Healthcare workers (HCWs) are deemed to be at high risk due to their profession as frontline fighters against the disease (8, 11). Among HCWs, hospital staff (HS) are specifically at a high risk of infection. It is estimated that about 7,000 HCWs died worldwide until early September 2020 (12), and about 300 HCWs lost their lives in Iran up to early October 2020 due to COVID-19 (13). Besides, multiple factors can predispose HCWs to different psychological disorders during this pandemic (14), and monitoring their serological immunity status may help manage their psychological status regarding contracting this disease. On the other hand, HS burnout during this pandemic should not be overlooked, especially in the next months, when we may face a co-epidemic of COVID-19 and influenza, which increases the workload of hospitals more than before (15, 16). Therefore, it is necessary to define and monitor seroimmunity and risk factors of coronavirus infection in HS to protect them against this disease, which guides policymakers to make proper decisions to control the disease spread in hospitals (8).
It is revealed that in many patients with COVID-19, IgG can be detected before IgM appearance or at the same time (17). It is a good indicator of long-term immunity after contact with the virus (18). A study showed that anti-SARS-CoV-2 (IgG) presence is 40% in COVID-19 cases after less than a week of their symptoms’ onset, while this value increases up to 79.8% by day 15 after the onset of symptoms (19). Therefore, it is a reliable value to detect seroprevalence in cases presenting > 14 days after the onset of symptoms with a sensitivity and specificity of 96.2% and 96.6 %, respectively (20).
2. Objectives
We aimed to assess the seroprevalence of COVID-19 IgG in HS.
3. Methods
3.1. Study Design, Participants, and Data Collection
A cross-sectional serosurvey was conducted from July 13 to August 5, 2020, among HS including medical, para-medical, and administrative staff from two main hospitals of Shiraz City, with two million population as the capital city of Fars Province in the south of Iran. Finally, 494 HCWs were conveniently recruited based on their willingness to take part in the study. First, trained interviewers were asked to complete a checklist that consisted of questions about socio-demographic, occupational, and epidemiological characteristics. Having an underlying medical condition, prior COVID-19 infection or symptoms, conducting real-time polymerase chain reaction (RT-PCR), or lung computed tomography (CT) were also queried. We asked about risk perception, observance of isolation precaution (standard, droplet, airborne, contact), and passing its related course. The filling of checklists was individually done face-to-face in private. One of the selected hospitals was Ali-Asghar Hospital, which was the main referral center for COVID-19 cases. Another hospital was Dastgheib Hospital, which was a general hospital. The reason for choosing the second hospital was to reveal any probable difference in the measured items between the two hospitals, one of which was dedicated to COVID-19 cases while the other was not.
3.2. Serologic Measurement
About 5 mL of blood was taken from each participant. After centrifugation, the isolated sera were kept at -80°C until testing. The IgG level was measured according to the World Health Organization (WHO) guidelines (21) using an anti-SARS-CoV-2 ELISA kit (Pishtaz Co.®). In summary, 96-well plates were coated (100 ng/well) overnight with recombinant nucleoprotein (22), and then incubated with diluted serum samples at 1:101. The optical density (OD) (450 nm-630 nm) was measured. The cutoff value was calculated as the mean of negative serum OD plus 0.15. Then, the OD of the sample was divided by the calculated cutoff value to determine the cutoff index. The cutoff indices above 1.1 were considered as positive tests, and the cutoff indices below 0.9 were considered as negative tests (19, 23). For indices in the gray zone (0.9 - 1.1), testing was repeated by retaking the blood sample (maximum of three times) to achieve a definite value. Also, quality assurance was done by rechecking the data in another laboratory. A positive test indicated that the anti-SARS-CoV-2 (IgG) antibody was present in the blood.
3.3. Statistical Analysis
All statistical analyses were performed using SPSS 20.0. Mean, and the standard deviation was used to present continuous variables, while categorical variables were shown as frequency and percentage. Univariate analysis was done using parametric tests (t-test) and nonparametric tests (chi-squared). Multivariable analysis was also done after checking collinearity and VIF factors using logistic regression (enter method), considering P values < 0.05 as the significance level.
3.4. Ethical Approval and Consent to Participate
All subjects gave their written informed consent, while voluntary participation in all stages of this study was respected. Privacy was assured in all steps of the study, including interviews, data gathering, recording, analysis, and reporting. The results of antibody titers were sent for each of the participants by the Short Message service (SMS) based on their requests. The protocol of this study followed the ethical guidelines of the 1975 Declaration of Helsinki as approved by the Shiraz University of Medical Sciences (SUMS) Ethics Committee with registration number IR.SUMS.REC.1399.314.
4. Results
Among 494 participants in this study, 282 (57%) were from Ali-Asghar Hospital (COVID-19 referral hospital) and 212 (43%) from Dastgheib Hospital (general hospital). In general, 29 (5.9%) participants had anti-SARS-CoV-2 IgG antibodies, including 18 (6.4%) from the first hospital and 11 (5.2%) from the second hospital (P = 0.3). The mean age of the participants was 37.4 ± 8.8 years (min-max: 21 - 76), and the female (311) to male (183) ratio was 1.7. Of all the subjects, 355 (71.9%) were married compared to 139 (28.1%) who were single. Besides, 397 (80.4%) subjects were university graduates. Furthermore, 29 (5.9%) were medical doctors, and 155 (31.4%) were nurses, while 310 (62.8%) had been working in other fields such as operation rooms (7.9%), laboratories (5.9%), management (4.3%), health sciences (4.3%), and other paramedics (40.5%). Of 494 participants, 180 (36.4%) had official and 306 (61.9%) had non-official (contractual, mandatory) employment status. The duration of employment was 7.8 ± 7.3 years (min-max: 1 - 31), and their positions in the hospital were as follows: 142 (28.7%) is highly critical wards, 159 (32.2%) in semi-critical wards, and 193 (39.1%) in low critical departments of the hospital. We defined the following wards as highly critical departments: Emergency, triage, ICU, isolation room, operation room, and recovery room. Semi-critical parts consisted of admission wards, reception, out-patient clinics, laboratory, pharmacy, radiology, EKG unit, and rehabilitation department. Low critical sections were management, security, transport section, laundry, kitchen, morgue, engineering, research centers, and repository.
Among the staff, 318 (64.4%) had rotational and 164 (32.2%) had fixed work shifts. Out of all HCWs, 132 (26.7%) reported a kind of chronic disease such as gastrointestinal, psychological, pulmonary, hypertension, cardiac, diabetes mellitus, rheumatologic, and allergy. Among 494 subjects, 403 (81.6%) stated that they had a full-time job in the hospital, 221(44.7%) had had close contact with COVID-19-confirmed patients, 123 (24.9%) had a history of traveling to other cities or provinces at least once, and 79 (16%) were the host of traveler(s) from other cities or provinces in the period between the beginning of COVID-19 epidemic and the time of this study. Moreover, 320 (64.8%) had at least one of the clinical symptoms within six months before this survey, including headache (28.3%), myalgia (24.1%), sore throat (23.7%), dry cough (16.2%), arthralgia (15%), fever (15.4%), rhinorrhea (14.2%), chest discomfort (13.6%), sneezing (12.8%), dyspnea (12.1%), diarrhea (10.3%), chills (10.9%), productive cough (8.5%), nausea (7.1%), anosmia (2.4%), vomiting (2%), and ageusia (1.4%). Among all of studied HS, 347 (70.2%) had been sampled from their nasopharynx and oropharynx and tested by polymerase chain reaction (PCR) for COVID-19, while 42 (12.1%) were positive, and out of 103 (20.8%) for whom CT scan of the lungs had been done before, 21 (20.4%) were positive for COVID-19, based on self-reports (Table 1). Furthermore, among individuals with positive PCR, nine (21.4%) had anti-SARS-CoV-2 IgG, while this figure was seven (33.3%) for individuals with positive CT scans (Table 2). Among all responders, 213 (43.1%) were highly concerned and anxious about becoming infected with COVID-19 in the hospital, while 341 (69%) reported that their families had a high level of anxiety about this issue. Among interviewees, 223 (45.1%) considered COVID-19 as a severe and virulent disease. Table 1 shows the comparison of demographic, epidemiological, clinical, paraclinical, and risk perception characteristics in both studied hospitals.
Table 1.General, Epidemiological, Clinical, Paraclinical, and Risk Perception Characteristics of Health Care Staff in the COVID-19 Referral Hospital Compared to a General Hospital in Shiraz, Iran (N = 494) a
| Characteristics | COVID-19 Referral Hospital (N = 282) | General Hospital (N = 212) | Statistic (P Value) |
|---|---|---|---|
| Age, y | 36.7 ± 8.6 | 38.3 ± 9.0 | 1.9 (0.04) |
| Gender | 6.4 (0.01) | ||
| Female | 164 (58.2) | 147 (69.3) | |
| Male | 118 (41.8) | 65 (30.7) | |
| Marital status | 1.3 (0.25) | ||
| Married | 197 (69.9) | 158 (74.5) | |
| Single | 85 (30.1) | 54 (25.5) | |
| Education | 0.3 (0.54) | ||
| ≤ 12 | 58 (20.6) | 39 (18.4) | |
| > 12 | 224 (79.4) | 173 (81.6) | |
| Field of education | 20.3 (< 0.001) | ||
| Medicine | 17 (6) | 12 (5.7) | |
| Nursing | 111 (39.4) | 44 (20.8) | |
| Others | 154 (54.6) | 156 (73.6) | |
| Working Department in hospitalb | 5.9 (0.051) | ||
| Highly critical | 80 (28.4) | 62 (29.2) | |
| Semi-critical | 80 (28.4) | 79 (37.3) | |
| Low critical | 122 (43.3) | 71 (33.5) | |
| Duration of employment in this hospital, y | 6.8 ± 6.8 | 9.1 ± 7.8 | 3.3 (0.001) |
| Type of employment | 1.1 (0.278) | ||
| Official | 98 (35) | 82 (39.8) | |
| Non-official | 182 (65) | 124 (60.2) | |
| Work shifts, N/week | 7 ± 1.6 | 6.9 ± 3.4 | -0.2 (0.77) |
| Type of work shift | 0.03 (0.86) | ||
| Rotational | 181 (66.3) | 137 (65.6) | |
| Fixed | 92 (33.7) | 72 (34.4) | |
| Having chronic disease | 2.7 (0.1) | ||
| Yes | 63 (33.3) | 69 (41.8) | |
| No | 126 (66.7) | 96 (58.2) | |
| Working in this hospital from the beginning of COVID-19 epidemic | 18.5 (< 0.001) | ||
| Yes | 247 (89.2) | 156 (74.3) | |
| No | 30 (10.8) | 54 (25.7) | |
| Having close contact with defined COVID-19 Patient(s) within six months ago | 34.3 (< 0.001) | ||
| Yes | 131 (78.9) | 90 (48.6) | |
| No | 35 (21.1) | 95 (51.4) | |
| Having a history of traveling within six months ago | 0.67 (0.41) | ||
| Yes | 74 (27.6) | 49 (24.3) | |
| No | 194 (72.4) | 153 (75.7) | |
| Being the host of traveler(s) within six months ago | 4.4 (0.036) | ||
| Yes | 36 (13.6) | 43 (20.9) | |
| No | 229 (86.4) | 163 (79.1) | |
| Having COVID-19 symptom(s) within six months ago | 7.1 (0.007) | ||
| Yes | 195 (71.4) | 125 (59.8) | |
| No | 78 (28.6) | 84(40.2) | |
| Type of symptoms within six months ago | |||
| Fever | 0.2 (0.604) | ||
| Yes | 48 (24.4) | 28 (21.9) | |
| No | 149 (75.6) | 100 (78.1) | |
| Cough | 0.001 (0.981) | ||
| Yes | 69 (35) | 45 (35.2) | |
| No | 128 (65) | 83 (64.8) | |
| Dyspnea | 4.9 (0.026) | ||
| Yes | 44 (22.3) | 16 (12.5) | |
| No | 153 (77.7) | 112 (87.5) | |
| Chest discomfort | 4.2 (0.038) | ||
| Yes | 48 (24.4) | 19 (14.8) | |
| No | 149 (75.6) | 109 (85.2) | |
| Myalgia | 4.3 (0.037) | ||
| Yes | 81 (41.1) | 38 (29.7) | |
| No | 116 (58.9) | 90 (70.3) | |
| Anosmia | FE (0.77) | ||
| Yes | 8 (4.1) | 4 (3.1) | |
| No | 189 (95.9) | 124 (96.9) | |
| Ageusia | FE (1) | ||
| Yes | 4 (2) | 3 (2.3) | |
| No | 193 (98) | 125 (97.7) | |
| How much did you feel about getting COVID-19 in this hospital during the first months of COVID-19 epidemic? | 18.2 (< 0.001) | ||
| High to very high | 120 (42.6) | 51 (24.1) | |
| None to moderate | 162 (57.4) | 161 (75.9) | |
| How much did you feel about getting COVID-19 in this hospital during this period of COVID-19 epidemic? | 2.3 (0.123) | ||
| High to very high | 130 (46.1) | 83 (39.2) | |
| None to moderate | 152 (53.9) | 129 (60.8) | |
| How has been changed your anxiety about getting COVID-19 from the beginning of its epidemic till now? | 0.5 (0.462) | ||
| Remained high or became high | 121 (42.9) | 98 (46.2) | |
| Remained low or became low | 161 (57.1) | 114 (53.8) | |
| How has changed your family's anxiety about your getting COVID-19 from the beginning of this epidemic till now? | 4.9 (0.026) | ||
| Remained high or became high | 206 (73) | 135 (63.7) | |
| Remained low or became low | 76 (27) | 77 (36.3) | |
| How much do you know COVID-19 as a virulent disease? | 0.4 (0.499) | ||
| High to very high | 131 (46.5) | 92 (43.4) | |
| None to moderate | 151 (53.5) | 120 (56.6) | |
| Anti-COVID-19 IgG | 0.3 (0.576) | ||
| Positive | 18 (6.4) | 11 (5.2) | |
| Negative | 264 (93.6) | 201 (94.8) | |
| PCR test for COVID-19 | 0.03 (0.856) | ||
| Positive | 28 (12.3) | 14 (11.7) | |
| Negative | 199 (87.7) | 106 (88.3) | |
| CT scan of lungs for COVID-19 | FE (0.501) | ||
| Positive | 17 (19.3) | 4 (26.7) | |
| Negative | 71 (80.7) | 11 (73.3) |
Abbrevation: PCR, polymerase chain reaction.
aValues are expressed as No. (%) or mean ± SD.
bHighly Critical, emergency, triage, ICU, isolation room, operation room, recovery room. Semi-critical, admission wards, reception, out-patient clinics, laboratory, pharmacy-radiology, EKG unit, rehabilitation department. Low critical, management, security, transport section, laundry, kitchen, cold room, engineering, research centers, repository.
Table 2.Univariable Analysis of Associated Factors with Immunity Against COVID-19 in Public Hospital Staff in Shiraz, Irana
| Characteristics | Having Anti-COVID-19 IgG (N = 29) | Not Having Anti-COVID-19 IgG (N = 446) | Statistic (P Value) | OR (%95 CI) |
|---|---|---|---|---|
| Type of hospital COVID-19 | 0.3 (0.576) | 1.2 (0.576 - 2.7) | ||
| Referral hospital | 18 (6.4) | 264 (93.6) | ||
| General hospital | 11 (5.2) | 201 (94.8) | ||
| Age, y | 40.4 ± 10.6 | 37.2 ± 8.6 | -1.8 (0.058) | - |
| Gender | 0.01 (0.919) | 0.9 (0.4 - 2) | ||
| Male | 11 (6) | 172 (94) | ||
| Female | 18 (5.8) | 293 (94.2) | ||
| Marital status | 0.2 (0.622) | 1.2 (0.5 - 2.9) | ||
| Married | 22 (6.2) | 333 (93.8) | ||
| Single | 7 (5) | 132 (95) | ||
| Education, y | 0.3 (0.529) | 0.7 (0.3 - 1.8) | ||
| ≤ 12 | 7 (7.2) | 90 (92.8) | ||
| > 12 | 22 (5.5) | 375 (94.5) | ||
| Field of education | 0.006 (0.937) | 0.9 (0.4 - 2.1) | ||
| Medicine | 11 (6) | 173 (94) | ||
| Nursing/others | 18 (5.8) | 292 (94.2) | ||
| Working Department in the hospitalb | 2.8 (0.089) | 0.4 (0.2 - 1.1) | ||
| Highly critical | 22 (7.3) | 279 (92.7) | ||
| Semi-critical/low-critical | 7 (3.6) | 186 (96.4) | ||
| Duration of employment in this hospital, y | 9.4 ± 8.5 | 7.7 ± 7.2 | -1.1 (0.232) | - |
| Type of employment | 0.3 (0.581) | 1.2 (0.5 - 2.8) | ||
| Official | 9 (5) | 171 (95) | ||
| Non-official | 19 (6.2) | 287 (93.8) | ||
| Work shifts, N/week | 7.5 ± 1.6 | 6.9 ± 2.6 | -0.8 (0.408) | - |
| Type of work shift | 7.1 (0.007) | 4.5 (1.3 - 15.4) | ||
| Rotational | 25 (7.9) | 293 (92.1) | ||
| Fixed | 3 (1.8) | 161 (98.2) | ||
| Having a chronic disease | 1 (0.316) | 0.613 (0.234 - 1.6) | ||
| Yes | 6 (4.5) | 126 (95.5) | ||
| No | 16 (7.2) | 206 (92.8) | ||
| Working in this hospital from the beginning of COVID-19 epidemic | FE = 0.447 | 0.56 (0.165 - 1.899) | ||
| Yes | 25 (6.2) | 378 (93.8) | ||
| No | 3 (3.6) | 81 (96.4) | ||
| Having close contact with a defined COVID-19 patient(s) within six months ago | 0.0 (0.986) | 1(0.387 - 2.631) | ||
| Yes | 12 (5.4) | 209 (94.6) | ||
| No | 7 (5.4) | 123 (94.6) | ||
| Having a history of traveling within six months ago | 0.2 (0.631) | 0.796 (0.314 - 2) | ||
| Yes | 6 (4.9) | 117 (95.1) | ||
| No | 21 (6.1) | 326 (93.9) | ||
| Hosting of traveler(s) within six months ago | FE = 0.798 | 1 (0.399 - 2.9) | ||
| Yes | 5 (6.3) | 74 (93.7) | ||
| No | 23 (5.9) | 369 (94.1) | ||
| Having COVID-19 symptoms within six months ago | 0.3 (0.561) | 0.779 (0.336 - 1.8) | ||
| Yes | 20 (6.3) | 300 (93.8) | ||
| No | 8 (4.9) | 154 (95.1) | ||
| Result of PCR test for COVID-19 | FE = 0.000 | 0.163 (0.065 - 0.411) | ||
| Positive | 9 (21.4) | 33 (78.6) | ||
| Negative | 13 (4.3) | 292 (95.7) | ||
| CT scan of lungs for COVID-19 | FE = 0.001 | 0.103 (0.026 - 0.397) | ||
| Positive | 7 (33.3) | 14 (66.7) | ||
| Negative | 4 (4.9) | 78 (95.1) | ||
| How much did you feel about getting COVID-19 in this hospital during the first months of COVID-19 epidemic? | 2.5 (0.111) | 0.546 (0.257 - 1.16) | ||
| High to very high | 14 (8.2) | 157 (91.8) | ||
| None to moderate | 15 (4.6) | 308 (95.4) | ||
| How much did you feel about getting COVID-19 in this hospital during this period of COVID-19 epidemic? | 0.3 (0.563) | 0.8 (0.38 - 1.7) | ||
| High to very high | 14 (6.6) | 199 (93.4) | ||
| None to moderate | 15 (5.3) | 266 (94.7) | ||
| How has been changed your anxiety about getting COVID-19 from the beginning of this epidemic till now? | 0.1 (0.659) | 1.1 (0.559 - 2.5) | ||
| Remained high or became high | 14 (6.4) | 205 (93.6) | ||
| Remained low or became low | 15 (5.5) | 260 (94.5) | ||
| How has changed your family's anxiety about your getting COVID-19 from the beginning of this epidemic till now? | 0.6 (0.403) | 0.7 (0.331 - 1.56) | ||
| Remained high or became high | 18 (5.3) | 323 (94.7) | ||
| Remained low or became low | 11 (7.2) | 142 (92.8) | ||
| How much do you know COVID-19 as a fatal disease? | 0.1 (0.727) | 0.8 (0.413 - 1.853) | ||
| High to very high | 14 (6.3) | 209 (93.7) | ||
| None to moderate | 15 (5.5) | 256 (94.5) | ||
| Observance of standard precautions | ||||
| Proper hand washing with soaps or disinfecting them before and after contact with any patient or patients' specimen | FE = 1 | 0.94 (0.91 - 0.96) | ||
| Often to always | 19 (5.8) | 307 (94.2) | ||
| None to sometimes | 0 (0) | 4 (100) | ||
| Proper hand washing before and after removing gloves | FE = 1 | 1 (0.136 - 8.6) | ||
| Often to always | 18 (5.8) | 293 (94.2) | ||
| None to sometimes | 1 (6.3) | 15 (93.8) | ||
| Wearing gloves when contacting patients or their specimens | FE = 0.643 | 1.5 (0.325 - 6.941) | ||
| Often to always | 17 (6) | 268 (94) | ||
| None to sometimes | 2 (8.7) | 21 (91.3) | ||
| Proper disposal of used protective equipment or infectious wastes | FE = 0.006 | 13.7 (2.8 - 66.8) | ||
| Often to always | 16 (5.2) | 294 (94.8) | ||
| None to sometimes | 3 (42.9) | 4 (57.1) | ||
| Disinfection of surfaces and equipment that are in close with patients | FE = 0.251 | 2.3 (0.496 - 11.3) | ||
| Often to always | 18 (6.1) | 277 (93.9) | ||
| None to sometimes | 2 (13.3) | 13 (86.7) | ||
| Observance of droplet precaution | ||||
| Keeping a distance of at least 1.5 meters from a patient suspected of having COVID-19 | FE = 0.481 | 1.4 (0.398 - 5.11) | ||
| Often to always | 18 (6.2) | 274 (93.8) | ||
| None to sometimes | 3 (8.6) | 32 (91.4) | ||
| Wearing a medical or surgical mask when being less than 1.5 meters away from a patient suspected of having COVID-19 | FE = 1 | 0.936 (0.91 - 0.964) | ||
| Often to always | 20 (6.4) | 294 (93.6) | ||
| None to sometimes | 0 (0) | 6 (100) | ||
| Using goggles or face shields in the case of close contact with a patient suspected of having COVID-19 | 0.4 (0.49) | 0.676 (0.221 - 2) | ||
| Often to always | 18 (7.8) | 213 (92.2) | ||
| None to sometimes | 4 (5.4) | 70 (94.6) | ||
| Using surgical gowns in the case of close contact with a patient suspected of having COVID-19 | FE = 0.219 | 0.225 (0.029 - 1.726) | ||
| Often to always | 18 (7.7) | 215 (92.3) | ||
| None to sometimes | 1 (1.9) | 53 (98.1) | ||
| Observance of airborne precautions | ||||
| Exclusive use of filtered masks such as N95 and FFP2 if the patient's respiratory particles are suspected to be aerosolized | FE = 0.385 | 0.455 (0.102 - 2) | ||
| Often to always | 18 (7.9) | 209 (92.1) | ||
| None to sometimes | 2 (3.8) | 51 (96.2) | ||
| Have you ever passed training courses about COVID-19-related isolation precautions? | FE = 1 | 0.92 (0.264 - 3.2) | ||
| Yes | 19 (5.3) | 338 (94.7) | ||
| No | 3 (4.9) | 58 (95.1) |
Abbreviation: PCR, polymerase chain reaction.
aValues are expressed as No. (%) or mean ± SD.
bHighly critical, emergency, triage, ICU, isolation room, operation room, recovery room. Semi-critical, admission wards, reception, out-patients clinics, laboratory, pharmacy-radiology, EKG unit, rehabilitation department. Low critical, management, security, transport section, laundry, kitchen, cold room, engineering, research centers, repository.
Table 3 shows the difference between isolation precautions, which were observed in the two studied hospitals. As a standard precaution, regular and proper handwashing before and after contact with any patient and before and after using gloves was observed by 326 (66%) and 311 (63%) of the hospital staff, respectively. Wearing gloves before contact with patients or their specimens was observed by 285 (57.7%), while proper disposal of used protective equipment or infectious waste and disinfection of surfaces and equipment that were in close contact with patients all or most of the time were applied by 310 (62.8%) and 295 (59.7%) of the interviewees, respectively. As the droplet precaution, keeping a distance of at least 1.5 meters from patients suspected of COVID-19 and wearing a medical or surgical mask while being in close contact with them were observed by 292 (59.1%) and 314 (63.6%) of the respondents, respectively. Considering contact precautions, goggles or face shields were used by 231 (46.8%), and wearing a surgical gown was reported by 233 (47.2%) in the case of being in close contact with a patient suspected of COVID-19. As the airborne precaution, putting on filtered masks if the patient’s respiratory particles were suspected to be aerosolized (e.g., in bronchoscopy, endoscopy, respiratory and cardiovascular resuscitation), was applied by 227 (46%). Out of all respondents, 357 (72.3%) had passed education about isolation precautions regarding COVID-19.
Table 3.Observance of Isolation Precaution Toward COVID-19 by Health Care Staff in the COVID-19 Referral Hospital (N = 282) Compared to a General Hospital in Shiraz, Iran (N = 212)a
| Item | COVID-19 Referral Hospital | General Hospital | Statistic (P Value) |
|---|---|---|---|
| Standard precaution | |||
| Proper handwashing with soap or disinfecting them before and after contact with any patient or patient’ specimen | FE = 0.364 | ||
| Often to always | 167 (99.4) | 159 (98.1) | |
| None to sometimes | 1 (0.6) | 3 (1.9) | |
| Proper handwashing before and after removing gloves | 0.7 (0.388) | ||
| Often to always | 160 (94.1) | 151 (96.2) | |
| None to sometimes | 10 (5.9) | 6 (3.8) | |
| Wearing gloves when contacting patients or their specimens | 1.1 (0.293) | ||
| Often to always | 141 (91) | 144 (94.1) | |
| None to sometimes | 14 (9) | 9 (5.9) | |
| Proper disposal of used protective equipment or infectious wastes | FE = 0.266 | ||
| Often to always | 163 (98.8) | 147 (96.7) | |
| None to sometimes | 2 (1.2) | 5 (3.3) | |
| Disinfection of surfaces and equipment that are in close with patients | 0.1 (0.713) | ||
| Often to always | 152 (95.6) | 143 (94.7) | |
| None to sometimes | 7 (4.4) | 8 (5.3) | |
| Droplet precaution | |||
| Keeping a distance of at least 1.5 meters from a patient suspected of having COVID-19 | 12.8 (< 0.001) | ||
| Often to always | 140 (83.3) | 152 (95.6) | |
| None to sometimes | 28 (16.7) | 7 (4.4) | |
| Wearing a medical or surgical mask when being less than 1.5 meters away from a patient suspected of having COVID-19 | FE = 0.433 | ||
| Often to always | 164 (98.8) | 150 (97.4) | |
| None to sometimes | 2 (1.2) | 4 (2.6) | |
| Contact Precaution | |||
| Using goggles or face shields in the case of close contact with a patient suspected of having COVID-19 | 4.1 (0.043) | ||
| Often to always | 128 (80.5) | 103 (70.5) | |
| None to sometimes | 31 (19.5) | 43 (29.5) | |
| Using surgical gowns in the case of close contact with a patient suspected of having COVID-19 | 38 (< 0.001) | ||
| Often to Always | 143 (94.7) | 90 (66.2) | |
| None to Sometimes | 8 (5.3) | 46 (33.8) | |
| Airborne precaution | |||
| Exclusive use of filtered masks such as N95 and FFP2 if the patient’s respiratory particles are suspected to be aerosolized | 30.2 (< 0.001) | ||
| Often to always | 142 (92.8) | 85 (66.9) | |
| None to sometimes | 11 (7.2) | 42 (33.1) |
aValues are expressed as No. (%).
The univariable analysis showed that hospital health workers whose daily work shifts were rotational (7.9%) were more likely to have anti-SARS-CoV-2 IgG than the ones with fixed shifts (1.8%) (P = 0.007) (Table 2). Moreover, having IgG was more prevalent in individuals who had not accurately followed the proper disposal of used protective equipment or infectious wastes (42.9%) than in the counterpart group (5.2%) (FE = 0.006) (Table 2).
Multivariable analysis revealed that non-proper disposal of used protective equipment or infectious wastes (OR = 26.5), rotational daily work shifts (OR = 7.5), being anxious about getting infected with COVID-19 (OR = 3.8), and age (OR = 1.06) were the significant determinants of having anti-SARS-CoV-2 IgG in HS (Table 4).
Table 4.Multivariable Analysis of Associated Factors with Immunity Against COVID-19 in Public Hospitals’ Staff in Shiraz, Iran
| Variable | B | EXP B | 95% CI | P-Value |
|---|---|---|---|---|
| Constant | -7.47 | 0.001 | - | < 0.001 |
| Age | 0.059 | 1.06 | 1.01 - 1.11 | 0.018 |
| Being anxious about getting COVID-19 | 1.33 | 3.8 | 1.3 - 10.9 | 0.013 |
| Rotational versus fixed work shifts in the hospital | 2.02 | 7.5 | 1.4 - 40.4 | 0.018 |
| Non-proper disposal of used protective equipment or infectious wastes | 3.2 | 26.5 | 2.9 - 236.3 | 0.003 |
5. Discussion
This study showed that about one out of 17 HS had anti-SARS-CoV-2 IgG, and no significant difference was noticed in the seroprevalence of COVID-19 IgG between the main referral and general hospitals. However, older HS, those who were more anxious, those who had rotational daily work shifts, and especially those that implemented improper disposal of used protective equipment or infectious wastes had a higher probability of the previous infection with this virus.
Studies about the seroprevalence of COVID-19 IgG in different clinical settings have various findings. Seroprevalence varies from 0.74% among medical staff in a retrospective study, which was performed at a hospital in Fujisawa, Japan (24), to 17% among high-risk healthcare workers on day 14 in an observational study conducted in Nanjing Drum Tower Hospital in China (8). Other surveys showed the IgG seroprevalence among HCWs was 11% (Brussel, Belgium) (11), 1.2% (Essen, Germany) (25), 0.83% ( New Jersey, USA) (20), 2.0% (Wuhan, China) (26), 1.7% (Naples, Italy) (27), 1.6% (Indianapolis, USA) (28), 2.7% (Copenhagen, Denmark) (29), 7.4% (Milan, Italy) (30), and 4.9% (Michigan, USA) (31). These findings are more or less similar to our findings. The different results may be due to various methodologies. For instance, Brussel et al.’s study was performed two weeks after the first epidemiological wave with Ig seroprevalence estimation of 11% at baseline (11), while Essen et al.’s study was performed about two weeks before this wave with IgG seroprevalence estimation of 1.2% (25). Part of data collection coincided with the second epidemiological wave of the disease in Iran, which could have raised the seroprevalence rate.
Also, it was revealed that non-proper disposal of used protective equipment or infectious wastes was the most significant determinant of having anti-SARS-CoV-2 IgG in HS. Indeed, proper disposal of used protective equipment differs from the proper use of protective equipment, which should not be overlooked by the nosocomial infection control team, especially as about one-third of HS had not passed education and training about COVID-19 isolation precautions. Another study that highlighted the importance of assessing the seroprevalence of COVID-19 immunity among HS emphasized the proper protection awareness of HCWs (26).
We also found that HCWs with rotational shifts were more susceptible to becoming infected with COVID-19 than HCWs with fixed shifts. It may be due to the different COVID-19 exposure rates among morning, afternoon, and evening shift workers and the possible adverse effect of rotational work shifts on human immunity, as a recent study showed that night shift, working can influence the immune system (32).
Furthermore, we found that being anxious about getting the disease (which was seen in about half of the HS) increased the chance of becoming infected. Anxiety is also one of the factors that can impact the immune system (33), and it can be the result of some misunderstanding about COVID-19 among HCWs that leads to obsession. Therefore, it is essential to decrease anxiety (1) in HS via continuous mental support and training for them.
We also realized that being older is a determinant that can slightly increase the positivity of anti-SARS-CoV-2 IgG. However, another study did not show such a significant difference (26).
This survey also revealed that no significant difference existed in the rates of seropositivity of anti-COVID-19 IgG between HS with different positions in the hospital (highly critical, semi-critical, and low critical departments). This may suggest that the hospitals are well protected in all parts and that a high rate of exposure to SARS-CoV-2 occurred outside the hospital. Another study came to the same conclusion according to the evaluated risk factors (31).
5.1. Strengths and Limitations
As a strong point, this study was performed in a double-center setting (a COVID-19 main referral hospital and a general hospital), which provided making a comparison between them, considering different clinical, paraclinical, socioeconomic, and infection control variables. However, this study had some limitations. We could not conduct a longitudinal serosurvey (due to the logistic and budget shortages); however, the findings can be used as a baseline for future serosurveys. Moreover, the sampling method was convenient, although the participants were from nearly all sections of the hospitals.
5.2. Conclusion
The majority of HS did not have anti-SARS-CoV-2 IgG even though they had anxiety about getting this disease. Continuous training and providing technical consultation about this disease, especially the proper disposal of used protective equipment or infectious wastes in rotational daily shift workers, is recommended, while psychological support of HS should not be neglected.
