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A prospective study of risk factors associated with seroprevalence of SARS-CoV-2 antibodies in healthcare workers at a large UK teaching hospital

Open AccessPublished:September 01, 2022DOI:https://doi.org/10.1016/j.jinf.2022.08.030

      Highlights

      • The risk of SARS-CoV-2 infection in healthcare workers is highly heterogeneous
      • The risk of SARS-CoV-2 is significantly higher in BAME healthcare workers
      • Working in COVID-19 specific areas increases the risk of infection
      • Porters, domestic staff, and healthcare assistants are healthcare staff at highest risk of SARS-CoV-2 infection.

      Abstract

      Objectives

      To describe the risk factors for SARS-CoV-2 infection in UK healthcare workers (HCWs).

      Methods

      We conducted a prospective sero-epidemiological study of HCWs at a major UK teaching hospital using a SARS-CoV-2 immunoassay. Risk factors for seropositivity were analysed using multivariate logistic regression.

      Results

      410/5,698 (7·2%) staff tested positive for SARS-CoV-2 antibodies. Seroprevalence was higher in those working in designated COVID-19 areas compared with other areas (9·47% versus 6·16%) Healthcare assistants (aOR 2·06 [95%CI 1·14-3·71]; p=0·016) and domestic and portering staff (aOR 3·45 [95% CI 1·07-11·42]; p=0·039) had significantly higher seroprevalence than other staff groups after adjusting for age, sex, ethnicity and COVID-19 working location. Staff working in acute medicine and medical sub-specialities were also at higher risk (aOR 2·07 [95% CI 1·31-3·25]; p<0·002). Staff from Black, Asian and minority ethnic (BAME) backgrounds had an aOR of 1·65 (95% CI 1·32 – 2·07; p<0·001) compared to white staff; this increased risk was independent of COVID-19 area working. The only symptoms significantly associated with seropositivity in a multivariable model were loss of sense of taste or smell, fever, and myalgia; 31% of staff testing positive reported no prior symptoms.

      Conclusions

      Risk of SARS-CoV-2 infection amongst HCWs is highly heterogeneous and influenced by COVID-19 working location, role, age and ethnicity. Increased risk amongst BAME staff cannot be accounted for solely by occupational factors.

      Key words

      Background

      With >580 million cases and >6 million deaths reported to date globally, the ongoing COVID-19 pandemic continues to impact daily life (

      World Health Organisation. Coronavirus Disease (COVID-2019) Situation Reports. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports. Accessed September 23rd 2020.

      ). A nationwide lockdown in the UK on 23rd March 2020 succeeded in slowing infection rates during the “first wave” (
      • Anderson RM
      • Hollingsworth TD
      • Baggaley RF
      • Maddren R
      • Vegvari C.
      COVID-19 spread in the UK: the end of the beginning?.
      ); however, subsequent waves and the emergence of novel dominant variants have continued to place unprecedented pressure on the NHS (

      UK Health Security Agency. COVID-19 Variants: Genomically Conformed Case Numbers [Available from: https://www.gov.uk/government/publications/covid-19-variants-genomically-confirmed-case-numbers.

      , ) and drive infections globally (
      • Lin L
      • Zhao Y
      • Chen B
      • He D.
      Multiple COVID-19 waves and vaccination effectiveness in the United States.
      ,
      • Viana R
      • Moyo S
      • Amoako DG
      • Tegally H
      • Scheepers C
      • Althaus CL
      • et al.
      Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa.
      ,
      • Volz E
      • Mishra S
      • Chand M
      • Barrett JC
      • Johnson R
      • Geidelberg L
      • et al.
      Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England.
      ). The logistics of managing patients with COVID-19 presented unique challenges to hospitals and NHS trusts across the UK; evidence and practices evolved rapidly as experience was gained. Healthcare workers (HCWs) are at a higher risk of SARS-CoV-2 infection than the general population (
      • Nguyen LH
      • Drew DA
      • Graham MS
      • Joshi AD
      • Guo CG
      • Ma W
      • et al.
      Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study.
      ,
      • Gomez-Ochoa SA
      • Franco OH
      • Rojas LZ
      • Raguindin PF
      • Roa-Diaz ZM
      • Wyssmann BM
      • et al.
      COVID-19 in healthcare workers: a living systematic review and meta-analysis of prevalence, risk factors, clinical characteristics, and outcomes.
      ), and subsequent evidence has emerged for risk factors associated with SARS-CoV-2 infection in front-line HCWs (
      • Eyre DW
      • Lumley SF
      • O'Donnell D
      • Campbell M
      • Sims E
      • Lawson E
      • et al.
      Differential occupational risks to healthcare workers from SARS-CoV-2 observed during a prospective observational study.
      ,
      • Shields A
      • Faustini SE
      • Perez-Toledo M
      • Jossi S
      • Aldera E
      • Allen JD
      • et al.
      SARS-CoV-2 seroprevalence and asymptomatic viral carriage in healthcare workers: a cross-sectional study.
      ,
      • Dimcheff DE
      • Schildhouse RJ
      • Hausman MS
      • Vincent BM
      • Markovitz E
      • Chensue SW
      • et al.
      Seroprevalence of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) infection among VA healthcare system employees suggests higher risk of infection when exposed to SARS-CoV-2 outside of the work environment.
      ,
      • Bandyopadhyay S
      • Baticulon RE
      • Kadhum M
      • Alser M
      • Ojuka DK
      • Badereddin Y
      • et al.
      Infection and mortality of healthcare workers worldwide from COVID-19: a systematic review.
      ).
      Protecting HCWs by identifying risk factors for SARS-CoV-2 infection will continue to be paramount3 as the UK accepts coronavirus as a common endemic disease. Controlling transmission within a hospital setting, as well as from hospitals back into the community, was a key element in controlling the pandemic (
      The Lancet
      COVID-19: protecting health-care workers.
      ,
      • Wang J
      • Zhou M
      • Liu F.
      Reasons for healthcare workers becoming infected with novel coronavirus disease 2019 (COVID-19) in China.
      ). However, defining HCW specific risk-factors remains a challenge. Additionally, higher rates of symptomatic SARS-CoV-2 infection, hospitalisation and death have been observed amongst patients from ethnic minority populations in the UK (
      • Sapey E
      • Gallier S
      • Mainey C
      • Nightingale P
      • McNulty D
      • Crothers H
      • et al.
      Ethnicity and risk of death in patients hospitalised for COVID-19 infection in the UK: an observational cohort study in an urban catchment area.
      ) and worldwide (
      • Vahidy FS
      • Nicolas JC
      • Meeks JR
      • Khan O
      • Pan A
      • Jones SL
      • et al.
      Racial and ethnic disparities in SARS-CoV-2 pandemic: analysis of a COVID-19 observational registry for a diverse US metropolitan population.
      ,
      • Price-Haywood EG
      • Burton J
      • Fort D
      • Seoane L.
      Hospitalization and mortality among black patients and white patients with Covid-19.
      ); the reasons for this disparity are unclear. Reported infections in HCW suggests higher mortality in HCWs from minority backgrounds (
      • Kursumovic E
      • Lennane S
      • Cook TM.
      Deaths in healthcare workers due to COVID-19: the need for robust data and analysis.
      ); however, it is not yet clear to what extent workplace exposures influence infection. Here, we present the results of a large sero-epidemiological study of SARS-CoV-2 seropositivity in staff at a teaching hospital in the East of England undertaken during the first wave of the COVID-19 pandemic.

      Methods

      Setting

      Cambridge University Hospitals NHS Foundation Trust (CUH) is a tertiary referral centre and teaching hospital with 1,000 beds and 11,545 staff serving a population of 580,000 people in the East of England. The facility is equipped with a 20-bed ICU, a 23-bed neurosciences and trauma ICU, and an Emergency Department that receives ∼14,000 attendees a month. Between March and June 2020, CUH treated 525 patients with PCR-confirmed COVID-19 (Figure 1). The peak of COVID-19 admissions occurred in late March and early April 2020, with comparatively few COVID-19 admissions from June 2020 onwards. The definition of COVID-19 working for the purpose of risk stratification included clinical areas designated as either “Red” (patients with PCR-confirmed SARS-CoV-2 infection) or “Amber” (patients for whom there is a high clinical suspicion of COVID-19).
      Figure 1:
      Figure 1Epidemic curve of COVID-19 admissions at Cambridge University Hospitals NHS Foundation Trust
      As of September 2020, the East of England reported 27,516 laboratory-confirmed cases of SARS-CoV-2 infection (
      Gov.uk Coronavirus
      (COVID-19) in the UK. Cases in United Kingdowm.
      ), with a corresponding population rate of 441·2 per 100,000 people as of September 2020. This rate was substantially less than the worst affected regions of North West England (772·9/100,000) and Yorkshire and the Humber (693·2/100,000) (
      Gov.uk Coronavirus
      (COVID-19) in the UK. Cases in United Kingdowm.
      ). According to the 2011 England and Wales census (
      Office for National Statistics
      UK census.
      ) 85·3% of the population of the East of England are White British, 5·5% are White Other, 4·8% are Asian, 2% are Black, and 1·9% are of Mixed ethnicity. The proportion of Black, Asian, and Minority Ethnic (BAME) staff employed at CUH is representative of the overall NHS workforce () (21·2% vs 20·7%, respectively).
      An asymptomatic staff screening programme using SARS-CoV-2 PCR testing was established in April 2020 (
      • Rivett L
      • Sridhar S
      • Sparkes D
      • Routledge M
      • Jones NK
      • Forrest S
      • et al.
      Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.
      ). A staff screening programme for SARS-CoV-2 serological testing was initiated on the 10th of June 2020. All staff members were invited by email to participate in the serological screening programme and asked to self-refer for a clinic appointment. Written informed consent was obtained from all participants enrolled into this study. As part of this process all participants were invited to join the NIHR BioResource – COVID-19 Research Cohort (IRAS 220277). At enrolment, participants completed a questionnaire asking about demographic characteristics, healthcare role, ethnicity, previous symptoms consistent with COVID-19 and previous results of SARS-CoV-2 PCR testing. A total of 7·8 ml of blood was collected, including one serum sample and one whole blood sample. The serum sample was assayed for total SARS-CoV-2 antibody; both residual serum and whole blood were stored for future analyses.

      Laboratory assays

      Serological testing for antibodies directed against SARS-CoV-2 was performed using the Centaur XP SARS-Cov-2 Total Antibody assay (Siemens Healthcare Limited, Surrey, UK). This method is a fully automated high throughput enzyme linked chemiluminescent bridging immunoassay which targets the S1RBD antigen of SARS-CoV-2 and can detect all Ig subclasses (IgG, IgM, and IgA).  The quantity of SARS-CoV2 antibodies correlates directly with relative light units (RLU), which is converted to Index Values with a measuring interval of 0.05 ->10 index, where values below 1 are reported as nonreactive and those ≥1.0 are reported as reactive, as validated by the manufacturer by clinical correlation. The method was independently validated by Public Health England and has a reported sensitivity and specificity of 98.1% (95% CI 96.6 – 99.1) and 99.9% (95% CI 99.4 – 100) respectively. Samples were processed in the Biochemistry laboratory at CUH following the SOP as stated by the manufacturer in their Instruction for Use (IFU) after a local verification using guidance from The Royal College of Pathologists (
      Royal College of Pathologists
      Verification and Validation Methodology and Sample Sets for Evaluation of Assays for SARS-CoV-2 (COVID-19).
      ).
      As previously described, the RT-PCR assay used at CUH designates a cycle threshold (Ct) of ≤36 to correspond to a positive result (
      • Rivett L
      • Sridhar S
      • Sparkes D
      • Routledge M
      • Jones NK
      • Forrest S
      • et al.
      Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.
      ).

      Statistical analysis

      Seroprevalence is reported as a percentage ([proportion with antibodies/number tested] x 100). Logistic regression was used for univariable and multivariable analyses of seroprevalence comparisons. The Wilcoxon rank-sum test was used for comparison of median Ct values. Data were analysed using Stata v14.2 (StataCorp, College Station, Texas).

      Results

      Baseline information

      The CUH staff serology screening clinic was operational between 10th June and the 7th of August 2020. A total of 8,376 (73%) staff attended the clinic for SARS-CoV-2 serology; 5,697/8,376 (68%) of these consented to be enrolled in the study (Figure 2). 1,700/5,967 (28·5%) of study participants reported that they had worked in a designated COVID-19 area within the CUH structure during the peak of the epidemic between February and June 2020. The median age of participants was 38 years (range 17-83 years) and 22·7% (1,293/5,697) were male (Table 1). A total of 22 staff required hospital admission for COVID-19. No CUH staff members died.
      Table 1Baseline demographics
      Baseline variableMaleFemale
      n (%)1,293 (22.7)4,404 (77.3)
      Age (median [IQR])38 (30 – 49)38 (29 – 49)
      Age bracket
      16 – 24 years66360
      25 – 34 years4511427
      35 – 44 years3361035
      45 – 54 years250919
      55 – 64 years166555
      65 – 74 years2174
      75 + years34
      COVID working (n, %)493 (38.1)1,291 (29.3)
      Ethnicity
      White (n, %)887 (68.6)3,580 (81.3)
      BAME (all) (n, %)382 (29.5)752 (17.1)
      Asian (n, %)276 (21.4)495 (11.2)
      Black (n, %)30 (2.3)90 (2.0)
      Chinese (n, %)21 (1.6)57 (1.3)
      Mixed (n, %)21 (1.6)47 (1.1)
      Other (n, %)34 (2.6)63 (1.4)
      Not stated (n, %)24 (1.9)72 (1.6)

      Seroprevalence

      The overall seroprevalence of total SARS-CoV-2 antibodies amongst all staff in this study was 7·2% (410/5,698). Amongst those reporting having worked in a dedicated COVID-19 area between February and June 2020, the seroprevalence increased to 9·5% (169/1,784; Table 2). Conversely, the comparable seroprevalence in those reporting they had never worked in COVID-19 area was 6·2% (241/3,913; p<0·0001). The prevalence of seropositivity in male staff (8·0%; 104/1293) was not significantly different (p=0·18) than that observed in female staff (6·95%; 306/4404). The risk of seropositivity decreased with age, with an odds ratio (OR) of 0·83 (95% CI 0·76 – 0·91) for every 10-year increase in age (p<0·0001).
      Table 2Odds ratio (OR) and adjusted odds ratio (aOR) for variables associated with seropositivity
      VariableSeropositivity n (%)Unadjusted OR (96% CI)p valueAdjusted OR (95% CI)p value
      No COVID working241/3913 (6.16)1-1-
      COVID working169/1784 (9.47)1.59 (1.30 – 1.96)<0.0011.50 (1.22 – 1.84)<0.001
      Female sex1-1-
      Male sex104/1293 (8.04)1.17 (0.93 – 1.47)0.181.10 (0.87 – 1.39)0.43
      Age-<0.001*-<0.001*
      Age 16-2447/456 (10.3)1-1-
      Age 25-34152/1878 (8.1)0.77 (0.54 – 1.08)0.130.72 (0.51 – 1.02)0.069
      Age 35-44102/1371 (7.4)0.70 (0.49 – 1.0)0.0540.69 (0.48 – 0.99)0.044
      Age 45-5471/1169 (6.1)0.56 (0.38 – 0.83)0.0030.57 (0.38 – 0.83)0.004
      Age 55-6432/721 (4.4)0.40 (0.25 – 0.64)<0.0010.44 (0.27 – 0.70)0.001
      Age 65-746/95 (6.3)0.59 (0.24 – 1.4)0.240.66 (0.27 – 1.59)0.34
      Age 75+0/7 (0)----
      Job role-0.0042*-0.098*
      Administrative19/412 (4.61)1-1-
      Nursing staff261 / 3471 (7.52)1.68 (1.04 – 2.71)0.0331.52 (0.94 – 2.46)0.088
      Junior doctor10/118 (8.47)1.92 (0.87 – 4.24)0.111.43 (0.64 – 3.23)0.39
      Consultant10/174 (5.75)1.26 (0.57 – 2.77)0.561.19 (0.53 – 2.68)0.42
      Healthcare assistant36/319 (11.29)2.63 (1.48 – 4.68)0.0012.06 (1.14 – 3.71)0.016
      Theatre staff3/24 (12.5)2.95 (0.81 – 10.78)0.102.40 (0.65 – 8.87)0.19
      Physiotherapist9/84 (10.71)2.48 (1.08 – 5.69)0.0321.82 (0.78 – 4.24)0.16
      Domestic and porter4/27 (14.81)3.60 (1.13 – 11.44)0.0303.45 (1.07 – 11.2)0.039
      Other58/1068 (5.43)1.19 (0.67 – 2.02)0.531.06 (0.62 – 1.80)0.85
      Ethnicity--<0.001*-<0.001*
      White275/4467 (6.16)1-1-
      Black22/120 (18.33)3.42 (2.12 – 5.52)<0.0013.42 (2.12 – 5.53)<0.001
      Asian85/771 (11.02)1.89 (1.46 – 2.44)<0.0011.69 (1.30 – 2.19)<0.001
      Chinese5/78 (6.41)1.04 (0.42 – 2.60)0.931.04 (0.42 – 2.60)0.94
      Mixed2/68 (2.94)0.46 (0.11 – 1.90)0.280.42 (0.10 – 1.71)0.23
      Other9/97 (9.28)1.56 (0.78 – 3.12)0.211.36 (0.68 – 2.74)0.38
      Not stated12/96 (12.5)2.18 (1.17 – 4.04)0.0132.10 (1.13 – 3.90)0.019
      aORs calculated using a multivariable model containing serostatus, age, sex, ethnicity, job role and COVID-working location.
      *p value for the likelihood ratio test for the overall effect of variable

      Occupation

      On univariate analysis, a number of HCW roles were associated with greater risk of the detection of SARS-CoV-2 antibodies. Nursing staff (OR 1·68 [95% CI 1·04 – 2·71]; p=0·033), healthcare assistants (HCAs) (OR 2·63 [95% CI 1·48 – 4·86]; p=0·001) physiotherapists (OR 2·48 [95% CI 1·08 – 5·69]; p=0·032) and porters and domestic staff (OR 3·60 [95% CI 1·13 – 11·44]; p=0·03) all displayed a higher risk compared to administrative staff (Table 2), who had the lowest seroprevalence at 4·6% (19/412). Security staff at CUH are employed by a third-party contractor and did not attend the staff serology testing clinic.

      Department

      Staff working specifically in the ICUs had a seroprevalence of 6·33% (10/158), and staff working specifically in the Emergency Department had a seroprevalence of 9·1% (9/99). However, neither of these staff groups had significantly different seropositivity using univariate analysis (p>0·1 in both groups) compared to non-ICU and non-Emergency Department staff respectively.

      Ethnicity

      We observed substantial heterogeneity in the proportion of seropositivity between self-reported ethnic groups (Table 2). Staff identifying as White had an overall seropositivity rate of 6·1%. In comparison, Asian staff (Indian/Pakistani/Bangladeshi/Other Asian) and Black staff (Black African/Black Caribbean/Other black) had a seroprevalence of 11·0% (85/771) and 18·3% (22/120), respectively. White staff were more likely to have reported symptoms than Asian or Black staff (29%, 28% and 19% respectively). Despite this, seroconversion following symptoms consistent with COVID-19 was significantly higher in Black staff (p=0·002) and in Asian staff (p<0·001) compared to white staff; 41% (9/22), 26·6% (54/203), and 14·1% (148/1052) of staff had SARS-CoV-2 antibodies after reporting consistent symptoms in Black, Asian and White staff, respectively. The proportion of staff reporting having worked in a COVID-19 area was 38·5%, 60·3% and 32·1% for Black, Asian, and White staff, respectively.

      Multivariable analyses

      After describing several variables associated with SARS-CoV-2 seropositivity in a univariate analysis we included these variables to assess the risk associated with age, sex, ethnicity, job role and COVID-working status in a multivariable model. Increasing age remained protective for seropositivity on multivariable analysis (aOR 0·85 per 10 years increase in age [95% CI 0·78 – 0·93]; p<0·001). The aOR of having detectable SARS-CoV-2 antibodies in those that reported working in COVID-19 areas was 1·50 (95% CI 1·22 – 1·84; p<0·0001). Nursing staff and physiotherapists were no longer significantly associated with seropositivity on multivariable analysis (Table 2, Figure 3). HCAs remained at a significantly higher risk of being seropositive (aOR 2·06 [95% CI 1·14 – 3·71 – 2·4]; p=0·016), as were domestic and portering staff (aOR 3·45 [95% CI 1·07 – 11·2]; p=0·039).
      Figure 3:
      Figure 3Adjusted odds ratio for SARS-CoV-2 seropositivity according to job role
      Ethnicity remained strongly associated with seropositivity (Table 2, Figure 4). The aORs in Asian and black staff in the multivariable model were 1·69 (95% CI 1·30 – 2·19; p<0·0001) and 3·42 (95% CI 2·12 – 5·53; p<0·0001), respectively (Table 2). There was no significant evidence that the effect of ethnicity was modified by COVID working location (p value of interaction 0·96), and we also observed a similar increase in risk associated with ethnicity when data were stratified by CUH COVID-19 working location. For Asian staff, the aOR for seroconversion was 1·59 (95% CI 1·09 – 2·32; p=0·016) for those working in COVID-19 areas compared to 1·76 (95% CI 1·21 – 2·55; p=0·003) for those not working in COVID-19 areas. For black staff the aOR for seroconversion when working in COVID-19 areas was 3·91 (95% CI 1·78 – 8·59; p=0·001), compared to 3·06 (95% CI 1·65 – 5·64; p<0·001) who reported working in a non-COVID-19 area.
      Figure 4:
      Figure 4Adjusted odds ratio for SARS-CoV-2 seropositivity according to ethnic group
      The aOR for seropositivity in staff self-reporting as BAME (as a binary variable compared to white staff in a separate multivariable model) was 1·65 (95% CI 1·32 – 2·07; p<0·0001) after controlling for age, sex, job role and COVID-19 working location. For staff self-reporting as BAME, the aOR for seroconversion was 1·59 (95% CI 1·13 – 2·23; p=0·007) for those working in COVID-19 areas and 1·68 (95% CI 1·23 – 2·39; p=0·001) for those who reported not working in a COVID-19 area during the epidemic.

      Symptoms

      Participants were asked about any symptoms consistent with COVID-19 since February 2020. Critically, seroprevalence was significantly higher in the group reporting symptoms (17·2%; 266/1,548) in comparison to those without symptoms (3·1%; 117/3827, p<0·0001). Almost 31% (126/410) of seropositive HCWs reported not having any symptoms consistent with COVID-19 since February 2020. After adjusting for age, sex, and ethnicity, the aOR of seropositivity was 6·97 (95% CI 5·54 – 8·78; p<0·0001) in the group who reported prior symptoms compared to those who did not. The loss of the sense of taste or smell was the strongest predictor of seropositivity on univariate analysis; however, only 44% (154/351) of those reporting the loss of taste or smell were seropositive (Table 3). In a multivariable logistic regression model containing all collected symptoms (Table 3), loss of sense of taste or smell (aOR 7·85 [95% CI 5·79 – 10·65], p<0·0001), myalgia (aOR 1·71 [95% CI 1·18 – 2·48], p<0·0005) and fever (aOR 1·44 [95% CI 1·02 – 2·04], p<0·038) were the only symptoms positively associated with seropositivity. Notably, reporting a sore throat at the time of symptoms was negatively associated with seropositivity (aOR 0·7 [95% CI 0·50 – 0·99], p=0·043) in the multivariable model.
      Table 3Unadjusted odds ratio (OR) and adjusted odds ratio (aOR) of SARS-CoV-2 seropositivity by reported symptoms
      UnivariableMultivariable
      SymptomNumber reporting symptoms n, (%)Antibody positiveAntibody negative% positiveORp valueORp value
      Loss of taste or smell351 (6.2)15419743.915.5 (12.2 – 19.9)<0.00110.70 (7.80 – 14.70)<0.001
      Myalgia807 (14.2)16664120.64.9 (4.0 – 6.1)<0.0011.71 (1.18 – 2.48)0.005
      Fever740 (13.0)14759319.94.4 (3.60 – 5.51)<0.0011.44 (1.02 – 2.04)0.038
      Cough874 (15.3)15472017.63.82 (3.10 – 4.73)<0.0011.33 (0.93 – 1.90)0.11
      Headache847 (14.9)15769018.54.13 (3.34 – 5.12)<0.0011.32 (0.91 – 1.91)0.14
      Nausea/vomiting/diarrhoea330 (5.8)6027018.23.19 (2.36 – 4.30)<0.0011.08 (0.73 – 1.58)0.71
      Nasal Discharge453 (8.0)7238115.92.74 (2.08 – 3.61)<0.0010.82 (0.57 – 1.17)0.27
      Shortness of breath494 (8.7)8540917.23.12 (2.41 – 4.04)<0.0010.76 (0.51 – 1.13)0.18
      Hoarse voice314 (5.5)4626814.72.37 (1.70 – 3.29)<0.0010.75 (0.50 – 1.15)0.19
      Wheeze285 (5.0)4623916.12.67 (1.91 – 3.72)<0.0010.74 (0.47 – 1.17)0.20
      Sore throat806 (14.2)11768914.52.66 (2.12 – 3.35)<0.0010.70 (0.50 – 0.99)0.043

      Seroconversion after positive SARS-CoV-2 PCR

      From 5,991 enrolled participants, 2,825 (47%) reported having had a SARS-CoV-2 PCR test between February 2020 and the time of blood sampling, primarily through the CUH HCW testing programme. Of these, 51 (2·05%) tested PCR positive for SARS-CoV-2 RNA, 47 had detectable SARS-CoV-2 antibodies, and four had no detectable SARS-CoV-2 antibodies. All serological samples in these cases were taken >21 days after positive PCR tests. The median SARS-CoV-2 PCR Ct value in those who seroconverted was 30 (IQR 24 – 34), in comparison to 36 (IQR 35·5 – 37) in those who did not seroconvert (p=0·006). The four staff who had previously tested SARS-CoV-2 PCR positive and were antibody negative all reported having symptoms consistent with COVID-19 infection at the time of PCR testing, although none reported the loss of taste or smell. Nine (18%) of the staff previously testing SARS-CoV-2 PCR positive, and who were antibody positive, were asymptomatic at the time of PCR testing.

      Discussion

      In this comprehensive assessment of factors associated with seropositivity for SARS-CoV-2 antibodies in HCWs at a large UK tertiary referral centre we were able to identify key at-risk occupational groups. Specifically, staff working in areas where patients with confirmed SARS-CoV-2 infection are cared for, those employed as HCA or domestic and portering staff, those of younger age, and those working in acute medicine or a medical sub-speciality were more likely to have SARS-CoV-2 antibodies. A reduced risk of SARS-CoV-2 seropositivity was associated with White ethnicity, being employed in an administrative role, and belonging to an older age group.
      We found that the seroprevalence of SARS-CoV-2 antibodies in staff working in non-COVID facing areas was slightly higher (6·16%) than in the general population in the East of England (5·0%) (
      • Ward H
      • Atchison C
      • Whitaker M
      • Ainslie KEC
      • Elliott J
      • Okell L
      • et al.
      SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic.
      ) and comparable to the national prevalence (6·0%) (
      • Ward H
      • Atchison C
      • Whitaker M
      • Ainslie KEC
      • Elliott J
      • Okell L
      • et al.
      SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic.
      ). This is in keeping with previous retrospective serological HCW studies reporting relatively low seroprevalences in Germany (1·6%) (
      • Korth J
      • Wilde B
      • Dolff S
      • Anastasiou OE
      • Krawczyk A
      • Jahn M
      • et al.
      SARS-CoV-2-specific antibody detection in healthcare workers in Germany with direct contact to COVID-19 patients.
      ), Wuhan (3·8%) (
      • Xu X
      • Sun J
      • Nie S
      • Li H
      • Kong Y
      • Liang M
      • et al.
      Seroprevalence of immunoglobulin M and G antibodies against SARS-CoV-2 in China.
      ) and Belgium (7·6%) (
      • Steensels D
      • Oris E
      • Coninx L
      • Nuyens D
      • Delforge ML
      • Vermeersch P
      • et al.
      Hospital-wide SARS-CoV-2 antibody screening in 3056 staff in a tertiary center in Belgium.
      ). Amongst Asian staff working at CUH the seroprevalence was also comparable to East of England data (10·5% vs 10·1%, respectively), as was the seroprevalence amongst Black staff at CUH compared to regional data (18% vs 15%, respectively) (
      • Ward H
      • Atchison C
      • Whitaker M
      • Ainslie KEC
      • Elliott J
      • Okell L
      • et al.
      SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic.
      ). Overall, we observed significantly higher seroprevalence in all BAME staff compared to White staff, and to a greater extent in Black and Asian staff specifically. These differences have been observed nationally and are not unique to HCWs. The finding that the increased risk associated with BAME staff was not influenced by COVID-19 area working (and independent of job role), as well as the ethnic differences in symptomatic seroconversion rates, demonstrates that the increased prevalence of antibodies in BAME HCWs cannot be accounted for by purely occupational factors.
      In staff who were previously SARS-CoV-2 PCR positive, 92% (47/51) had detectable antibodies. There was a significant difference in Ct values between those who did and did not seroconvert. A potential explanation for this difference is that higher viral loads may be required to generate a sustained antibody response (
      • Sun J
      • Tang X
      • Bai R
      • Liang C
      • Zeng L
      • Lin H
      • et al.
      The kinetics of viral load and antibodies to SARS-CoV-2.
      ). Alternatively, a false positive SARS-CoV-2 PCR result or the detection of viral nucleic acid without infectious virus would also explain a lack of seroconversion.
      Consistent with previous studies, we demonstrate that whilst reporting prior symptoms consistent with COVID-19 increased the chances of seropositivity, differentiating previous COVID-19 infection from other common respiratory tract infections based on symptoms alone is unreliable (
      • Eyre DW
      • Lumley SF
      • O'Donnell D
      • Campbell M
      • Sims E
      • Lawson E
      • et al.
      Differential occupational risks to healthcare workers from SARS-CoV-2 observed during a prospective observational study.
      ). specifically, the only symptoms that significantly predicted seropositivity on a multivariable logistic regression model were the loss of sense of taste or smell, myalgia and fever. Prior reporting of cough or shortness of breath were not good predictors of the presence of SARS-CoV-2 antibodies in a multivariable model. These data also reiterate previous findings that asymptomatic SARS-COV-2 infection amongst healthcare workers is common, with 31% of seropositive staff having never reported consistent symptoms, and 18% of PCR positive staff never having reported consistent symptoms. Our data highlight the importance of the contribution of the asymptomatically infected population to the spread of the disease(
      • Oran DP
      • Topol EJ.
      Prevalence of asymptomatic SARS-CoV-2 infection: a narrative review.
      ,
      • Yu X
      • Yang R.
      COVID-19 transmission through asymptomatic carriers is a challenge to containment.
      ). Consequently, asymptomatic screening of staff in healthcare settings became a major component of routine disease surveillance (
      • Rivett L
      • Sridhar S
      • Sparkes D
      • Routledge M
      • Jones NK
      • Forrest S
      • et al.
      Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.
      ,
      • Hall VJ
      • Foulkes S
      • Charlett A
      • Atti A
      • Monk EJM
      • Simmons R
      • et al.
      SARS-CoV-2 infection rates of antibody-positive compared with antibody-negative health-care workers in England: a large, multicentre, prospective cohort study (SIREN).
      ), and is likely to be of benefit in future waves associated with novel variants and in future pandemics.
      The development and widespread rollout of mRNA vaccines since this study was conducted has resulted in lower re-infection rates and symptomatic disease in HCWs in the UK, and elsewhere (
      • Hall VJ
      • Foulkes S
      • Saei A
      • Andrews N
      • Oguti B
      • Charlett A
      • et al.
      COVID-19 vaccine coverage in health-care workers in England and effectiveness of BNT162b2 mRNA vaccine against infection (SIREN): a prospective, multicentre, cohort study.
      ,
      • Malhotra S
      • Mani K
      • Lodha R
      • Bakhshi S
      • Mathur VP
      • Gupta P
      • et al.
      COVID-19 infection, and reinfection, and vaccine effectiveness against symptomatic infection among health care workers in the setting of omicron variant transmission in New Delhi, India.
      ). However, the understanding of HCW infection risk remains critical in the protection of HCWs to novel variants (and vaccine escape), as well as those unable to receive vaccination.
      We acknowledge several limitations to our study. Variables such as ethnicity, COVID-working location and job role were self-reported; however, we have no reason to think these variables were party to recall bias and it is unlikely to impact on the results to any large degree. The proportion of staff reporting being of Black ethnicity was relatively small, although the proportion of BAME staff is consistent with the wider NHS workforce, and our conclusions are therefore broadly generalisable. The terminology and designation of COVID-facing clinical areas was an evolving factor throughout the course of the epidemic and is likely to be variable between hospital trusts and regions, as will the re-distribution of workforces and workflows through hospitals. Additionally, there will have been heterogeneity in infection rates and admission pressures between different regions and between different hospitals within the same regions that may influence HCW exposure to infection differently. Consequently, this variation between practices may impact the specific risk factors assessed in this study to varying extents between different healthcare trusts. We were also unable to assess the use of PPE and adherence to PPE protocols in this study design. The selected assay may have reduced sensitivity in individuals who generated robust antibody responses to other SARS-COV-2 antigens or those producing low affinity antibodies during early disease. Similar considerations apply to other commercial assays (
      Public Health England
      Evaluation of Sensitivity and Specificity of Four Commercially Available SARS-CoV-2 Antibody Immunoassays.
      ), and a subsequent comparison demonstrated assay equivalence with the selected platform having higher accuracy (
      National S-C-SAEG.
      Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison.
      ), and an independently reported sensitivity and specificity of 98·1% (95% CI 96·6 – 99·1) and 99·1% (95% CI 99·4 – 100) respectively (
      National S-C-SAEG.
      Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison.
      ). We also note that symptom data were recorded retrospectively and may have been subject to recall bias.

      Conclusions

      Our study confirms prior findings and provides new information on the risk factors for SARS-COV-2 infection and antibody response in HCWs. We found that the occupational exposure to SARS-COV-2 is heterogenous across job roles, hospital department, and ethnicity. It is clear that HCWs who remain on the frontline of the COVID-19 pandemic require more protection from occupational exposure with accurate stratification of risk factors to develop mitigation strategies despite effective vaccines. The association with ethnic group is concerning and a deeper understanding of the societal and/or genetic factors predisposing the BAME population to SARS-COV-2 infection and seroconversion is needed.

      Declarations

      Ethical approval

      Ethical approval for this study was granted by the East of England – Cambridge Central Research Ethics Committee (IRAS ID: 220277).

      Availability of data and materials

      The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

      Funding

      SGB, IGG and MPW are funded by Wellcome Senior Fellowships (Grant ID 215515/Z/19/Z , 207498/Z/17/Z , 108070/Z/15/Z ). DJC and SL received funding for this work from Addenbrooke's Charitable Trust (Grant ID 900254 ). MET is supported by the Academy of Medical Sciences, the Health Foundation and the NIHR Cambridge Biomedical Research Centre. BW is funded by the National Institute for Health Research Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust.

      Authors’ Contributions

      DJC and SL contributed to study design, data collection, analysis, data interpretation, figures and tables, literature review and wrote the first draft of the manuscript. LW contributed to data collection and analysis and data interpretation. AS and MF contributed to study design, data collection, analysis and data interpretation. RB, KS, MPW, BW, DS, MJ, LR, MR, AC, KD, MM, AL, GG, OO, EW, OS, KT, RT, IH, DH, SH, SP, NK, KS, BG, NW and HS contributed to data collection and analysis and data interpretation. DDA and SS contributed to data analysis and interpretation and writing. JB, MET and GD contributed to data collection, analysis and data interpretation. IGG and SGB contributed to study design, data collection, analysis, data interpretation, figures and tables, literature review and contributed to the first draft of the manuscript. All authors reviewed and approved the final manuscript.

      Competing interests

      The authors declare that they have no competing interests

      Acknowledgements

      We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The authors also thank the Occupational Health Department at CUH for facilitating sample and data collection during the staff serology testing clinic.

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