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SARS-CoV-2 seroprevalence in healthcare workers and risk factors

      Highlights

      • 47.5% of HCWs 47.5% had a history of COVID-19 symptoms.
      • 5.1% of HCW were seropositive.
      • Neither gender, sex, BMI, nor having children were associated with seropositive status.
      • Working in a COVID-19 unit was associated with positive RT-PCR test.
      • Smoking was associated with a lower seroprevalence among HCWs.

      Abstract

      Background

      Exposure of healthcare workers (HCW) to SARS-CoV-2 is a public health concern. Not only are HCWs particularly exposed to SARS-CoV-2, but their contamination can also weaken the healthcare system.

      Methods

      We analyzed exposure of French University Hospital HCWs to SARS-CoV-2 through history of positive RT-PCR test and SARS-CoV-2 seroprevalence. Potential risk factors, such as age, BMI, having children or not, working in a COVID-19 unit, or smoking were explored.

      Results

      From May to June 2020, among the 8960 employees of the University Hospital of Nancy, a serological test was performed in 4696 HCWs. The average (SD) age was 40.4 (11.4) years, and the sample included 3926 women (83.6%). Of the 4696 HCWs, 1050 were smokers (22.4%). Among them, 2231 HCWs had a history of COVID-19 symptoms and/or flu-like syndrome (47.5%) and 238 were seropositive (5.1%). Neither gender, sex, BMI, nor having children were associated with a history of positive RT-PCR test or seropositive status. Previous work in a COVID-19 unit was associated with a history of positive RT-PCR test (p = 0.045), but not with seroprevalence (p = 0.215). As expected, history of COVID-19 clinical manifestations was more frequent in HCWs with positive serology than in HCWs with negative serology (adjusted OR = 1.9, 95%CI [1.4–2.5], p < 0.001). Less expected, smoking was associated with a reduced risk of seropositivity among HCWs (adjusted OR = 0.6, 95%CI [0.4–0.9], p = 0.019).

      Conclusion

      HCW are patently exposed to SARS-CoV-2. Care to COVID-19 patients was not associated with a higher SARS-CoV-2 seroprevalence. Smoking appears here associated to a lower seroprevalence.

      Keywords

      Introduction

      Healthcare workers (HCW) play a crucial role in the first and current response to the SARS-CoV-2 pandemic. They have been identified as a group at high risk of infection due to frequent and close contacts with COVID-19 patients (World Health Organization, 2020). The protection of HCWs is critical for pandemic control, both at the individual level for the continuity of care and at the collective level to avoid transmission to their professional and personal contacts [
      • Kea B.
      • Johnson A.
      • Lin A.
      • Lapidus J.
      • Cook JN.
      • Choi C.
      • et al.
      An international survey of healthcare workers use of personal protective equipment during the early stages of the COVID-19 pandemic.
      ].
      The Northeast of France was particularly impacted by the first epidemic wave. The EpiCoV survey conducted in May 2020 revealed that seroprevalence was highest in Paris (9%), and the Haut-Rhin department (10.8%), located in the Northeast of France, was the epicenter of the start of the epidemic in France. Seroprevalence in the whole Northeast of France was from 6.7% in May 2020 [
      • Warszawski J.
      • Beaumont A.L.
      • Seng R.
      • de Lamballerie X.
      • Rahib D.
      • Lydié N.
      • et al.
      Prevalence of SARS-Cov-2 antibodies and living conditions: the French national random population-based EPICOV cohort.
      ].
      The aim of the present study was (i) to describe the seroprevalence of SARS-CoV-2 in HCWs at Nancy University Hospital, located in the Northeast of France; (ii) to determine whether sex, age, BMI, having children, working in a COVID-19 unit, or smoking can be considered as risk factors for SARS-CoV-2 infection.

      Methods

      Study design and participants

      This study was a single-centre seroprevalence survey of HCW from a single time point. On May 2020, the French Health Minister offered SARS-CoV-2 serological screening to all HCWs. At Nancy University Hospital, HCWs who underwent blood sampling and serological analyses were asked to fill in a form to collect epidemiological and clinical data. All HCWs who completed this form were included in the study (Fig. 1). HCWs included medical staff, nursing staff, and maintenance staff.
      Figure 1
      Figure 1Flow chart of the COVIDOSOIN study.
      Collected data included date of birth, gender, height, weight, smoking status (smoker/non-smoker), working in a COVID unit or not, having children or not (and age range), having been screened for SARS-CoV-2 (RT-PCR) or not (dates of screening and results when appropriate), flu-like syndrome (fever, body aches, headache), dry cough, gastrointestinal symptoms, loss of taste/smell, influenza vaccination (and if so, date).

      Serological assay

      Blood samples were collected in a dry SST tube with serum-PET separator. Due to the high number of samples collected over a short period of time, SARS-CoV-2 serologies were performed using various techniques.
      The BYOSYNEX® COVID-19 BSS technique is a flow lateral immunoassay for qualitative detection of anti-SARS-CoV-2 IgM and IgG. The target protein is the Receptor Binding Domain (RBD) of the Spike S protein. According to the manufacturer, the sensitivity for IgG is 100% and the specificity is 99.5%, and the sensitivity for IgM is 91.8% and the specificity is 99.2%.
      The MagLumi COVID-19® test is an automated method based on chemiluminescence immunoassay. This test allows a semi-quantitative detection of anti-SARS-CoV-2 IgM and IgG directed against the receptor binding domain of protein S and the nucleocapsid (N) proteins. According to the manufacturer, the threshold of positivity is 1 AU/mL for IgM and IgG. For IgG, the sensitivity is 100% and the specificity is 99.1% 15 days after onset of the first post-infection symptoms. For IgM, the sensitivity is 77.46% and the specificity is 99.6% 15 days after onset of the first post-infection symptoms.
      Euroimmun® SARS-CoV-2 ELISA is a test for quantitative detection of anti- SARS-CoV-2 IgA and IgG by Enzyme-Linked Immunosorbent Assay (ELISA). The Euroimmun® SARS-CoV-2 ELISA uses a recombinant S1 domain of protein S as target. Results are expressed as a ratio; a final ratio greater than 1.2 indicates positive serology. For IgG, the sensitivity is 90% and the specificity is 100% 10 days after onset of the first post-infection symptoms. For IgA, the sensitivity is 100% and the specificity is 92.5% 10 days after the first post-infection symptoms.
      Ambiguous results were confirmed by another method, according to a unique flow chart: Positive IgM detected by BYOSYNEX® or MagLumi® methods without IgG detection were confirmed or invalidated by complementary techniques. Doubtful IgA detected by the EUROIMMUN® method (ratio ≥0.8 to <1.1) were confirmed or invalidated by MagLumi® technique.

      Statistical analysis

      A stratified description of HCW characteristics was performed according to serological status (positive vs. negative serology) and according to history of RT-PCR test result (positive vs. negative RT-PCR test), using frequencies and percentages for qualitative variables and mean and standard deviation for quantitative variables. HCW characteristics were then compared between groups, using Student's t-test/ANOVA or Wilcoxon/Kruskal–Wallis tests for quantitative variables, and Chi-square or Fisher's exact tests for qualitative variables according to the condition of use.
      To identify factors associated with seropositivity or with history of RT-PCR positivity (i.e., at least one positive RT-PCR test among the RT-PCR tests performed), a bivariate logistic regression model was implemented for each HCW characteristic, entering seropositivity (or RT-PCR positivity) as the dependent variable, and HCW characteristic as the independent variable. A stepwise procedure was implemented to identify factors associated with seropositivity, with a significance level for entry (sle) set at 0.2 and a significance level for stay (sls) at 0.05. Results were reported as odd ratios (OR) and 95% confidence intervals (95% CI). P values were two-sided. Significance level was set at 0.05. Statistical analyses were performed using SAS 9.4 (SAS Institute, Inc., Cary, NC).

      Results

      Description of the cohort

      From May 25, 2020 to June 29, 2020, 4696 HCWs out of the 8960 employees of University Hospital of Nancy underwent a serological test. A total of 3926 women (83.6%) and 770 men (16.4%) were included; the average (SD) age was 40.4 (11.4) years. All participants completed the COVIDOSOIN form.
      Among the 2231 HCW with a history of COVID-19-associated clinical signs (47.5%), flue-like syndrome was predominant (30.3% of HCW).
      Overall, 79.2% of included HCWs had worked in a COVID-19 unit. A total of 238 study participants were seropositive (5.1%) and 131 participants had a history of at least one positive RT-PCR test (2.8%).
      In terms of epidemiological characteristics, 1050 participants were smokers (22.4%); 21.8% were overweight and 10.7% were obese; 64.2% of HCWs interviewed had one or more children (Table 1).
      Table 1Global description of the cohort.
      all
      N = 4696
      Age in 2020 (years)
       N4696
       Mean ± SD [95%CI]40.4 ± 11.4 [40.1; 40.7]
       Median (Q1 - Q3)40.0 (30.0–50.0)
       Min - Max18.0–71.0
      Gender
       Male770(16.4%)
       Female3926(83.6%)
      BMI
       NS296(6.3%)
       Underweight159(3.4%)
       Normal weight2714(57.8%)
       Overweight1023(21.8%)
       Obesity504(10.7%)
      Smoking
       NS197(4.2%)
       Yes1050(22.4%)
       No3449(73.4%)
      Children (all ages)
       NS19(0.4%)
       Yes3013(64.2%)
       No1664(35.4%)
      Children under 2 years old
       NS19(0.4%)
       Yes358(7.6%)
       No4319(92.0%)
      Children between 2 and < 5 years old
       NS19(0.4%)
       Yes539(11.5%)
       No4138(88.1%)
      Children between 5 and < 10 years old
       NS19(0.4%)
       Yes776(16.5%)
       No3901(83.1%)
      Children between 10 and < 15 years old
       NS19(0.4%)
       Yes917(19.5%)
       No3760(80.1%)
      Children aged 15 years and older
       NS19(0.4%)
       Yes616(13.1%)
       No4061(86.5%)
      Seropositivity
       Positive238(5.1%)
       Negative4458(94.9%)
      Working in a COVID-19 unit
       Yes3718(79.2%)
       No978(20.8%)
      RT-PCR Screening
       NS45(1.0%)
       Yes629(13.4%)
       No4022(85.6%)
      At least one positive RT-PCR test
       NS45(1.0%)
       Yes131(2.8%)
       No4520(96.3%)
      COVID-19 clinical manifestations (all)
      COVID-19 clinical manifestations: flu-like syndrome, dry cough, gastrointestinal symptoms, loss of taste/smell.
       NS55(1.2%)
       Yes2231(47.5%)
       No2410(51.3%)
      Influenza-like syndrome
       NS187(4.0%)
       Yes1421(30.3%)
       No3088(65.8%)
      Dry cough
       NS267(5.7%)
       Yes1155(24.6%)
       No3274(69.7%)
      Gastrointestinal symptoms
       NS316(6.7%)
       Yes967(20.6%)
       No3413(72.7%)
      Loss of taste/smell
       NS428(9.1%)
       Yes258(5.5%)
       No4010(85.4%)
      Flu vaccine
       NS4(0.1%)
       Yes1871(39.8%)
       No2821(60.1%)
      Flu diagnosis
       Yes86(1.8%)
       No4610(98.2%)
      NS: Not specified.
      a COVID-19 clinical manifestations: flu-like syndrome, dry cough, gastrointestinal symptoms, loss of taste/smell.

      Epidemiological and clinical factors associated with a history of positive RT-PCR test

      When comparing HCWs with or without any history of positive RT-PCR test, no difference was observed in terms of age, sex, BMI, smoking, and having children (S1). HCWs with a history of positive RT-PCR test were more likely to have a history of COVID-19-associated clinical signs symptoms compared with HCWs without any history of positive RT-PCR test, whether for all syndrome and symptoms combined (98.5% vs. 46.6%, p < 0.001) or each taken one by one (S2). HCWs with a history of positive RT-PCR test were more likely to have worked in a COVID-19 unit than those with no history of positive RT-PCR (86.3% vs. 79.0%, p = 0.045).

      Epidemiological and clinical factors associated with positive SARS-cov-2 serology

      HCWs with positive serology were more likely to have a history of positive RT-PCR test than HCWs with negative serology (28.2% versus 1.5%, p < 0.001). History of COVID-19-associated clinical signs was also more frequent in HCWs with positive serology than in HCWs with negative serology, whether for all clinical signs combined (63.9% versus 47.2%, p < 0.001) or for each taken separately (S2). Participants who had worked in a COVID-19 unit were equally likely to be seropositive than those who did not work in a COVID-19 unit (p = 0.215).
      Using a multivariate analysis, age, sex, BMI, and having children (regardless of their age) were not risk factors for SARS-COV-2 seropositivity, neither having worked in a COVID-19 unit (Table 2). Loss of smell or taste was a risk factor for SARS-CoV-2 seropositivity (adjusted OR = 4.2, 95%CI [2.6–6.7], p < 0.001).
      Table 2Factors associated with positive seropositivity status.
      NSeropositivityBivariate regressionMultivariate regression
      Only factors with a significant association at the 0.2 threshold in the bivariate model were included.
      p
      n%Odds ratio95%CI
      CI: Confidence interval - Lower bound - Upper bound.
      pOdds ratio95%CI
      CI: Confidence interval - Lower bound - Upper bound.
      Inf
      CI: Confidence interval - Lower bound - Upper bound.
      Sup
      CI: Confidence interval - Lower bound - Upper bound.
      Inf
      CI: Confidence interval - Lower bound - Upper bound.
      Sup
      CI: Confidence interval - Lower bound - Upper bound.
      Age in 20200.497
      <30 years923424.61
      30–39 years1068484.51.00.61.5
      40–49 years901535.91.30.92.0
      ≥50 years967485.01.10.71.7
      Sex0.989
      Male648324.91.00.71.5
      Female32111595.01
      BMI0.029
      Normal weight23921134.71
      Underweight14321.40.30.11.2
      Overweight884566.31.41.01.9
      Obesity440204.51.00.61.6
      Smoking0.0020.019
      Yes884273.10.50.40.80.60.40.9
      No29751645.511
      Children (all ages)0.456
      Yes24421164.80.90.71.2
      No1417755.31
      Children under 2 years old0.416
      Yes300124?00.80.41.4
      No35591795.01
      Children between 2 and < 5 years old0.548
      Yes456204.40.90.51.4
      No34031715.01
      Children between 5 and < 10 years old0.785
      Yes639335.21.10.71.6
      No32201584.91
      Children between 10 and < 15 years old0.449
      Yes747334.40.90.61.3
      No31121585.11
      Children aged 15 years and older0.697
      Yes500234.60.90.61.4
      No33591685.01
      Working in a COVID-19 unit0.223
      Yes31041605.21.30.91.9
      No755314.11
      At least one positive RT-PCR test<0.001<0.001
      Yes944547.922.814.735.29.95.816.8
      No37651463.911
      COVID-19 clinical manifestations
      Variables that are not candidates for the multivariate model.
      <0.001
      Yes16601106.61.91.42.5
      No2199813.71
      Flu-like syndrome<0.001
      Yes1051918.72.61.93.4
      No28081003.61
      Dry cough<0.001
      Yes881748.42.21.73.0
      No29781173.91
      Gastrointestinal symptoms0.007
      Yes746527.01.61.22.2
      No31131394.51
      Loss of taste/smell<0.001<0.001
      Yes1835228.410.17.014.54.22.66.7
      No36761393.811
      Flu vaccine0.02
      Yes1525916.01.41.11.9
      No23341004.31
      NS: Not specified.
      a CI: Confidence interval - Lower bound - Upper bound.
      b Only factors with a significant association at the 0.2 threshold in the bivariate model were included.
      c Variables that are not candidates for the multivariate model.
      Finally, smoking was associated with a reduced risk of seropositivity (adjusted OR = 0.6, 95%CI [0.4–0.9], p = 0.019) (Table 2).

      Discussion

      In the present study, we evaluated the seroprevalence of SARS-CoV-2 in 4696 HCWs at Nancy University Hospital, Northeast France. Data concerning sex, age, BMI, having children, working in a COVID-19 unit, or smoking were collected as well as history of positive SARS-CoV-2 RT-PCR and clinical signs associated with COVID-19, meaning flu-like syndrome, dry cough, gastrointestinal symptoms, loss of taste/smell. The major finding of this study is the confirmed association between COVID-19 seropositive status and a history of COVID-19 associated clinical signs (all types). No effect of sex, age, BMI, and having children was observed on COVID-19 seropositive status. Unexpectedly, smoking was found to be associated to a lower seroprevalence.
      We compared our results to that of other studies that evaluated HCW SARS-CoV-2 seroprevalence, keeping in mind that results may be impacted by time-point and window for sampling. On the one hand, the seroprevalence of SARS-CoV-2 in HCW reached 7% In a study including 230,398 HCWs from 24 countries located all over the world (Europe, USA, China, Singapore, Mexico, India, South Korea), and 11% in a French national study [
      • Warszawski J.
      • Beaumont A.L.
      • Seng R.
      • de Lamballerie X.
      • Rahib D.
      • Lydié N.
      • et al.
      Prevalence of SARS-Cov-2 antibodies and living conditions: the French national random population-based EPICOV cohort.
      ], higher than in our hospital. On the other hand, lower seroprevalences were observed in Danish HCWs (4.04%) [
      • Iversen K.
      • Bundgaard H.
      • Hasselbalch R.B.
      • Kristensen J.H.
      • Nielsen P.B.
      • Pries-Heje M.
      • et al.
      Risk of COVID-19 in health-care workers in Denmark: an observational cohort study.
      ] and in a children's hospital in Southern Italy (1.3%) [
      • Caselli D.
      • Loconsole D.
      • Dario R.
      • Chironna M.
      • Aricò M.
      Effectiveness of preventive measures in keeping low prevalence of SARS-CoV-2 infection in health care workers in a referral children's hospital in southern Italy.
      ]. In the latter Italian study, the low seroprevalence was attributed to the strict application of preventive measures, with a strongly enforced policy of personal protective equipment (PPE) [
      • Caselli D.
      • Loconsole D.
      • Dario R.
      • Chironna M.
      • Aricò M.
      Effectiveness of preventive measures in keeping low prevalence of SARS-CoV-2 infection in health care workers in a referral children's hospital in southern Italy.
      ].
      SARS-CoV-2 seroprevalence of Nancy University Hospital HCW (5.1%) was lower than that in the Whole Northeast of France (6.7%) but higher to that of the Nancy Town (2.1%) metropolis [
      • Gégout Petit A.
      • Jeulin H.
      • Legrand K.
      • Jay N.
      • Bochnakian A.
      • Vallois P.
      • et al.
      Seroprevalence of SARS-CoV-2, symptom profiles and sero-neutralization in a suburban area.
      ]. Yet, seroprevalence was not associated with working in a COVID-19 unit. We can therefore assume that the protection protocols were well applied and made hypothesis that HCWs may also have been contaminated outside the hospital. As an example, other studies demonstrated that community and public transportations were risk factors for seroconversion in HCWs [
      • Martischang R.
      • Iten A.
      • Arm I.
      • Abbas M.
      • Meyer B.
      • Yerly S.
      • et al.
      Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroconversion and occupational exposure of employees at a Swiss university hospital: a large longitudinal cohort study.
      ], as well as social contact [
      • Caselli D.
      • Loconsole D.
      • Dario R.
      • Chironna M.
      • Aricò M.
      Effectiveness of preventive measures in keeping low prevalence of SARS-CoV-2 infection in health care workers in a referral children's hospital in southern Italy.
      ].
      Locally, another study evaluated the seroprevalence in laboratory staff of the same university hospital. This one was almost equal to that of local general population [
      • Gégout Petit A.
      • Jeulin H.
      • Legrand K.
      • Jay N.
      • Bochnakian A.
      • Vallois P.
      • et al.
      Seroprevalence of SARS-CoV-2, symptom profiles and sero-neutralization in a suburban area.
      ,

      Hartard C, Agrinier N, Franck P, Prin-Mathieu C, Debourgogne A, Venard V, et al. Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroprevalence among laboratory staff: safe handling of coronavirus disease 2019 (COVID-19) samples. Infect Control Hosp Epidemiol. :1-2.

      ] and lower compared to HCWs. When handling samples, laboratory technicians are better protected than HCWs, in particular through the use of microbiological safety stations in addition to PPE [

      Hartard C, Agrinier N, Franck P, Prin-Mathieu C, Debourgogne A, Venard V, et al. Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroprevalence among laboratory staff: safe handling of coronavirus disease 2019 (COVID-19) samples. Infect Control Hosp Epidemiol. :1-2.

      ].
      Our study revealed a negative association between smoking and the risk of being infected by SARS-CoV-2, analyzed by serology. This effect was not reported with RT-PCR analyses. But RT-PCR was not systematically realized, and this can lead to bias, if RT-PCR was realized more frequently in symptomatic and/or contact HCWs. The effect of smoking on SARS-CoV-2 infection is still debated. Lower SARS-CoV-2 infection rates among smokers has been previously described (Table 3). Notably, in a Chinese study of 1099 patients with COVID-19 performed until January 29, 2020, the proportion of smokers was 12.6% which is lower than the proportion of smokers in China (28%) [
      • Guan W jie
      • yi Ni Z.
      • Hu Y.
      • hua Liang W.
      • quan Ou C.
      • xing He J.
      • et al.
      Clinical characteristics of coronavirus disease 2019 in China.
      ]. Miyara et al. also reported that daily smokers are less likely to develop symptomatic or severe SARS-CoV-2 infection compared with the general population. This risk in smokers versus non-smokers is five and four times lower in outpatients and inpatients, respectively [
      • Miyara M.
      • Tubach F.
      • Pourcher V.
      • Morélot-Panzini C.
      • Pernet J.
      • Haroche J.
      • et al.
      Lower rate of daily smokers with symptomatic COVID-19: a monocentric self-report of smoking habit study.
      ]. The Italian observational study MUSTANG-OCCUPATION-COVID 19 found that among the current smokers, 19.6% were seropositive whereas 9.2% had not antibodies against SARS-CoV-2 [
      • Della Valle P.
      • Fabbri M.
      • Madotto F.
      • Ferrara P.
      • Cozzolino P.
      • Calabretto E.
      • et al.
      Occupational exposure in the lombardy region (Italy) to SARS-CoV-2 infection: results from the MUSTANG–OCCUPATION–COVID-19 study.
      ]. Contradictory results were observed in other countries [
      • Mostafa A.
      • El-Sayed M.H.
      • El-Meteini M.
      • Saleh A.
      • Omar A.
      • Mansour O.
      • et al.
      SARS-Co-V2 infection in never, former, and current tobacco/nicotine users: a cohort study of 4040 Egyptian healthcare workers.
      ,
      • Jackson S.E.
      • Brown J.
      • Shahab L.
      • Steptoe A.
      • Fancourt D.
      COVID-19, smoking and inequalities: a study of 53 002 adults in the UK.
      ].
      Table 3COVID-19 risk factors associated with smoking: literature data.
      ReferenceStudy populationPopulation sizeResultsConclusion
      Rentsch et al., 2020 [
      • Rentsch C.T.
      • Kidwai-Khan F.
      • Tate J.P.
      • Park L.S.
      • King J.T.
      • Skanderson M.
      • et al.
      Covid-19 testing, hospital admission, and intensive care among 2,026,227 United States veterans aged 54-75 years.
      ]
      Patients hospitalized and/or in intensive care units3789OR = 0.45, 95%CI [0.35–0.57]Current smoking was associated with decreased likelihood of COVID-19
      Guan et al., 2020 [
      • Guan W jie
      • yi Ni Z.
      • Hu Y.
      • hua Liang W.
      • quan Ou C.
      • xing He J.
      • et al.
      Clinical characteristics of coronavirus disease 2019 in China.
      ]
      Patients hospitalized and/or in intensive care units661OR = 0.20, 95%CI [0.08–0.51]

      Adjustment for age: OR = 0.23, 95%CI [0.09–0.59]

      Adjustment for occupation: OR = 0.27, 95%CI [0.10–0.71]
      Smoking was found to be associated with a lower risk of infection, and this association remained significant after adjustment for age or occupation
      De Lusignan et al., 2020 [
      • Lusignan S de
      • Dorward J.
      • Correa A.
      • Jones N.
      • Akinyemi O.
      • Amirthalingam G.
      • et al.
      Risk factors for SARS-CoV-2 among patients in the oxford royal college of general practitioners research and surveillance centre primary care network: a cross-sectional study.
      ]
      Outpatients3802Adjusted OR = 0.49; 95%CI [0.34–0.71]Active smoking was associated with decreased odds of positive test result
      Miyara et al., 2022 [
      • Miyara M.
      • Tubach F.
      • Pourcher V.
      • Morélot-Panzini C.
      • Pernet J.
      • Haroche J.
      • et al.
      Lower rate of daily smokers with symptomatic COVID-19: a monocentric self-report of smoking habit study.
      ]
      Outpatients479OR = 0.24, 95% CI [0.12–0.48]The rate of active daily smoking was significantly lower in COVID-19 patients than in the general 2019 French population after standardization by age and gender
      Hospitalized patients479OR = 0.24, 95%CI [0.14–0.40]
      Jackson et al., 2021 [
      • Jackson S.E.
      • Brown J.
      • Shahab L.
      • Steptoe A.
      • Fancourt D.
      COVID-19, smoking and inequalities: a study of 53 002 adults in the UK.
      ]
      Outpatients53,002Adjusted OR = 1.79, 95%CI [1.22–2.62]Current smoking was independently associated with self-reported confirmed COVID-19 infection
      Mostafa et al., 2021 [
      • Mostafa A.
      • El-Sayed M.H.
      • El-Meteini M.
      • Saleh A.
      • Omar A.
      • Mansour O.
      • et al.
      SARS-Co-V2 infection in never, former, and current tobacco/nicotine users: a cohort study of 4040 Egyptian healthcare workers.
      ]
      Healthcare workers4040Former smokers: adjusted OR = 0.45, 95%CI [0.11–1.89] (p = 0.273)

      Current smokers: adjusted OR = 0.65, 95%CI [0.38–1.09] (p = 0.101)
      Former or recent smoking was not associated with positive SARS-CoV-2 test results in HCWs
      Concerning the durability of humoral protection, a study of a sample of Italian healthcare workers showed that BioNTech-Pfizer COVID-19 vaccine-induced antibody titers declined more rapidly in current smokers than in nonsmokers (211.80 AU/mL vs. 487.50 AU/mL at 60 days after the end of the vaccination cycle). Current smokers showed significantly lower antibody titers or a more rapid decline in vaccine-induced IgG compared with nonsmokers. This shows that active smoking has a negative impact on the humoral response to BioNTech-Pfizer COVID-19 vaccines. It would be interesting to know if this negative impact also occurs in case of natural infection with Sars-CoV-2 [
      • Ferrara P.
      • Ponticelli D.
      • Agüero F.
      • Caci G.
      • Vitale A.
      • Borrelli M.
      • et al.
      Does smoking have an impact on the immunological response to COVID-19 vaccines? Evidence from the VASCO study and need for further studies.
      ].
      In the urban area of the University Hospital of Nancy, another study (MAGIC) was conducted to better define the association of SARS-CoV-2 seroprevalence and tobacco consumption. The study compared three groups, i.e. smokers (˃ 5 cigarettes/day), people in the process of quitting smoking using nicotine replacements, and non-smokers. The study included HCWs as well as people from the general population, aged over 18 years. Small numbers in each group did not allow for observing significant differences, but the same trend was observed. People consuming tobacco and people consuming nicotine replacements tended to have a smaller SARS-CoV-2 seroprevalence (n = 4/62 seropositive in smoker or nicotine replacement groups and 16/113 in non-smoker groups, respectively, p = 0.16). This suggests that nicotine may have an effect on the susceptibility to SARS-CoV-2 infection.
      The association between SARS-CoV-2 infection and smoking is still debated, but so is the mechanism of action of nicotine and tobacco. On the one hand, smoking was associated with the down regulation of ACE2 (the SARS-CoV-2 cell receptor) and can thus reduce entry of viral particles into cells [
      • Wang G.Z.
      • Zhang L.
      • Zhao X.C.
      • Gao S.H.
      • Qu L.W.
      • Yu H.
      • et al.
      The Aryl hydrocarbon receptor mediates tobacco-induced PD-L1 expression and is associated with response to immunotherapy.
      ], and on the other hand ACE2 gene expression has been described as significantly increased in cells exposed to high nicotine concentration [
      • McAlinden K.D.
      • Lu W.
      • Ferdowsi P.V.
      • Myers S.
      • Markos J.
      • Larby J.
      • et al.
      Electronic cigarette aerosol is cytotoxic and increases ACE2 expression on human airway epithelial cells: implications for SARS-CoV-2 (COVID-19).
      ]. We may want to keep in mind that smoking has a structural impact on the respiratory tract and alters the immune system, which generally makes smokers more susceptible to viral and bacterial infections of the lungs [
      • Arcavi L.
      • Benowitz N.L.
      Cigarette smoking and infection.
      ]. Therefore, it obviously cannot be proposed as a prevention tool.
      The present study has limitations such as self-declaration of epidemiological and clinical data. Moreover, due to the large flow of blood sampling performed over a short period of time, various methods had to be used for anti-SARS-CoV-2 antibodies detection. The three methods used all included anti-Spike antibodies detection. They were all validated according to the same local certification criteria and using the same samples. Finally, the same algorithm was applied irrespective of the method used, with the aim to eliminate false positive reaction when only IgM or IgA were positive. Finally, due to the retrospective design of the study we cannot assess the chronological sequence from symptom onset to RT-PCR testing nor when people worked in a COVID-19 unit.
      The strength of the study is the short collection time for all 4696 samples, which enabled a precise evaluation of University Hospital HCWs serological status. The study was performed at an optimal time, i.e., two months after the first epidemic wave in Northeast France. Indeed, the sensitivity of anti-SARS-CoV-2 antibodies detection methods is optimal more than 14 days after the infection, and post-infectious antibodies were described to be detectable for 6–7 months.
      The profile of the epidemic is now completely different, since variants with modulated infectiveness emerged, and HCWs can now benefit from vaccination. All studies analyzing the beginning of the epidemic, including the present one, are precious to improve knowledge on HCW exposure to recently emerging viruses and could no longer be performed as SARS-CoV-2 seropositive status is currently indifferently associated with past infection or vaccination.

      Ethical consideration

      Ethical approval was not provided for this study on human participants because this was a non-interventional study. Biological materials were obtained via standard care (no supplemental sampling) and data were analyzed anonymously.

      Authorship statement

      Stéphanie Weber: Investigation, Data Curation, Writing - Original Draft, Visualization. Alice Didelot: Investigation, Data Curation, Writing - Original Draft, Visualization. Nelly Agrinier: Methodology, Validation, Formal analysis, Writing - Review & Editing. Laurent Peyrin Biroulet: Conceptualization, Writing - Review & Editing. Evelyne Schvoerer: Conceptualization, Writing - Review & Editing. Christian Rabaud: Conceptualization, Writing - Review & Editing, Supervision, Project administration. Hélène Jeulin: Conceptualization, Methodology, Resources, Writing - Review & Editing, Project administration.

      Conflict of interest

      No conflict of interest to declare.

      Funding

      No funding was used for this study.

      Acknowledgments

      We thank all the Hospital staff for their contribution and Laboratory staff for their investment in performing the serological tests. We also thank statisticians from the CIC-EC (CHRU-Nancy, INSERM, Université de Lorraine) for analyses.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article:

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