For factors with multiple categories, the 15 most populous are presented and the remaining collated into other, which forms the reference group. except for Medical/Dental, where the trend was reversed (4.4% BAME versus 9.6% White). The median IMD decile for BAME staff was Aspn 4 (IQR: 2, 7) and for White staff was 7 (IQR: 4, 9). When restricting to medical and dental staff only, the median IMD decile for BAME staff (8; IQR: 4, 9) and for White staff (8; IQR: 6, 9) were similar. Table?2 displays the weighted regression estimates for the assessed demographic and socioeconomic risk factors for SARS-CoV-2 seroprevalence. BAME individuals had increased odds of SARS-CoV-2 seroprevalence (adjusted OR 1.99, 95%CI: 1.69, 2.34; em p /em 0.001) relative to White individuals. Critical care (adjusted OR 0.29, 95%CI: 0.13, 0.57; em p /em ?=?0.001) and theatre services (adjusted OR 0.29, 95%CI: 0.15, 0.49; em p /em 0.001) had decreased odds of SARS-CoV-2 seroprevalence. All medicine division clusters had increased odds of seroprevalence (adjusted OR range 1.72 to 3.35; all em p /em ??0.001). Healthcare science assistants (adjusted OR 0.35, 95%CI: 0.14, 0.73; em p /em ?=?0.01), healthcare science practitioners (adjusted OR 0.07, 95%CI: 0.01, 0.31; em p /em ?=?0.004), and specialty registrars (adjusted OR 0.62, 95%CI: 0.41, 0.91; em p /em ?=?0.019) had decreased odds of SARS-CoV-2 seroprevalence. Foundation year 2 doctors (adjusted OR 2.11, 95%CI: 1.40, 3.13; em p /em 0.001), healthcare assistants (adjusted OR 1.52, 95%CI: 1.17, 1.98; em p /em ?=?0.002), and nurses (adjusted OR 1.35, 95%CI: 1.08, 1.69; em p /em ?=?0.008) had increased odds of SARS-CoV-2 seroprevalence. Table 2 Demographic and socioeconomic factors associated with SARS-CoV-2 seroprevalence in HCWs and support staff. Both unadjusted and inverse probability weight-adjusted regression data are presented. For factors with multiple categories, the 15 most populous are presented and the remaining collated into other, which forms the reference group. Abbreviations: IPW C inverse probability weight; OR C odds ratio; CI C confidence interval; BAME C Black, Asian and Minority Ethnic. Unadjusted modelIPW-adjusted modelCharacteristicORa95% CIa em p /em -valueORa95% CIa em p /em -valueEthnicityWhiteBAME1.761.40, 2.21 0.0011.991.69, 2.34 0.001Undisclosed1.330.76, 2.180.31.160.81, 1.610.4GenderFemaleMale1.010.80, 1.28 0.90.960.81, 1.140.7Age31C40 =20 years1.060.53, 1.980.91.470.96, 2.200.071 =71 years0.860.05, MK-6892 4.470.90.740.17, 2.080.621C301.51.16, 1.950.0021.641.36, 1.99 0.00141C501.321.01, 1.740.0451.361.11, 1.670.00351C601.230.92, 1.640.21.451.17, 1.80 0.00161C701.310.85, 1.980.21.280.94, 1.730.1Neighbourhood deprivation1.010.97, 1.040.70.990.96, 1.020.5specialtyOtherCluster 1 C Neurosurgery, spines and pain0.890.50, 1.490.70.840.51, 1.320.5Cluster 2 C Trauma and orthopaedics1.460.91, 2.270.111.440.96, 2.100.067Cluster 30.960.56, 1.560.90.940.61, 1.410.8Critical care services0.310.11, 0.700.0130.290.13, 0.570.001Domestics0.940.53, 1.650.80.990.66, 1.48 0.9General surgery services0.620.31, 1.120.140.620.35, 1.030.081Imaging0.80.46, MK-6892 1.310.40.860.55, 1.280.5Maternity services0.670.31, 1.310.30.750.41, 1.290.3Medicine Cluster 11.751.24, 2.430.0011.721.30, 2.25 0.001Medicine Cluster 23.432.51, 4.67 0.0013.352.61, 4.30 0.001Medicine Cluster 43.012.05, 4.37 0.0012.842.07, 3.85 0.001Other bank services1.420.95, 2.070.0771.170.93, 1.460.2Pathology services0.510.22, 1.030.0830.530.28, 0.900.028Theatre services0.30.14, 0.57 0.0010.290.15, 0.49 0.001Therapies services1.210.72, 1.960.41.290.83, 1.930.2RoleOtherAssistant1.560.97, 2.440.0591.390.99, 1.930.051Clerical worker0.740.48, 1.120.20.810.59, 1.110.2Consultant0.860.52, 1.370.50.840.57, 1.230.4Foundation year 21.460.71, 2.800.32.111.40, 3.13 0.001Health care support worker2.281.27, 4.070.0052.792.05, 3.82 0.001Healthcare assistant1.571.12, 2.190.0081.521.17, 1.980.002Healthcare science assistant0.410.12, 1.060.10.350.14, 0.730.01Healthcare science practitioner0.090.01, 0.450.0220.070.01, 0.310.004Housekeeper1.670.97, 2.770.0541.521.01, 2.260.041Manager0.890.43, 1.690.70.860.48, 1.430.6Midwife0.760.28, 1.940.60.590.27, 1.210.2Officer0.850.51, 1.360.50.840.56, 1.220.4Porter2.111.04, 4.000.0291.571.01, 2.400.041Specialty registrar0.750.43, 1.250.30.620.41, 0.910.019Staff Nurse1.240.94, 1.640.141.351.08, 1.690.008 Open in a separate window aOR?=?Odds Ratio, CI?=?Confidence Interval. Studies in other centres have consistently shown higher rates of seroprevalence in HCWs C London (31.6%),3 Birmingham (24.4%),4 and Oxford (11%).5 As expected, working within areas of the hospital that provided care to acutely unwell patients was associated with higher rates of seroprevalence. However, in contrast to findings from a Danish study of HCWs,6 seroprevalence did not associate with wards designated for COVID-19 cohorting. As observed elsewhere,4 seroprevalence rates were low in the intensive care unit, where contamination risk was likely mitigated by enhanced PPE use and probable reduced infectivity of cases that had progressed to the characterised immune-mediated disease phase. We found the highest seroprevalence rates in wards with known nosocomial outbreaks. Supporting a role for MK-6892 transmitting between personnel organizations Further, administrative and clerical personnel MK-6892 (frequent connection with medical personnel) got higher seroprevalence than health care scientists (infrequent connection with medical personnel). Our data focus on the complicated interplay between natural, social, and financial elements that determine threat of infection throughout a.