Advertisement
Research Article| Volume 134, P97-107, April 2023

Download started.

Ok

Comparison of risk factors for SARS-CoV-2 infection among healthcare workers during Omicron and Delta dominance periods in Japan

Open AccessPublished:February 16, 2023DOI:https://doi.org/10.1016/j.jhin.2023.01.018

      Summary

      Background

      The risk factors for coronavirus disease (COVID-19) among healthcare workers (HCWs) might have changed since the emergence of the highly immune evasive Omicron variant.

      Aim

      To compare the risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among HCWs during the Delta- and Omicron-predominant periods.

      Methods

      Using data from repeated serosurveys among the staff of a medical research centre in Tokyo, two cohorts were established: Delta period cohort (N = 858) and Omicron period cohort (N = 652). The potential risk factors were assessed using a questionnaire. Acute/current or past SARS-CoV-2 infection was identified by polymerase chain reaction or anti-nucleocapsid antibody tests, respectively. Poisson regression was used to calculate the risk ratio (RR) of infection risk.

      Findings

      The risk of SARS-CoV-2 infection during the early Omicron-predominant period was 3.4-fold higher than during the Delta-predominant period. Neither working in a COVID-19-related department nor having a higher degree of occupational exposure to SARS-CoV-2 was associated with an increased infection risk during both periods. During the Omicron-predominant period, infection risk was higher among those who spent ≥30 min in closed spaces, crowded spaces, and close-contact settings without wearing mask (≥3 times versus never: RR: 6.62; 95% confidence interval: 3.01–14.58), whereas no such association was found during the Delta period.

      Conclusion

      Occupational exposure to COVID-19-related work was not associated with the risk of SARS-CoV-2 infection in the Delta or Omicron period, whereas high-risk behaviours were associated with an increased infection risk during the Omicron period.

      Keywords

      Introduction

      The Omicron variant of SARS-CoV-2 has been identified in 192 countries, and is the dominant lineage globally, representing 97% of variant cases reported at the end of May 2022 [

      GISAID. Tracking of variants. Available at: https://www.gisaid.org/hcov19-variants/ [last accessed June 2022].

      ]. This variant has caused an exponential growth in COVID-19 incidence [
      • McCallum M.
      • Czudnochowski N.
      • Rosen L.E.
      • Zepeda S.K.
      • Bowen J.E.
      • Walls A.C.
      • et al.
      Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement.
      ,

      Worldometer. COVID-19 coronavirus pandemic. Available at: https://www.worldometers.info/coronavirus [last accessed April 2022].

      , ]. Consequently, the immense demand for healthcare services poses an increased occupational risk for healthcare workers (HCWs) to be infected [
      • Fall A.
      • Eldesouki R.E.
      • Sachithanandham J.
      • Morris C.P.
      • Norton J.M.
      • Gaston D.C.
      • et al.
      The displacement of the SARS-CoV-2 variant Delta with Omicron: an investigation of hospital admissions and upper respiratory viral loads.
      ]. Therefore, identifying both occupational and non-occupational risk factors among HCWs during the circulation of this variant is crucial for controlling and minimizing the risk of infection [
      • Baker J.M.
      • Nelson K.N.
      • Overton E.
      • Lopman B.A.
      • Lash T.L.
      • Photakis M.
      • et al.
      Quantification of occupational and community risk factors for SARS-CoV-2 seropositivity among health care workers in a large U.S. health care system.
      ,
      • Lan F.Y.
      • Filler R.
      • Mathew S.
      • Buley J.
      • Iliaki E.
      • Bruno-Murtha L.A.
      • et al.
      Sociodemographic risk factors for coronavirus disease 2019 (COVID-19) infection among Massachusetts healthcare workers: a retrospective cohort study.
      ].
      Studies among HCWs during the early phase of the COVID-19 pandemic (before the Omicron variant) showed that engagement in the care of patients with COVID-19 and inappropriate use of personal protective equipment were major occupational risk factors, whereas close contact with patients with COVID-19 in daily life was among the important community risk factors [
      • Baker J.M.
      • Nelson K.N.
      • Overton E.
      • Lopman B.A.
      • Lash T.L.
      • Photakis M.
      • et al.
      Quantification of occupational and community risk factors for SARS-CoV-2 seropositivity among health care workers in a large U.S. health care system.
      ,
      • Galanis P.
      • Vraka I.
      • Fragkou D.
      • Bilali A.
      • Kaitelidou D.
      Seroprevalence of SARS-CoV-2 antibodies and associated factors in healthcare workers: a systematic review and meta-analysis.
      ,
      • Jacob J.T.
      • Baker J.M.
      • Fridkin S.K.
      • Lopman B.A.
      • Steinberg J.P.
      • Christenson R.H.
      • et al.
      Risk factors associated with SARS-CoV-2 seropositivity among US health care personnel.
      ,
      • Sikkema R.S.
      • Pas S.D.
      • Nieuwenhuijse D.F.
      • O’Toole Á.
      • Verweij J.
      • van der Linden A.
      • et al.
      COVID-19 in health-care workers in three hospitals in the south of the Netherlands: a cross-sectional study.
      ]. However, the relative importance of each risk factor might have changed over time, especially after the emergence of the Omicron variant with giant mutations in the post-vaccination era. Epidemiological evidence is lacking among HCWs, and risk factors vary over time during the circulation of different dominant variants [
      • Kumar S.
      • Thambiraja T.S.
      • Karuppanan K.
      • Subramaniam G.
      Omicron and Delta variant of SARS-CoV-2: a comparative computational study of spike protein.
      ]. Addressing this issue would form the basis for an effective strategy to protect HCWs against circulating variants.
      During the COVID-19 pandemic, using data from repeated serological surveys among staff of a national medical and research institution in Tokyo, we built two cohorts with exposure to Delta- and Omicron-dominant waves. The objective of the present study was to identify the risk factors for SARS-CoV-2 infection among HCWs in each period and to compare the relative importance of the risk factors in terms of their prevalence and impact.

      Methods

      Study setting

      The National Centre for Global Health and Medicine (NCGM) has played a leading role in the prevention and control of COVID-19 in Japan. Based on the specific mission of the NCGM on the COVID-19 control campaign, a project with repeated surveys, including the laboratory antibody test, was conducted to survey the antibodies among the NCGM staff [
      • Tanaka A.
      • Yamamoto S.
      • Miyo K.
      • Mizoue T.
      • Maeda K.
      • Sugiura W.
      • et al.
      Seroprevalence of antibodies against SARS-CoV-2 in a large national hospital and affiliated facility in Tokyo, Japan.
      ,
      • Yamamoto S.
      • Tanaka A.
      • Oshiro Y.
      • Ishii M.
      • Ishiwari H.
      • Konishi M.
      • et al.
      Seroprevalence of SARS-CoV-2 antibodies in a national hospital and affiliated facility after the second epidemic wave of Japan.
      ]. The progress of this project is shown in Figure 1, and the present study was conducted from July 2020 to March 2022 with five rounds of surveys. In each survey, we invited participants to donate venous blood samples and complete an online questionnaire. Venous blood samples were used for immunological testing, and serum separation was performed at the laboratory in the NCGM on the same day as sample collection. This study was approved by the NCGM ethics committee. Written informed consent was obtained from all participants.
      Figure 1
      Figure 1Timeline of antibody surveys, vaccine dates among National Center for Global Health and Medicine staff, and changes in the number of newly confirmed COVID-19 cases in Japan.
      NCGM also conducted a vaccination campaign for the staff since March 2021, which was before the third-round survey in June 2021, and most vaccinated NCGM staff received two doses before the third-round survey; whereas the booster shot was provided since December 2021, which was during the period of the fourth-round survey at the end of December 2021.

      Cohort definition

      In this study, we established two cohorts to investigate potential infection risk factors during the Omicron- and Delta-predominant periods. The selection and exclusion processes for the two cohorts are presented in Figure 2. A total of 2683 staff participated in the survey in June 2021 (baseline of cohort 1); of these, 895 attended the follow-up survey in December 2021. The Delta-predominant epidemic occurred between the two surveys. Of these, 37 participants who were positive on SARS-CoV-2 anti-nucleocapsid antibody test at baseline or in any previous survey or who reported a COVID-19 history at baseline were excluded, leaving 858 participants in cohort 1 (Supplementary Appendix). A total of 919 staff participated in the survey in December 2021 (baseline of cohort 2); of these, 704 attended the follow-up survey in March 2022. The Omicron-predominant epidemic occurred between the two surveys. Of these, 52 participants who were positive on SARS-CoV-2 anti-nucleocapsid antibody test at baseline or in any previous survey or who reported a COVID-19 history at baseline were excluded, leaving 652 participants in cohort 2.
      Figure 2
      Figure 2Flowchart of the study design and participant selection.

      Detection of SARS-CoV-2 infection

      The outcome was the incidence of SARS-CoV-2 infection, which was defined as positive on anti-nucleocapsid antibody test at the end of each period or on polymerase chain reaction (PCR) or antigen test during each period. For serological tests, we qualitatively measured IgG (Abbott Architect) and total antibodies (Roche Elecsys Anti-SARS-CoV-2) against the nucleocapsid protein. Seropositivity was defined as the positive detection of IgG or total antibodies according to the manufacturers' instructions (positive IgG threshold: ≥1.4 (S/C); total antibody positive threshold: ≥1.0 (Col)) [
      • Yamamoto S.
      • Fukunaga A.
      • Tanaka A.
      • Takeuchi J.S.
      • Inoue Y.
      • Kimura M.
      • et al.
      Association between reactogenicity and SARS-CoV-2 antibodies after the second dose of the BNT162b2 COVID-19 vaccine.
      ]. The sensitivity was 100% for the Abbott assay and 99.5% for the Roche assay [
      • Bryan A.
      • Pepper G.
      • Wener M.H.
      • Fink S.L.
      • Morishima C.
      • Chaudhary A.
      • et al.
      Performance characteristics of the Abbott Architect SARS-CoV-2 IgG assay and seroprevalence in Boise, Idaho.
      ,
      • Muench P.
      • Jochum S.
      • Wenderoth V.
      • Ofenloch-Haehnle B.
      • Hombach M.
      • Strobl M.
      • et al.
      Development and validation of the Elecsys Anti-SARS-CoV-2 immunoassay as a highly specific tool for determining past exposure to SARS-CoV-2.
      ]. Data on the history of PCR or antigen positivity were retrieved from the COVID-19 staff registry in the Infection Control Office at NCGM. In NCGM, PCR test for the staff has been done only for those who had symptoms suggestive of COVID-19 or who had close contact with patients with COVID-19, while some staff (mainly hospital staff) have participated, on a voluntary basis, in a regular self-monitoring programme using an antibody test kit from January 2022 onward (cohort 2 period).

      Covariates

      Risk factors evaluated in this investigation included demographic characteristics (sex and age), occupational factors (job category, affiliated department, and degree of possible exposure to SARS-CoV-2), close contact with COVID-19 patients in the past two months (contact in the hospital, contact at home, and contact both in the hospital and at home), adherence to infection prevention practices, high-risk behaviours in the past two months (the frequency of spending ≥30 min in the closed spaces, crowded spaces, and close-contact setting (3Cs) and having dinner in a group of ≥5 people for >1 h), and vaccination status. The main clinical symptoms indicative of COVID-19 within the last two months were assessed (common cold-like symptoms lasting ≥4 days, high fever, severe fatigue, dyspnoea, and loss of sense of taste or smell). Follow-up data were used for all of the above variables, except vaccination status, for which baseline data were used.
      Age was classified into three groups: <30, 30–39, and ≥40 years. Job was classified into three groups: doctors, nurses, and others (allied health professionals, administrative, technical, or research staff). The affiliated departments were dichotomized into COVID-19- and non-COVID-19-related department. The degree of possible exposure to SARS-CoV-2 was classified into three categories: low (not engaged in COVID-19-related work), moderate (engaged in COVID-19-related work without heavy exposure to SARS-CoV-2), and high (heavily exposed to SARS-CoV-2). Adherence to infection prevention practices was classified as low, moderate, and high according to the four questions we asked: ‘keeping social distance’, ‘wearing masks’, ‘not touching eyes, noses, and mouths’, and ‘washing or sanitizing hands’. Each question has four response options: ‘not at all’ and ‘rarely’, ‘often’, and ‘always’. Zero was assigned to ‘not at all’ and ‘rarely’, 1 to ‘often’, and 2 to ‘always’. Total score was summarized ranging from 0 to 8. Adherence to infection prevention practices was classified as low (0–4), moderate (5–6), and high (7–8) according to the total score. The frequency of spending ≥30 min in the 3Cs without masks was classified into three groups: never, 1–2 times, and ≥3 times, and the frequency of having dinner in a group of ≥5 people for >1 h was classified into two groups: never and ≥1 time. The vaccination status was classified into two groups in cohort 1: none and first/second dose, and four groups in cohort 2: none, first/second dose, booster before the Omicron pandemic, and booster after the Omicron pandemic.

      Statistical analysis

      Participant characteristics and infection cases (%) were presented as the number of categorical variables in each cohort. In risk factor analysis, we estimated risk ratio (RR) with a 95% confidence interval (CI) using robust Poisson regression models. Model 1 was adjusted for sex and age. Model 2 was fully adjusted for all the above-mentioned covariates except clinical symptoms. Sensitivity analyses were also conducted in both cohorts by excluding patients who received a booster dose before each pandemic during the follow-up period. All reported P-values were two-tailed, and the level of significance was set at P < 0.05. All statistical analyses were performed with the Stata 16 software (Stata Corp LLP, College Station, TX, USA).

      Ethical approval

      Written informed consent was obtained from all participants and the study procedure was approved by the NCGM Ethics Committee (approval number: NCGM-G-003598).

      Results

      Baseline characteristics

      In cohort 1, the mean age (standard deviation) was 33 (9) years, 77.0% were female, 67.9% were nurses, 18.1% worked in a COVID-related department, and 29.0% were involved in high degree of possible exposure to SARS-CoV-2 (Table I). Similar demographic characteristics were observed in cohort 2. The proportion of those who had close contact with COVID-19 patients in the hospital was 3.4% in cohort 1 and 2.1% in cohort 2, whereas those who had contact at home were 0.8% and 1.8% in cohorts 1 and 2, respectively. High-risk behaviours decreased from cohort 1 to cohort 2: the proportion of spending ≥30 min in the 3Cs without masks (≥1 time) decreased from 30.0% to 15.5%, and the proportion of having dinner in a group of ≥5 people for >1 h decreased from 21.8% to 8.0%. Regarding the main clinical symptoms, the proportion of high fever and severe fatigue decreased from cohort 1 to cohort 2 (high fever: 7.0% versus 4.6%; and severe fatigue: 7.8% versus 6.4%), whereas other symptoms were similar in both cohort 1 and cohort 2. The vaccination coverage (defined as at least one dose of the COVID-19 vaccine) increased from 93.2% in cohort 1 to 99.1% in cohort 2.
      Table IDemographic characteristics in cohorts 1 and 2
      CharacteristicsCohort 1 (June 2021 to December 2021)Cohort 2 (December 2021 to March 2022)
      No.%No.%
      Study sample858100.0652100.0
      Sex
       Men19723.013220.2
       Women66177.052079.8
      Age range (years)
       <3044051.331448.2
       30–3923126.917627.0
       ≥4018721.816224.8
      Job category
       Doctor11413.36710.3
       Nurse58367.944768.6
       Others
      Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, etc.
      16118.813821.2
      Affiliated department
       Non-COVID-1970381.953882.5
       COVID-1915518.111417.5
      Degree of possible exposure to SARS-CoV-2
       Low39445.927141.6
       Moderate21525.117426.7
       High24929.020731.7
      Close contact with COVID-19 patients
       No close contact82295.862595.9
       Contact in the hospital
      Close contact with COVID-19 patients or coworkers.
      293.4142.1
       Contact at home
      Close contact with COVID-19 family members or cohabitants.
      70.8121.8
       Contact in the hospital and at home00.010.2
      Score of adherences to infection-prevention practices in the past one month
       Low14316.710516.1
       Moderate40547.228443.6
       High31036.126340.3
      High-risk behaviours in the past two months
       Spending ≥30 min in the 3Cs without mask
        Never60170.055184.5
        1–2 times15918.58312.7
        ≥3 times9811.4182.8
      Having dinner in a group of ≥5 people for >1 h
       Never67178.260092.0
       ≥1 time18721.8528.0
      Major clinical symptoms indicative of COVID-19
       Common cold-like symptom lasting ≥4 days
        No76889.558890.2
        Yes9010.5649.8
      High fever
       No79893.062295.4
       Yes607.0304.6
      Severe fatigue
       No79192.261093.6
       Yes677.8426.4
      Dyspnoea
       No84097.963597.4
       Yes182.1172.6
      Loss of sense of taste or smell
       No84598.564598.9
       Yes131.571.1
      Vaccination status
       None586.860.9
       One or two doses80093.2213.2
       Booster before Omicron pandemicNANA50377.1
       Booster after the Omicron pandemicNANA12218.7
      3Cs, closed spaces, crowded places, and close-contact settings; NA, not applicable.
      a Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, etc.
      b Close contact with COVID-19 patients or coworkers.
      c Close contact with COVID-19 family members or cohabitants.

      SARS-CoV-2 infection

      During six months of follow-up in cohort 1 and three months in cohort 2, 2.2% and 7.4% of the staff were infected, respectively (Table II). No repeated infections were reported in both cohorts. Compared to cohort 1, the infection rate in cohort 2 increased, especially among women, nurses, workers in non-COVID-19-related departments, and those with low and moderate degrees of exposure to SARS-CoV-2. Regarding close contact, the infection rate among those who had close contact with COVID-19 patients in the hospital increased from 3.4% in cohort 1 to 21.4% in cohort 2. In contrast, the infection rate among those who had close contact with COVID-19 patients at home was similar in cohort 1 (42.8%) and cohort 2 (41.7%). All infected staff who had close contact in the hospital were nurses in the non-COVID-related department in both cohort 1 and cohort 2. Additionally, all these infections were related to close contact with patients with COVID-19. Regarding high-risk behaviours, increased infection risks were observed among individuals who spent ≥30 min in the 3Cs without masks (1–2 times: from 1.9% in cohort 1 to 9.6% in cohort 2; ≥3 times: from 2.4% in cohort 1 to 38.9% in cohort 2), and those who had dinner in a group of ≥5 people for >1 h (from 2.7% in cohort 1 to 11.5% in cohort 2).
      Table IIRobust Poisson regression models to estimate the association between risk factors and the SARS-CoV-2 infections
      CharacteristicsCohort 1 (June 2021 to December 2021)Cohort 2 (December 2021 to March 2022)
      Infection No. (%)RR (95% CI)Infection No. (%)RR (95% CI)
      Model 1
      Sex and age were adjusted in model 1.
      Model 2
      Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      Model 1
      Sex and age were adjusted in model 1.
      Model 2
      Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      Sex
       Men9 (4.6)Ref.Ref.7 (5.3)Ref.Ref.
       Women10 (1.5)0.30 (0.12–0.76)0.39 (0.14–1.07)41 (7.9)1.50 (0.67–3.36)0.60 (0.19–1.90)
      Age range (years)
       <3011 (2.5)Ref.Ref.22 (7.0)Ref.Ref.
       30–395 (2.2)0.74 (0.26–2.11)0.66 (0.21–2.07)16 (9.1)1.35 (0.72–2.51)1.17 (0.56–2.45)
       ≥403 (1.6)0.52 (0.14–1.94)0.23 (0.05–1.27)10 (6.2)0.94 (0.44–1.99)0.96 (0.45–2.02)
      Job category
       Doctor4 (3.5)0.79 (0.21–2.21)0.83 (0.24–2.84)1 (1.5)0.55 (0.06–5.25)0.64 (0.08–5.22)
       Nurse9 (1.5)0.65 (0.24–1.80)0.29 (0.07–1.10)43 (9.6)4.87 (1.48–16.04)3.81 (1.07–13.64)
       Others
      Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, and so on.
      6 (3.7)Ref.Ref.4 (2.9)Ref.Ref.
      Affiliated department
       Non-COVID-1914 (2.0)Ref.Ref.40 (7.4)Ref.Ref.
       COVID-195 (3.2)1.69 (0.64–4.46)1.96 (0.58–6.60)8 (7.0)0.91 (0.44–1.88)0.90 (0.41–1.96)
      Degree of possible exposure to SARS-CoV-2
       Low8 (2.0)Ref.Ref.25 (9.2)Ref.Ref.
       Moderate5 (2.3)1.04 (0.32–3.41)1.04 (0.31–3.55)14 (8.1)0.90 (0.48–1.70)0.97 (0.49–1.91)
       High6 (2.4)0.89 (0.31–2.58)0.57 (0.23–1.43)9 (4.4)0.49 (0.23–1.03)0.61 (0.29–1.28)
      Close contact with COVID-19 patients
       No close contact15 (1.8)Ref.Ref.39 (6.2)Ref.Ref.
       Contact in the hospital
      Close contact with COVID-19 patients or coworkers.
      1 (3.4)2.45 (0.31–19.14)4.35 (0.44–42.68)3 (21.4)3.31 (1.17–9.37)3.35 (1.09–10.31)
       Contact at home
      Close contact with COVID-19 family members or cohabitants.
      3 (42.8)51.70 (16.39–77.49)24.65 (7.84–163.09)5 (41.7)7.27 (3.34–15.83)7.53 (2.90–19.56)
       Contact in the hospital and at home0 (0.0)NANA1 (100.0)24.16 (9.50–61.45)7.79 (1.92–31.68)
      Score of adherences to infection prevention practices in the past one month
       Low3 (2.1)Ref.Ref.10 (9.5)Ref.Ref.
       Moderate8 (2.0)1.03 (0.28–3.88)0.90 (0.23–3.53)22 (7.7)0.78 (0.38–1.60)0.97 (0.46–2.06)
       High8 (2.6)1.35 (0.36–5.15)1.12 (0.20–6.22)16 (6.1)0.62 (0.28–1.34)0.78 (0.33–1.88)
      High-risk behaviours in the past two months
       Spending ≥30 min in the 3Cs without mask
        Never14 (2.3)Ref.Ref.33 (6.0)Ref.Ref.
        1–2 times3 (1.9)0.68 (0.20–2.36)0.47 (0.13–1.68)8 (9.6)1.65 (0.80–3.42)1.96 (0.96–3.99)
        ≥3 times2 (2.0)0.87 (0.21–3.66)0.85 (0.20–3.65)7 (38.9)6.19 (3.13–12.24)6.62 (3.01–14.58)
      Having dinner in a group of ≥5 people for >1 h
       Never14 (2.1)Ref.Ref.42 (7.0)Ref.Ref.
       ≥1 time5 (2.7)1.05 (0.34–3.22)1.12 (0.31–4.01)6 (11.5)1.70 (0.75–3.82)0.88 (0.34–2.33)
      Major clinical symptoms indicative of COVID-19
       Common cold-like symptom lasting ≥4 days
        No11 (1.4)Ref.Ref.18 (3.1)Ref.Ref.
        Yes8 (8.9)6.36 (2.52–16.09)5.84 (2.49–13.73)30 (46.9)15.12 (8.87–25.80)16.08 (8.90–29.06)
      High fever
       No14 (1.8)Ref.Ref.36 (5.8)Ref.Ref.
       Yes5 (8.3)4.55 (1.67–12.45)5.34 (1.90–15.03)12 (40.0)6.97 (4.06–11.96)5.38 (2.81–10.28)
      Severe fatigue
       No13 (1.6)Ref.Ref.30 (4.9)Ref.Ref.
       Yes6 (9.0)5.40 (2.10–13.86)5.27 (2.04–13.60)18 (42.9)8.80 (5.39–14.38)8.83 (4.99–15.64)
      Dyspnoea
       No14 (1.7)Ref.Ref.40 (6.3)Ref.Ref.
       Yes5 (27.8)18.54 (7.58–45.36)19.69 (5.76–67.37)8 (47.1)7.92 (4.23–14.83)7.45 (3.62–15.36)
      Loss of sense of taste or smell
       No13 (1.5)Ref.Ref.43 (6.7)Ref.Ref.
       Yes6 (46.2)31.22 (14.73–66.15)39.72 (14.09–111.99)5 (71.4)11.55 (6.66–20.03)7.09 (3.49–14.41)
      Vaccination status
       None1 (1.7)0.87 (0.11–6.68)1.41 (0.15–13.16)1 (16.7)0.78 (0.11–5.53)0.85 (0.18–4.06)
       One or two doses18 (2.3)Ref.Ref.5 (23.8)Ref.Ref.
       Booster before Omicron pandemic NANANA34 (6.8)0.30 (0.13–0.70)0.57 (0.20–1.66)
       Booster after the Omicron pandemic NANANA8 (6.6)0.29 (0.11–0.79)0.65 (0.20–2.12)
      RR, risk ratio; CI, confidence interval; NA, not applicable; 3Cs, closed spaces, crowded places, and close-contact settings.
      a Sex and age were adjusted in model 1.
      b Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      c Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, and so on.
      d Close contact with COVID-19 patients or coworkers.
      e Close contact with COVID-19 family members or cohabitants.

      Risk factors of SARS-CoV-2 infection

      Table II shows the association between risk factors and risk of SARS-CoV-2 infection. In a fully adjusted model (model 2), compared with participants other than doctors and other job category, nurses were associated with a lower, albeit statistically non-significant, infection risk in cohort 1 (RR: 0.29; 95% CI: 0.07–1.10); but with a higher infection risk (RR: 3.81; 95% CI: 1.07–13.64) in cohort 2. Those who had close contact with COVID-19 cases in the hospital had a non-significantly higher infection risk in cohort 1 (RR: 4.35; 95% CI: 0.44–42.68), and this association became weaker in cohort 2 (RR: 3.35; 95% CI: 1.09–10.31). Close contact with COVID-19 cases at home was associated with a higher infection risk in cohort 1 (RR: 24.65; 95% CI: 7.84–163.09), but this association became weaker in cohort 2 (RR: 7.53; 95% CI: 2.90–19.56). Those who spent ≥30 min in the 3Cs without masks were associated with an increased infection risk in cohort 2 (≥3 times: RR: 6.19; 95% CI: 3.13–12.24) but a decreased infection risk in cohort 1 (≥3 times: RR 0.85; 95% CI: 0.20–3.65) although the decrease was not statistically significant. There was a suggestion of decreasing trend in the risk of infection with the increasing adherence to the infection prevention practice scores in cohort 2 (moderate: RR: 0.97; 95% CI: 0.46–2.06; high: RR: 0.78; 95% CI: 0.33–1.88) but not in cohort 1. Regarding clinical symptoms, compared with the results in cohort 1, associations in cohort 2 were stronger for common cold-like symptoms lasting ≥4 days (RR in cohort 1 versus cohort 2: 5.84 versus 16.08), and severe fatigue (RR in cohort 1 versus cohort 2: 5.27 versus 8.83); but weaker for dyspnoea (RR in cohort 1 versus cohort 2: 19.69 versus 7.45) and loss of sense of taste or smell (RR in cohort 1 versus cohort 2: 39.72 versus 7.09). In cohort 2, participants who received a booster shot were associated with a lower, albeit statistically non-significant, infection risk compared with those who received the one/two doses (booster shot before the Omicron pandemic: RR: 0.57; 95% CI: 0.20–1.66; booster shot after the Omicron pandemic: RR: 0.65; 95% CI: 0.20–2.12).
      Similar results were observed in cohort 1 after excluding 296 participants who received a booster dose during the follow-up period and in cohort 2 after excluding 28 participants who received a booster dose during the follow-up period Table III.
      Table IIISensitivity analysis of the association between risk factors and the SARS-CoV-2 infections
      CharacteristicsCohort 1 (June 2021 to December 2021)Cohort 2 (December 2021 to March 2022)
      Total no.Infection No. (%)RR (95% CI)Total no.Infection No. (%)RR (95% CI)
      Model 1
      Sex and age were adjusted in model 1.
      Model 2
      Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      Model 1
      Sex and age were adjusted in model 1.
      Model 2
      Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      Study sample56212 (2.2)53040 (7.6)
      Sex
       Men1435 (3.5)Ref.Ref.1134 (3.5)Ref.Ref.
       Women4197 (1.7)0.47 (0.14–1.58)0.38 (0.10–1.40)41736 (8.6)2.51 (0.91–6.88)1.03 (0.25–4.29)
      Age range (years)
       <302957 (2.4)Ref.Ref.22516 (17.1)Ref.Ref.
       30–391512 (1.3)0.52 (0.11–2.50)0.34 (0.07–1.76)15014 (9.3)1.43 (0.73–2.81)1.14 (0.53–2.45)
       ≥401163 (2.6)0.93 (0.22–3.90)0.36 (0.08–1.68)15510 (6.5)1.04 (0.48–2.24)0.97 (0.44–2.16)
      Job category
       Doctor812 (2.5)0.66 (0.11–3.96)0.58 (0.12–2.72)501 (2.0)2.54 (0.15–41.49)2.85 (0.23–35.30)
       Nurse3446 (1.7)0.80 (0.20–3.23)0.22 (0.03–1.57)36438 (10.4)14.92 (1.60–138.47)10.28 (1.12–94.54)
       Others
      Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, etc.
      1374 (2.9)Ref.Ref.1161 (0.9)Ref.Ref.
      Affiliated department
       Non-COVID-194819 (1.9)Ref.Ref.43733 (7.6)Ref.Ref.
       COVID-19813 (3.7)2.38 (0.70–8.12)6.68 (1.11–40.18)937 (7.5)0.98 (0.45–2.12)0.93 (0.41–2.14)
      Degree of possible exposure to SARS-CoV-2
       Low2546 (2.4)Ref.Ref.22122 (10.0)Ref.Ref.
       Moderate1423 (2.1)0.78 (0.17–3.60)0.84 (0.15–4.58)14711 (7.5)0.80 (0.40–1.61)0.88 (0.43–1.82)
       High1663 (1.8)0.63 (0.15–2.65)0.44 (0.16–1.18)1627 (4.3)0.47 (0.20–1.09)0.54 (0.25–1.16)
      Close contact with COVID-19 patients
       No close contact54210 (1.8)Ref.Ref.50431 (6.2)Ref.Ref.
       Contact in the hospital
      Close contact with COVID-19 patients or coworkers.
      160 (0.0)NANA123 (25.0)3.75 (1.35–10.43)4.35 (1.35–13.98)
       Contact at home
      Close contact with COVID-19 family members or cohabitants.
      42 (50.0)48.50 (11.95–196.90)172.14 (25.28–1171.96)135 (38.5)7.60 (3.56–16.25)2.92 (3.09–21.11)
       Contact in the hospital and at home00 (0.0)NANA11 (100.00)43.17 (11.67–159.69)2.92 (2.59–87.18)
      Score of adherences to infection-prevention practices within recent one month
       Low1011 (1.0)Ref.Ref.848 (9.5)Ref.Ref.
       Moderate2606 (2.3)2.43 (0.27–21.43)1.81 (0.14–24.06)23117 (7.4)0.71 (0.31–1.58)0.87 (0.34–2.24)
       High2015 (2.5)2.57 (0.38–23.18)2.92 (0.18–46.37)21515 (7.0)0.69 (0.30–1.64)0.86 (0.40–1.86)
      High-risk behaviors within recent two months
       Spending ≥30 min in the 3Cs without mask
        Never40110 (2.5)Ref.Ref.44427 (6.1)Ref.Ref.
        1–2 times1061 (0.9)0.33 (0.04–2.65)0.39 (0.04–3.62)716 (8.5)1.41 (0.62–3.24)1.79 (0.82–3.91)
      ≥3 times551 (1.8)0.71 (0.10–5.37)1.14 (0.10–12.55)157 (46.7)7.26 (3.71–14.21)9.02 (4.30–18.93)
      Having dinner in a group of ≥5 people for >1 h
       Never4549 (2.0)Ref.Ref.48835 (7.2)Ref.Ref.
       ≥1 time1083 (2.8)1.26 (0.29–5.56)1.02 (0.18–18.20)425 (11.9)1.71 (0.71–4.13)0.93 (0.32–2.70)
      Major clinical symptoms indicative of COVID-19
       Common cold-like symptom lasting ≥4 days
        No5015 (1.0)Ref.Ref.47615 (3.2)Ref.Ref.
        Yes617 (11.5)13.22 (4.12–42.37)11.13 (3.54–35.00)5425 (46.3)13.84 (7.77–24.64)14.03 (7.20–27.33)
      High fever
       No5228 (1.5)Ref.Ref.50731 (6.1)Ref.Ref.
       Yes404 (10.0)6.77 (2.07–22.11)7.78 (1.97–30.79)239 (39.1)6.09 (3.33–11.13)7.81 (3.58–17.06)
      Severe fatigue
       No5147 (1.3)Ref.Ref.49524 (4.8)Ref.Ref.
       Yes485 (45.5)8.53 (2.85–25.54)8.42 (2.08–34.11)3516 (45.7)9.27 (5.49–15.67)9.51 (4.74–19.06)
      Dyspnoea
       No5517 (1.3)Ref.Ref.51332 (6.2)Ref.Ref.
       Yes115 (50.0)37.91 (14.73–97.58)61.66 (9.74–390.19)178 (47.1)8.03 (4.14–15.59)61.66 (9.74–390.19)
      Loss of sense of taste or smell
       No5527 (1.3)Ref.Ref.52335 (6.7)Ref.Ref.
       Yes105 (50.0)43.83 (15.86–121.16)68.86 (6.73–704.87)75 (71.4)10.43 (5.90–18.43)8.61 (2.47–30.02)
      Vaccination status
       None211 (4.8)0.90 (0.12–6.69)1.74 (0.17–18.20)61 (16.7)0.75 (0.11–5.22)0.84 (0.15–4.59)
       One or two doses54111 (2.0)Ref.Ref.215 (23.8)Ref.Ref.
       Booster before Omicron pandemicNANANANA50334 (6.8)0.31 (0.14–0.72)0.72 (0.22–2.35)
      RR, risk ratio; CI, confidence interval; NA, not applicable; 3Cs, closed spaces, crowded places, and close-contact settings.
      a Sex and age were adjusted in model 1.
      b Sex, age, job category, affiliated department, occupational risk degree of SAR-CoV-2 infection, close contact with COVID-19 cases, high-risk behaviours, and vaccination status were adjusted in model 2.
      c Others include allied healthcare professionals, administrative staff, staff working in the laboratory and research institution, etc.
      d Close contact with COVID-19 patients or coworkers.
      e Close contact with COVID-19 family members or cohabitants.

      Discussion

      To our knowledge, this is the first study to directly compare risk factors of SARS-CoV-2 infection among HCWs in the Delta and Omicron periods in the same target population. Working in a COVID-19-related department and having a higher occupational risk of infection were not associated with an increased risk of infection during the spread of either variant. More than 40% of staff who lived with a household member with COVID-19 were infected during both periods, whereas the infection rate among staff who had close contact in the hospital was low during the Delta period (3.4%), but increased during the Omicron period (21.4%). Risky behaviours (positive) and adherence to infection prevention practices (inverse) were associated with infection risk only during the Omicron wave.
      The present finding of no increased risk of infection among the staff in COVID-19-related departments, or of being at higher risk of occupational exposure to SARS-CoV-2 during the Delta- and Omicron-predominant waves, contradicts some previous studies that report a higher infection risk among staff working in COVID-19-related departments [
      • Mo Y.
      • Eyre D.W.
      • Lumley S.F.
      • Walker T.M.
      • Shaw R.H.
      • O’Donnell D.
      • et al.
      Transmission of community- and hospital-acquired SARS-CoV-2 in hospital settings in the UK: a cohort study.
      ,
      • Elfström K.M.
      • Blomqvist J.
      • Nilsson P.
      • Hober S.
      • Pin E.
      • Månberg A.
      • et al.
      Differences in risk for SARS-CoV-2 infection among healthcare workers.
      ,
      • Cooper D.J.
      • Lear S.
      • Watson L.
      • Shaw A.
      • Ferris M.
      • Doffinger R.
      • et al.
      A prospective study of risk factors associated with seroprevalence of SARS-CoV-2 antibodies in healthcare workers at a large UK teaching hospital.
      ]. However, the findings of a few other studies are consistent with our findings, which include our previous observations among NCGM staff prior to the emergence of these variants, demonstrating that staff at high occupational risk would be safe as long as appropriate prevention measures were adopted [
      • Tanaka A.
      • Yamamoto S.
      • Miyo K.
      • Mizoue T.
      • Maeda K.
      • Sugiura W.
      • et al.
      Seroprevalence of antibodies against SARS-CoV-2 in a large national hospital and affiliated facility in Tokyo, Japan.
      ,
      • Yamamoto S.
      • Tanaka A.
      • Oshiro Y.
      • Ishii M.
      • Ishiwari H.
      • Konishi M.
      • et al.
      Seroprevalence of SARS-CoV-2 antibodies in a national hospital and affiliated facility after the second epidemic wave of Japan.
      ,
      • Erber J.
      • Kappler V.
      • Haller B.
      • Mijočević H.
      • Galhoz A.
      • Prazeres da Costa C.
      • et al.
      Infection control measures and prevalence of SARS-CoV-2 IgG among 4,554 University Hospital Employees, Munich, Germany.
      ]. In the NCGM, multiple infection control measures have been adopted to protect frontline HCWs since the early phase of the pandemic, including the provision of personal protective equipment, training programmes for taking care of COVID-19 patients, and management and support policies for COVID-19 patients [

      Manual for the prevention of nosocomial COVID-19 infection at NCGM V.5.3. (In Japanese.) Available at: https://www.ncgm.go.jp/covid19/pdf/20220615_COVID-19.pdf [last accessed July 2022].

      ]. The present finding lends further support to the effectiveness of these measures in the protection of frontline HCWs even after the emergence of the variants with high immune evasion properties.
      During the observation period, among a few staff members who had close contact with patients with COVID-19 in the hospital during both periods of Delta (3.4%, N = 29) and Omicron (2.1%, N = 14), the infection rate was much higher during Omicron (21.4%) than during the Delta variant (3.4%). This finding is consistent with the high transmission and evasion properties of the Omicron variant [
      • Karim S.S.A.
      • Karim Q.A.
      Omicron SARS-CoV-2 variant: a new chapter in the COVID-19 pandemic.
      ,
      • Abdullah F.
      • Myers J.
      • Basu D.
      • Tintinger G.
      • Ueckermann V.
      • Mathebula M.
      • et al.
      Decreased severity of disease during the first global Omicron variant covid-19 outbreak in a large hospital in Tshwane, South Africa.
      ,
      • Maslo C.
      • Friedland R.
      • Toubkin M.
      • Laubscher A.
      • Akaloo T.
      • Kama B.
      Characteristics and outcomes of hospitalized patients in South Africa during the COVID-19 Omicron wave compared with previous waves.
      ]. Regarding occupational background for the infected staff who had close contact in the hospital (cohort 1: N = 1; cohort 2: N = 3), they were all nurses working for non-COVID-related departments, suggesting that virus transmission in the hospital might have occurred through colleague or inpatient in general wards, but not in COVID-19 specific wards. In the NCGM, all inpatients were tested for SARS-CoV-2 infection at admission. Owing to the high false-negative rate of initial PCR assays for COVID-19 (12%), infection control measures must be strengthened in hospitals, including general wards, during the virus pandemic with high transmission potential to prevent nosocomial infections [
      • Pecoraro V.
      • Negro A.
      • Pirotti T.
      • Trenti T.
      Estimate false-negative RT–PCR rates for SARS-CoV-2. A systematic review and meta-analysis.
      ].
      During the follow-up period, close contact with a family member with COVID-19 was rare (Delta 0.8%, N = 7 versus Omicron 1.8%, N = 12); however, infection rates were very high (Delta 42.8% versus Omicron 41.7%). Our results were in line with existing data showing high household transmission rates of COVID-19 in the USA (29%), Canada (49%), and the UK (43%), which have been attributed to less mask use, low ventilation, and difficulty of isolation at home [
      • Lewis N.M.
      • Chu V.T.
      • Ye D.
      • Conners E.E.
      • Gharpure R.
      • Laws R.L.
      • et al.
      Household transmission of severe acute respiratory syndrome coronavirus-2 in the United States.
      ,
      • Bhatt M.
      • Plint A.C.
      • Tang K.
      • Malley R.
      • Huy A.P.
      • McGahern C.
      • et al.
      Household transmission of SARS-CoV-2 from unvaccinated asymptomatic and symptomatic household members with confirmed SARS-CoV-2 infection: an antibody-surveillance study.
      ,
      • Allen H.
      • Vusirikala A.
      • Flannagan J.
      • Twohig K.A.
      • Zaidi A.
      • Chudasama D.
      • et al.
      Household transmission of COVID-19 cases associated with SARS-CoV-2 delta variant (B.1.617.2): national case–control study.
      ,
      • Madewell Z.J.
      • Yang Y.
      • Longini Jr., I.M.
      • Halloran M.E.
      • Dean N.E.
      Household transmission of SARS-CoV-2: a systematic review and meta-analysis.
      ,
      • Tang L.
      • Liu M.
      • Ren B.
      • Chen J.
      • Liu X.
      • Wu X.
      • et al.
      Transmission in home environment associated with the second wave of COVID-19 pandemic in India.
      ]. In Japan, infections among children have markedly increased after the emergence of variants, especially Omicron, putting HCWs living with children at higher risk of infection than before [

      Ministry of Health, Labour and Welfare. Visualizing the data: information on COVID-19 infections. Available at: https://covid19.mhlw.go.jp/en/ [last accessed July 2022].

      ,
      • Chen F.
      • Tian Y.
      • Zhang L.
      • Shi Y.
      The role of children in household transmission of COVID-19: a systematic review and meta-analysis.
      ,
      • Yamamoto S.
      • Mizoue N.
      • Mizoue T.
      • Konishi M.
      • Horii K.
      • Sugiyama H.
      • et al.
      Living with school-age children and absence among staff of a tertiary hospital during the Omicron epidemic in Tokyo.
      ,
      • Cordery R.
      • Reeves L.
      • Zhou J.
      • Rowan A.
      • Watber P.
      • Rosadas C.
      • et al.
      Transmission of SARS-CoV-2 by children to contacts in schools and households: a prospective cohort and environmental sampling study in London.
      ]. The expansion of vaccine coverage among the younger generation is a priority issue to prevent HCWs living with school-age children against household infection.
      Spending long hours in a crowded location has been indicated as a high-risk situation for clustered infections [

      Cabinet Secretariat. COVID-19 information and resources. Available at: https://corona.go.jp/en/[last accessed August 2022].

      ]. In the present study, such high-risk behaviour was associated with an increased infection rate during the Omicron-predominant wave, but not during the Delta wave. Similarly, there was a suggestion to decrease the risk of infection by increasing adherence to infection prevention practices during Omicron, but not Delta, predominance. These results emphasize the importance of avoiding risky behaviours and adhering to standard infection prevention practices during pandemics of high immune evasive variants, even in the post-vaccination era.
      This study has several strengths. We identified the infection cases using two sources of diagnostic information: an in-house registry of COVID-19 patients and a serological survey. Serological data are useful for capturing all infections, including undiagnosed ones, and may be particularly important during the epidemic of the Omicron variant infection, which is characterized by asymptomatic or mild symptoms and is more likely to be left undiagnosed. Additionally, we used data from repeated serological surveys, which enabled us to make a direct comparison of risk factors for infection between different periods of variant dominance. Our study has some limitations. First, we were aware of the selective participation in cohort 2. According to the in-house registry, clustered infections among nurses occurred in non-COVID departments during the Omicron-predominant epidemic, suggesting the presence of staff-to-staff transmission; however, these nurses did not participate in the end survey of cohort 2. Due to this selective participation, the present study was not suitable for assessing the risk associated with close contact with staff members with COVID-19. Second, the exposure status could have changed during follow-up. For instance, some participants received a booster dose during follow-up, leading to misclassification of the vaccine status. However, the results remained unchanged after excluding those who received a booster dose during follow-up in both cohorts. Third, the number of infections was relatively small in cohort 2 (N = 48), making it difficult to detect a modest and statistically significant risk. Finally, this study was conducted at a single national medical institution designated for COVID-19; therefore, the findings may not be generalizable to other settings.
      In conclusion, there was a 3.4-fold increase in the risk of SARS-CoV-2 infection from the Delta- to Omicron-predominant period. Occupational factors were not associated with the risk of SARS-CoV-2 infection in both periods, whereas high-risk behaviour and poor adherence to infection prevention practices were associated with an increased risk of infection during the Omicron period. Greater emphasis should be placed on extra-hospital infection when planning infection control measures for HCWs during the epidemic of highly immune-evasive SARS-CoV-2 variants.

      Acknowledgements

      The authors thank H. Osawa and M. Shichishima for their contribution to data collection, and the staff of the Laboratory Testing Department for their contribution to the measurement of antibody testing results.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article.

      Conflict of interest statement

      None declared.

      Funding sources

      This work was supported by the NCGM COVID-19 Gift Fund (grant number 19K059) and the Japan Health Research Promotion Bureau Research Fund (grant number 2020-B-09). Abbott Japan and Roche Diagnostics provided reagents for the anti-nucleocapsid antibody assays.

      References

      1. GISAID. Tracking of variants. Available at: https://www.gisaid.org/hcov19-variants/ [last accessed June 2022].

        • McCallum M.
        • Czudnochowski N.
        • Rosen L.E.
        • Zepeda S.K.
        • Bowen J.E.
        • Walls A.C.
        • et al.
        Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement.
        Science. 2022; 375: 864-868
      2. Worldometer. COVID-19 coronavirus pandemic. Available at: https://www.worldometers.info/coronavirus [last accessed April 2022].

        • Latif A.A.
        • Mullen J.L.
        • Alkuzweny M.
        • Tsueng G.
        • Cano M.
        • Haag E.
        • et al.
        (the Center for Viral Systems Biology. Japan variant report. Available at:) ([last accessed May 2022])
        • Fall A.
        • Eldesouki R.E.
        • Sachithanandham J.
        • Morris C.P.
        • Norton J.M.
        • Gaston D.C.
        • et al.
        The displacement of the SARS-CoV-2 variant Delta with Omicron: an investigation of hospital admissions and upper respiratory viral loads.
        EBioMedicine. 2022; 79104008
        • Baker J.M.
        • Nelson K.N.
        • Overton E.
        • Lopman B.A.
        • Lash T.L.
        • Photakis M.
        • et al.
        Quantification of occupational and community risk factors for SARS-CoV-2 seropositivity among health care workers in a large U.S. health care system.
        Ann Intern Med. 2021; 174: 649-654
        • Lan F.Y.
        • Filler R.
        • Mathew S.
        • Buley J.
        • Iliaki E.
        • Bruno-Murtha L.A.
        • et al.
        Sociodemographic risk factors for coronavirus disease 2019 (COVID-19) infection among Massachusetts healthcare workers: a retrospective cohort study.
        Infect Control Hosp Epidemiol. 2021; 42: 1473-1478
        • Galanis P.
        • Vraka I.
        • Fragkou D.
        • Bilali A.
        • Kaitelidou D.
        Seroprevalence of SARS-CoV-2 antibodies and associated factors in healthcare workers: a systematic review and meta-analysis.
        J Hosp Infect. 2021; 108: 120-134
        • Jacob J.T.
        • Baker J.M.
        • Fridkin S.K.
        • Lopman B.A.
        • Steinberg J.P.
        • Christenson R.H.
        • et al.
        Risk factors associated with SARS-CoV-2 seropositivity among US health care personnel.
        JAMA Netw Open. 2021; 4e211283
        • Sikkema R.S.
        • Pas S.D.
        • Nieuwenhuijse D.F.
        • O’Toole Á.
        • Verweij J.
        • van der Linden A.
        • et al.
        COVID-19 in health-care workers in three hospitals in the south of the Netherlands: a cross-sectional study.
        Lancet Infect Dis. 2020; 20: 1273-1280
        • Kumar S.
        • Thambiraja T.S.
        • Karuppanan K.
        • Subramaniam G.
        Omicron and Delta variant of SARS-CoV-2: a comparative computational study of spike protein.
        J Med Virol. 2022; 94: 1641-1649
        • Tanaka A.
        • Yamamoto S.
        • Miyo K.
        • Mizoue T.
        • Maeda K.
        • Sugiura W.
        • et al.
        Seroprevalence of antibodies against SARS-CoV-2 in a large national hospital and affiliated facility in Tokyo, Japan.
        J Infect. 2021; 82 (e1–e3)
        • Yamamoto S.
        • Tanaka A.
        • Oshiro Y.
        • Ishii M.
        • Ishiwari H.
        • Konishi M.
        • et al.
        Seroprevalence of SARS-CoV-2 antibodies in a national hospital and affiliated facility after the second epidemic wave of Japan.
        J Infect. 2021; 83: 237-279
        • Yamamoto S.
        • Fukunaga A.
        • Tanaka A.
        • Takeuchi J.S.
        • Inoue Y.
        • Kimura M.
        • et al.
        Association between reactogenicity and SARS-CoV-2 antibodies after the second dose of the BNT162b2 COVID-19 vaccine.
        Vaccine. 2022; 40 (7): 1924
        • Bryan A.
        • Pepper G.
        • Wener M.H.
        • Fink S.L.
        • Morishima C.
        • Chaudhary A.
        • et al.
        Performance characteristics of the Abbott Architect SARS-CoV-2 IgG assay and seroprevalence in Boise, Idaho.
        J Clin Microbiol. 2020; 58e00941-20
        • Muench P.
        • Jochum S.
        • Wenderoth V.
        • Ofenloch-Haehnle B.
        • Hombach M.
        • Strobl M.
        • et al.
        Development and validation of the Elecsys Anti-SARS-CoV-2 immunoassay as a highly specific tool for determining past exposure to SARS-CoV-2.
        J Clin Microbiol. 2020; 58e01694-20
        • Mo Y.
        • Eyre D.W.
        • Lumley S.F.
        • Walker T.M.
        • Shaw R.H.
        • O’Donnell D.
        • et al.
        Transmission of community- and hospital-acquired SARS-CoV-2 in hospital settings in the UK: a cohort study.
        PLoS Med. 2021; 18e1003816
        • Elfström K.M.
        • Blomqvist J.
        • Nilsson P.
        • Hober S.
        • Pin E.
        • Månberg A.
        • et al.
        Differences in risk for SARS-CoV-2 infection among healthcare workers.
        Prev Med Rep. 2021; 24101518
        • Cooper D.J.
        • Lear S.
        • Watson L.
        • Shaw A.
        • Ferris M.
        • Doffinger R.
        • et al.
        A prospective study of risk factors associated with seroprevalence of SARS-CoV-2 antibodies in healthcare workers at a large UK teaching hospital.
        J Infect. 2022; 85: 557-564
        • Erber J.
        • Kappler V.
        • Haller B.
        • Mijočević H.
        • Galhoz A.
        • Prazeres da Costa C.
        • et al.
        Infection control measures and prevalence of SARS-CoV-2 IgG among 4,554 University Hospital Employees, Munich, Germany.
        Emerg Infect Dis. 2022; 28: 572-581
      3. Manual for the prevention of nosocomial COVID-19 infection at NCGM V.5.3. (In Japanese.) Available at: https://www.ncgm.go.jp/covid19/pdf/20220615_COVID-19.pdf [last accessed July 2022].

        • Karim S.S.A.
        • Karim Q.A.
        Omicron SARS-CoV-2 variant: a new chapter in the COVID-19 pandemic.
        Lancet. 2021; 398: 2126-2128
        • Abdullah F.
        • Myers J.
        • Basu D.
        • Tintinger G.
        • Ueckermann V.
        • Mathebula M.
        • et al.
        Decreased severity of disease during the first global Omicron variant covid-19 outbreak in a large hospital in Tshwane, South Africa.
        Int J Infect Dis. 2022; 116: 38-42
        • Maslo C.
        • Friedland R.
        • Toubkin M.
        • Laubscher A.
        • Akaloo T.
        • Kama B.
        Characteristics and outcomes of hospitalized patients in South Africa during the COVID-19 Omicron wave compared with previous waves.
        JAMA. 2022; 327: 583-584
        • Pecoraro V.
        • Negro A.
        • Pirotti T.
        • Trenti T.
        Estimate false-negative RT–PCR rates for SARS-CoV-2. A systematic review and meta-analysis.
        Eur J Clin Invest. 2022; 52e13706
        • Lewis N.M.
        • Chu V.T.
        • Ye D.
        • Conners E.E.
        • Gharpure R.
        • Laws R.L.
        • et al.
        Household transmission of severe acute respiratory syndrome coronavirus-2 in the United States.
        Clin Infect Dis. 2021; 73: 1805-1813
        • Bhatt M.
        • Plint A.C.
        • Tang K.
        • Malley R.
        • Huy A.P.
        • McGahern C.
        • et al.
        Household transmission of SARS-CoV-2 from unvaccinated asymptomatic and symptomatic household members with confirmed SARS-CoV-2 infection: an antibody-surveillance study.
        CMAJ Open. 2022; 10: E357-e366
        • Allen H.
        • Vusirikala A.
        • Flannagan J.
        • Twohig K.A.
        • Zaidi A.
        • Chudasama D.
        • et al.
        Household transmission of COVID-19 cases associated with SARS-CoV-2 delta variant (B.1.617.2): national case–control study.
        Lancet Reg Health Eur. 2022; 12100252
        • Madewell Z.J.
        • Yang Y.
        • Longini Jr., I.M.
        • Halloran M.E.
        • Dean N.E.
        Household transmission of SARS-CoV-2: a systematic review and meta-analysis.
        JAMA Netw Open. 2020; 3e2031756
        • Tang L.
        • Liu M.
        • Ren B.
        • Chen J.
        • Liu X.
        • Wu X.
        • et al.
        Transmission in home environment associated with the second wave of COVID-19 pandemic in India.
        Environ Res. 2022; 204111910
      4. Ministry of Health, Labour and Welfare. Visualizing the data: information on COVID-19 infections. Available at: https://covid19.mhlw.go.jp/en/ [last accessed July 2022].

        • Chen F.
        • Tian Y.
        • Zhang L.
        • Shi Y.
        The role of children in household transmission of COVID-19: a systematic review and meta-analysis.
        Int J Infect Dis. 2022; 122: 266-275
        • Yamamoto S.
        • Mizoue N.
        • Mizoue T.
        • Konishi M.
        • Horii K.
        • Sugiyama H.
        • et al.
        Living with school-age children and absence among staff of a tertiary hospital during the Omicron epidemic in Tokyo.
        J Hosp Infect. 2022; 130: 151-153
        • Cordery R.
        • Reeves L.
        • Zhou J.
        • Rowan A.
        • Watber P.
        • Rosadas C.
        • et al.
        Transmission of SARS-CoV-2 by children to contacts in schools and households: a prospective cohort and environmental sampling study in London.
        Lancet Microbe. 2022; 3: e814-e823
      5. Cabinet Secretariat. COVID-19 information and resources. Available at: https://corona.go.jp/en/[last accessed August 2022].