Skip to main content
PLOS ONE logoLink to PLOS ONE
. 2022 May 25;17(5):e0267725. doi: 10.1371/journal.pone.0267725

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort–EPICOV

Josiane Warszawski 1,2,*, Laurence Meyer 1,2, Jeanna-Eve Franck 3, Delphine Rahib 4, Nathalie Lydié 4, Anne Gosselin 5,6, Emilie Counil 5, Robin Kreling 1, Sophie Novelli 1, Remy Slama 7,8, Philippe Raynaud 9, Guillaume Bagein 9, Vianney Costemalle 9, Patrick Sillard 10, Toscane Fourie 11, Xavier de Lamballerie 11, Nathalie Bajos 3,12; Epicov Team
Editor: Dong Keon Yon13
PMCID: PMC9132278  PMID: 35613100

Abstract

Background

We aimed to study whether social patterns of exposure to SARS-CoV-2 infection changed in France throughout the year 2020, in light to the easing of social contact restrictions.

Methods

A population-based cohort of individuals aged 15 years or over was randomly selected from the national tax register to collect socio-economic data, migration history, and living conditions in May and November 2020. Home self-sampling on dried blood was proposed to a 10% random subsample in May and to all in November. A positive anti-SARS-CoV-2 ELISA IgG result against the virus spike protein (ELISA-S) was the primary outcome. The design, including sampling and post-stratification weights, was taken into account in univariate and multivariate analyses.

Results

Of the 134,391 participants in May, 107,759 completed the second questionnaire in November, and respectively 12,114 and 63,524 were tested. The national ELISA-S seroprevalence was 4.5% [95%CI: 4.0%-5.1%] in May and 6.2% [5.9%-6.6%] in November. It increased markedly in 18-24-year-old population from 4.8% to 10.0%, and among second-generation immigrants from outside Europe from 5.9% to 14.4%. This group remained strongly associated with seropositivity in November, after controlling for any contextual or individual variables, with an adjusted OR of 2.1 [1.7–2.7], compared to the majority population. In both periods, seroprevalence remained higher in healthcare professions than in other occupations.

Conclusion

The risk of Covid-19 infection increased among young people and second-generation migrants between the first and second epidemic waves, in a context of less strict social restrictions, which seems to have reinforced territorialized socialization among peers.

Introduction

Social determinants contribute to socioeconomic, ethno-racial and spatial inequalities in COVID-19 exposure and severity [1, 2]. Their role may change over time according to the stringency or duration of social contact restrictions [3] and vaccination policies. African, Asian, Latin-American and other ethnic minorities were disproportionately affected by SARS-CoV-2 in Europe and North America during the first epidemic wave [48]. However, in the UK, the difference in age-standardized COVID-19 mortality between people with black ethnic background and the white population decreased markedly between the first and second waves [9].

France has been severely affected by COVID-19. The first wave peaked two weeks after the first national lockdown initiated on 17th March 2020, in a context of mask shortages and little availability of PCR tests. The first lockdown, which ended on 11th May 2020, after a dramatic decrease to a very low incidence rate, was very strict, with closure of schools, universities, cultural and social venues, shops except for essential supply, teleworking, and limitation of outdoor circulation.

The second wave started slowly at the end of August, despite a wide-scale distribution of masks and free access to PCR and antigenic tests. Following a period of mandatory physical-distancing and curfew with territorial variations, a second national lockdown was instated from 30 October to 15 December 2020. Unlike the first lockdown which caused widespread suspension of both social and professional life, the second was less restrictive, with no school closure and extended list of shops authorized to remain open. Between the first and second lockdown, teleworking was encouraged, measures maintaining barriers to extra-professional social life remained, especially face covering and maximum numbers admitted to access attractions, coffees and restaurant, but which let more opportunities to get together, especially during the summer.

Most analysis of social and ethnic disparities are based on mortality, hospitalization, and virologic PCR data. Here, we aimed to study the social dynamics of the epidemic between the end of the first lockdown in May and the second in November 2020, using the French national EpiCoV cohort, a large random population-based seroprevalence study [10], enabling identification of changes in factors associated with seropositivity in the context of the easing of social contact restrictions.

Materials and methods

Study design

Individuals aged 15 years or older living in France were randomly selected from the FIDELI administrative sampling frame, covering 96.4% of the population, providing postal addresses for all, and e-mail addresses or telephone numbers for 83%. FIDELI is the national database on housing and individuals issued from tax files, containing demographic information on people and household structure and income, and additional contextual data about the living place of people. The sampling design is detailed elsewhere [10]. Differential sampling was used to ensure oversampling of the less densely populated départements (i.e French administrative districts), and lower-income categories. Residents in nursing homes for elderly persons were excluded, as it was not feasible to obtain help from caregivers to facilitate telephone or web contact with them during the first lockdown. All selected individuals were contacted by post, e-mail and text messages, with up to seven reminders. In the first round in May, computer-assisted-web interviews (CAWI) or computer-assisted-telephone interviews (CATI) were offered to a random 20% subsample. The remaining 80% were assigned to CAWI exclusively. All first-round respondents were eligible for the second in November 2020.

Home capillary blood self-sampling for serological testing

This was proposed during the web/telephone questionnaire to a national random subsample in May, and to all respondents in November. Dried-blood spots were collected on 903Whatman paper (DBS) kits sent to each participant agreeing to blood sampling, mailed to three biobanks (Bordeaux, Amiens, Montpellier) to be punched with a PantheraTM machine (Perkin Elmer). Eluates were processed in a virology laboratory (Unité des virus Emergents, Marseille) with commercial ELISA kits (Euroimmun®, Lübeck, Germany) to detect anti-SARS-CoV-2 antibodies (IgG) against the S1 domain of the viral spike protein (ELISA-S), according to the manufacturer’s instructions.

Outcome

SARS-Cov-2 seroprevalence was estimated as the proportion of individuals tested with an ELISA-S ratio ≥1.1, according to the threshold specified by the manufacturer.

Exposure

Contextual living conditions included administrative geographical area, population density in the municipality of residence, whether the neighbourhood was defined as socially deprived with prioritizing of socio-economic interventions, the number of people in the household, the household per capita income decile, and whether any other household member had had a positive virological PCR or Antigen test since January 2020. Individual characteristics included gender, age, personal and parental migration history, educational level, current occupation (collected with more detail in November), tobacco use, body mass index and comorbidities, number of contacts and face mask use outside home in the week before the second-round interview.

Ethics and regulatory issues

The survey was approved by CNIL (the French data protection authority) (ref: MLD/MFI/AR205138) and the ethics committee (Comité de Protection des Personnes Sud M editerranee III 2020-A01191-38) on April 2020, and by the “Comité du Label de la Statistique Publique”. The serological results were sent to the participants by post with information about interpreting individual test results.

Statistical analyses

We first repeated the same univariate and multivariate analyses on the May and November samples to estimate, for each period, the seroprevalence on national level and by geographical area, contextual variables, housing conditions, and individual characteristics, and to study changes in the strength of their associations with the presence of antibodies between these two periods. We then considered the subsample of people tested negative in May (ELISA-S ratio <0.7), to study associations with positive serology in November, as a measure of the incidence of new infections between the two periods. Finally, we performed an additional multivariate analysis on the November sample, as it was much larger and included more detailed information than in May, that we added step by step in order to study the role of socio-economic and migration status more fully.

Final calibrated weights were calculated to correct for non-response, as detailed elsewhere [10], for first and second round. Response homogeneity groups were derived from the sampling weight divided by the probability of response estimated with logit models adjusted for auxiliary variables potentially linked to both the response mechanism and the main variables of interest in the EpiCov survey. The Fideli sampling frame provided a wide range of auxiliary variables, including sociodemographics, income, quality of contact information, and contextual variables at territorial level, such as population density, proportion of people below the poverty line, obtained from geo-referenced information. Variables collected in the first round were added as auxiliary variables to adjust non-response models for the second round. First-step weights estimated from the percentage of respondents in each homogeneity group were calibrated according to the margins of the population census data and population projections for age categories, gender, departement, educational level, and region, to decrease the variance and the residual bias for variables correlated with margins.

The unequal probabilities sampling design, and final calibrated weights were taken into account, with the specific design-based “proc survey” procedures of SAS and “svy” procedures of STATA. Prevalences were estimated, using weighted percentages, and logit transformed confidence limits were used to remain within the interval [0,1]. The design-based Pearson chi-squared test statistic developed by Rao was used for multiway contingency tables [11]. Crude and adjusted odds ratios were estimated with logistic regression models based on design-based methods [12]. The significance threshold was 0.05.

Results

Among the 134 391 respondents to the first-round questionnaire in May 2020, 107 759 (80.2%) completed the second-round questionnaire in November 2020 (Fig 1). Serological tests were performed in mainland France on 12 114 participants for the first round (median date: May 21st 2020; IQR: 18th– 28th May), and 63 524 for the second (November 24th 2020; IQR: 18th November– 4th December).

Fig 1. Flowchart: The national EpiCov cohort, round 1 (May 2020) and round 2 (November 2020).

Fig 1

The national seroprevalence (ELISA-S ratio ≥1.1) increased from 4.5% [95%CI: 4.0–5.1%] in May to 6.2% [5.9–6.6%] in November, with wide disparities between départements from under 2% to 13% (Table 1; S1 Table).

Table 1. SARS-Cov-2 SEROPREVALENCE (ELISA-S ≥ 1.11) according to living condition, among people living in mainland France 2: The national EpiCov cohort, rounds 1 & 2.

ELISA ≥ 1.1 (May 2020) 3 ELISA ≥ 1.1 (November 2020) 3
Total cases % CI 95% p Total cases % CI95% P
All 12114 785 4.5 [4.0–5.1] 63524 3943 6.2 [5.9–6.6]
Number of people in household
    1 1665 74 2.1 [1.4–3.1] <0.001 10377 570 5.2 [4.5–5.9] <0.001
    2 4266 203 2.7 [2.2–3.4] 24994 1331 4.9 [4.6–5.3]
    3 2268 173 5.1 [4.0–6.6] 10902 741 6.5 [5.8–7.2]
    4 2560 210 7.1 [5.6–8.9] 12040 899 7.9 [7.1–8.8]
    5 or more 1349 125 8.5 [6.1–11.8] 5189 400 10.1 [8.7–11.8]
≥1 suspected Covid case in household <0.001
    Living alone 1665 74 2.1 [1.4–3.1] 10377 570 5.2 [4.5–5.9] <0.001
    No (and not living alone) 8822 433 4.0 [3.4–4.7] 37355 1494 4.1 [3.8–4.5]
    Yes before June 2020 1621 278 12.9 [10.6–15.6] 4543 514 12.0 [10.4–13.8]
    Yes since June 2020 8143 966 13.4 [12.2–14.6]
    Yes before and after June 2020 3084 397 12.6 [11.1–14.3]
Population density in municipality
    Low 3666 219 3.4 [2.7–4.4] <0.001 23647 1178 4.5 [4.1–4.8] <0.001
    Medium 3562 199 3.3 [2.5–4.2] 18650 1075 5.4 [4.9–6]
    High 4886 367 6.4 [5.3–7.6] 21227 1690 8.5 [7.9–9.2]
Socially-deprived neighbourhood
    No 11589 743 4.2 [3.7–4.8] 0.021 61840 3778 5.9 [5.6–6.2] <0.001
    Yes 525 42 8.2 [4.7–14] 1684 165 11.2 [8.9–14]
Geographical area (region)
    11- Ile de France 2430 214 9.0 [7.3–11.2] <0.001 10441 1021 11.0 [10;0–12.1] <0.001
    24-Centre Loire 232 8 2.4 [1.2–5.0] 2527 107 4.2 [3.1–5.7]
    27-Bourgogne Franche Comté 280 7 1.5 [0.6–3.4] 3056 195 5.6 [4.6–6.7]
    28-Normandie 266 7 1.5 [0.7–3.3] 2788 115 3.1 [2.5–3.8]
    32-Hauts de France 1499 66 3.7 [2.2–6.1] 5876 418 6.8 [5.9–7.9]
    44-Grand Est 3239 323 6.7 [5.2–8.5] 6461 501 6.7 [5.9–7.6]
    52-Pays de Loire 328 11 2.9 [1.6–5.3] 3869 148 3.0 [2.4–3.8]
    53-Bretagne 307 12 4.8 [2.3–9.8] 3510 105 2.5 [1.9–3.2]
    75-Nouvelle Aquitaine 538 13 2.0 [1.1–3.5] 5820 202 3.4 [2.8–4.1]
    76-Occitanie 560 19 2.2 [1.4–3.7] 6335 268 4.5 [3.7–5.5]
    84-Auvergne 716 36 4.0 [2.8–5.6] 8274 643 8.4 [7.4–9.4]
    93-PACA 1687 69 5.0 [3.2–7.6] 4278 211 4.4 [3.5–5.4]
    94-Corse 32 0 0.0 289 9 4.8 [1.9–11.4]

1. Home sampling by finger prick/Euroimmun ELISA-S test

2. People aged 15 years or over residing in mainland France, outside nursing homes for elderly and prisons.

3. The sampling design is taken into account for the estimation of prevalence, confidence intervals (logit transformation) and statistical tests, with the SAS procsurvey procedure. The percentages are weighted by sampling weight (the inverse of inclusion probability), corrected for non-response weigts and calibrated on the margin of the census. The prevalences are not equal to n/N.

In both periods, seroprevalence was significantly higher among individuals living in highly densely populated municipalities, in socially deprived neighbourhoods and in large households (Table 1). The strength of the association with household size was weaker in November than in May.

Seroprevalence, which tended to be higher among women than men in May (5.0% versus 3.9%; p = 0.054), was similar between men and women in November (6.1% and 6.3%; p = 0.52) (Table 2). Seroprevalence increased with higher diploma levels, and was associated with a U-shaped curve with family per capita income, with lowest rates in the central decile especially in May. Prevalence remained nearly twice as high among healthcare professionals as among people with other occupations, whether self-reported as essential or not, respectively 11.3% and 6.4% in November. Detailed analysis of professional occupations in November showed the highest seroprevalences in hospital professions (physicians, nurses and assistant nurses), two to three times higher than for other occupations, including private physicians, pharmacists, teachers and workers in essential stores. Daily smokers were at lower risk of having antibodies than occasional, former or non-smokers.

Table 2. SARS-Cov-2 SEROPREVALENCE (ELISA-S ≥ 1.11) according to individual socio-economic factors, among people living in mainland France 2: The national EpiCov cohort, rounds 1 & 2.

ELISA ≥ 1.1 (May 2020) 3 ELISA ≥ 1.1 (November 2020) 3
Total cases % CI 95% p Total cases % CI95% P
All 12114 785 4.5 [4.0–5.1] 63524 3943 6.2 [5.9–6.6]
Gender
    Men 5469 321 3.9 [3.1–4.8] 0.052 27564 1665 6.1 [5.7–6.6] 0.459
    Women 6645 464 5.0 [4.3–5.9] 35960 2278 6.4 [6–6.8]
Age (years)
    15–17 418 27 4.5 [2.2–8.9] <0.001 1438 128 9.8 [7.8–12.2] <0.001
    18–24 1042 61 4.8 [3–7.6] 4919 483 10.0 [8.6–11.5]
    25–34 1544 118 5.0 [3.7–6.7] 6816 490 7.2 [6.3–8.3]
    35–44 2050 198 8.3 [6.7–10.4] 10345 671 6.5 [5.8–7.4]
    45–54 2340 176 4.9 [3.9–6.2] 12596 850 6.5 [5.9–7.2]
    55–64 2234 122 4.8 [3.3–7.1] 12879 710 5.3 [4.8–5.8]
    65–74 1727 64 1.8 [1.2–2.7] 10611 462 4.3 [3.8–4.9]
    75+ 759 19 0.7 [0.4–1.4] 3920 149 3.7 [2.9–4.7]
Migratory status 4
    No (majority population) 9769 612 4.1 [3.5–4.7] <0.001 54296 3172 5.3 [5.1–5.6] <0.001
    Immigrant from Europe
    First- generation 345 22 3.8 [2–6.9] 1577 84 5.2 [3.9–6.8]
    Second- generation 668 39 3.8 [2.4–5.9] 3164 197 6.0 [4.9–7.3]
    Immigrant from outside Europe
    First- generation 606 61 9.2 [6.2–13.6] 1760 207 13.3 [10.7–16.3]
    Second- generation 581 44 5.9 [3.8–9.2] 1894 233 14.4 [11.9–17.4]
Detailed Migratory status 4
No (majority population)
    Born in Mainland France 9646 596 4.0 3.4–4.6 53697 3109 5.3 [5.0–5.5]
    Born in FOD 5 56 8 12.4 5.3–26.3 301 32 7.3 [4.8–11.2]
    Parents born in FOD5 67 8 3.3 1.2–9.2 298 31 7.5 [4.7–11.6]
Immigrant from Europe
    First- generation 345 22 3.8 [2–6.9] 1577 84 5.2 [3.9–6.8]
    Second- generation 668 39 3.8 [2.4–5.9] 3164 197 6.0 [4.9–7.3]
1st generation from outside Europe
    Born in Africa 356 35 7.4 4.5–12.1 950 126 15.5 [11.9–20.0]
    Born in Asia or elsewhere 250 26 13.4 7.1–23.7 810 81 9.4 [6.8–12.8]
2nd generation from outside Europe 581 44 5.9 [3.8–9.2] 1894 233 14.4 [11.9–17.4]
    Born in Africa 385 29 6.8 4.0–11.4 1181 156 15.6 [12.3–19.6]
    Born in Asia or elsewhere 196 15 4.1 1.9–8.4 713 77 12.1 [8.7–16.5]
Occupation in May 6
    Healthcare profession 578 74 11.4 [8.2–15.6] <0.001 3219 338 11.3 [9.8–13] <0.001
    Other essential profession 1219 99 5.2 [3.8–7.1] 6259 381 6.4 [5.3–7.7]
    Non-essential profession 4960 365 5.7 [4.8–6.8] 24984 1619 6.4 [5.9–6.9]
    No occupation 5356 247 3.0 [2.3–3.9] 29046 1605 5.7 [5.3–6.2]
Educational level
    < High school diploma 1908 98 3.2 [2.2–4.8] <0.001 8496 488 5.6 [4.9–6.3] <0.001
High school diploma 3922 204 3.3 [2.6–4.2] 20384 1171 5.7 [5.2–6.3]
    Secondary first degree diploma 2435 184 6.4 [5.0–8.0] 13509 835 6.9 [6.3–7.6]
    ≥ Bachelor’s degree 3849 299 6.2 [5.2–7.5] 21135 1449 7.3 [6.8–7.9]
Family income per capita (deciles)
    D01 (lowest) 798 52 5.7 [3.2–9.9] 0.016 3672 241 8.2 [6.7–10] <0.001
    D02-D03 1430 86 4.8 [3.5–6.7] 6481 385 6.2 [5.3–7.3]
    D04-D05 1718 97 3.3 [2.4–4.5] 9098 523 5.3 [4.7–6.0]
    D06-D07 2423 128 2.9 [2.2–3.8] 13252 785 5.9 [5.4–6.5]
    D08-D09 3332 237 5.5 [4.5–6.7] 18724 1147 6.1 [5.7–6.6]
    D10 2112 159 6.0 [4.7–7.6] 10880 766 7.0 [6.5–7.6]
Tobacco use <0.001
    Daily smoker 1995 69 2.8 [2.0–4.0] 0.032 8949 266 2.7 [2.3–3.2]
    Occasional smoker 470 33 5.1 [3.1–8.2] 2941 196 7.8 [6.2–9.7]
    Ex smoker since epidemic 879 48 5.4 [3.3–8.6]
    Ex-smoker before epidemic 3888 253 4.5 [3.5–5.8] 15895 940 5.7 [5.2–6.3]
    Non-smoker 5756 430 5.1 [4.3–6.0] 34819 2492 7.5 [7.1–8]

1. Home sampling by finger prick/Euroimmun ELISA-S test

2. People aged 15 years or over residing in mainland France, outside nursing homes for elderly and prisons.

3. The sampling design is taken into account for the estimation of prevalence, confidence intervals (logit transformation) and statistical tests, with the SAS procsurvey procedure. The percentages are weighted by sampling weight (the inverse of inclusion probability), corrected for non-response weigts and calibrated on the margin of the census. The prevalences are not equal to n/N.

4. Migratory status: Majority population = persons born in France who are neither first nor second-generation immigrants / First-generation immigrants: born non-French outside France and living permanently in France (including those who subsequently acquired French nationality) / Second-generation immigrants: born and living in France, with at least one parent a first-generation immigrant

5. FOD: French overseas départements

6. Self-reported in round 1: a) Healthcare professions Include medical and paramedical professionals, firefighters, pharmacists and ambulance drivers (but not including hospital cleaners, for example),.; b) Other essential professions included: Home helps or housekeepers, food shop workers, delivery drivers, public transportation drivers, cab drivers, bank customer services or reception staff, petrol station employees, police officers, postal workers, cleaning staff, security guards, construction workers, truck drivers, farmers and social workers), also self-reported.

The major changes in seroprevalence between May and November 2020 concerned age and migration status. In May 2020, the highest prevalence was observed among middle-aged people (8.3% in 35–44 years old) while in November 2020, it concerned the youngest (9.6% and 9.9% respectively in the 15–17 and 18–24 age groups). In May 2020, prevalence was significantly higher among immigrants born outside Europe (9.2% compared to 5.9% among second-generation immigrants from outside Europe, and 4.1% in the French-born population), but the increased risk disappeared after adjustment for living conditions (Table 3). In contrast, in November 2020, seroprevalence was higher in both first (13.3%) and second (14.4%) generation immigrants from outside Europe, compared to 5.3% among French-born and 6.0% among European immigrants, and they remained at higher risk even after adjustment for living conditions (adjusted odds ratio respectively: 2.1 [1.7–2.8] and 2.2 [1.8–2.9]).

Table 3. Univariate and multivariate logistic regressions: Factors associated with ELISA-S seropositivity1 among people living in mainland France at the end of first and second lockdown 2: The national EpiCov cohort, rounds 1 & 2.

ELISA ≥ 1.1 (May 2020) ELISA ≥ 1.1 (November 2020)
ORcrude 95% CI3 ORadj 95% CI3 ORcrude 95% CI3 ORadj 95% CI3
Individual characteristics
Gender P = 0.053 P = 0.085 P = 0.45 P = 0.88
    Men ref ref ref ref
    Women 1.3 [1.0–1.7] 1.3 [1.0–1.7] 1.0 [0 .9–1.2] 1.0 [0.9–1.1]
Age (years) P<0.001 P = 0.003 P<0.001 P<0.001
    15–17 6.3 [2.3–17.1] 3.2 [1.0–10.3] 2.8 [2.0–4.1] 2.0 [1.4–3.0]
    18–24 6.9 [3.0–15.6] 2.9 [1.2–6.0] 2.9 [2.2–3.9] 2.2 [1.6–3.0]
    25–34 7.2 [3.4–14.9] 2.5 [1.5–8.2] 2.0 [1.5–2.7] 1.6 [1.1–2.3]
    35–44 12.3 [6.1–25.0] 5.4 [2.4–12.5] 1.8 [1.4–2.4] 1.3 [0.9–1.8]
    45–54 7.0 [3.4–14.2] 3.6 [1.6–8.4] 1.8 [1.4–2.4] 1.5 [1.1–2.1]
    55–64 6.9 [3.1–15.1] 4.8 [2.0–11.6] 1.5 [1.1–1.9] 1.4 [1.0–1.9]
    65–74 2.5 [1.1–5.5] 2.3 [1.0–5.2] 1.2 [0.9–1.5] 1.2 [0.9–1.6]
    75+ ref ref ref ref
Migration status 4 P = 0.002 P = 0.705 P<0.001 P<0.001
    No (majority population) ref ref ref ref
    First- generation from Europe 0.9 [0.5–1.8] 1.1 [0.6–2.3] 1.0 [0.7–1.3] 1.1 [0.8–1.4]
    Second- generation Europe 0.9 [0.6–1.5] 1.0 [0.6–1.7] 1.1 [0.9–1.4] 1.2 [1.0–1.5]
    First-generation outside Europe 2.4 [1.5–3.9] 1.6 [0.8–3.0] 2.7 [2.1–3.5] 2.0 [1.5–2.5]
    Second- generation outside Europe 1.5 [0.9–2.5] 1.1 [0.6–1.9] 3.0 [2.4–3.8] 2.1 [1.7–2.7]
Occupational status 5 P<0.001 P = 0.002 P<0.001 P = 0.001
    Healthcare profession 2.1 [1.4–3.2] 2.1 [1.4–3.2] 1.9 [1.6–2.2] 1.9 [1.6–2.3]
    Other essential profession 0.9 [0.6–1.3] 1.0 [0.7–1.5] 1.0 [0.8–1.2] 0.9 [0.8–1.1]
    Non-essential profession ref ref ref ref
    No occupation 0.5 [0.4–0.7] 0.8 [0.6–1.2] 0.9 [0.8–1.0] 1.0 [0.9–1.1]
Educational level P<0.001 P = 0.072 P<0.001 P = 0.31
    < High school diploma ref ref ref ref
    High school diploma 1.0 [0.6–1.7] 1.0 [0.6–1.6] 1.0 [0.9–1.2] 1.1 [0.9–1.3]
    Secondary first degree diploma 2.0 [1.3–3.3] 1.5 [0.9–2.5] 1.3 [1.1–1.5] 1.2 [1.0–1.5]
    ≥ Bachelor’s degree 2.0 [1.3–3.1] 1.2 [0.7–1.9] 1.3 [1.1–1.6] 1.1 [0.9–1.4]
Family income per capita (deciles) P<0.001 P = 0.004 P<0.001 P = 0.009
    D01 (lowest) 2.0 [1.0–3.9] 1.5 [0.8–2.9] 1.4 [1.1–1.8] 1.1 [0.8–1.3]
    D02-D03 1.7 [1.1–2.6] 1.7 [1.0–2.6] 1.1 [0.9–1.3] 0.9 [0.7–1.1]
    D04-D05 1.1 [0.7–1.7] 1.1 [0.7–1.7] 0.9 [0.8–1.0] 0.8 [0.7–1.0]
    D06-D07 ref ref ref ref
    D08-D09 1.9 [1.4–2.7] 1.9 [1.3–2.7] 1.0 [0.9–1.2] 1.0 [0.9–1.2]
    D10 2.1 [1.5–3.1] 1.9 [1.3–2.9] 1.2 [1.1–1.4] 1.2 [1.0–1.3]
Tobacco use P = 0.035 P = 0.025 P<0.001 P<0.001
    Daily smoker ref ref ref ref
    Occasional smoker 1.8 [1.0–3.5] 2.0 [1.0–4.0] 3.1 [2.3–4.2] 2.4 [1.7–3.3]
    Ex smoker since epidemic 2.1 [1.2–3.5] 1.9 [1.1–3.2]
    Ex-smoker before epidemic 1.6 [1.0–2.6] 1.8 [1.2–2.9] 2.2 [1.8–2.7] 2.4 [2.0–3.0]
    Non-smoker 1.8 [1.2–2.8] 1.9 [1.2–2.8] 3.0 [2.5–3.6] 2.8 [2.3–3.5]
Living conditions
Population density in municipality P<0.001 P <0.001 P<0.001 P<0.001
    Low ref ref ref ref
    Medium 1.0 [0.7–1.4] 1.1 [0.8–1.6] 1.2 [1.1–1.4] 1.1 [1.0–1.3]
    High 1.9 [1.4–2.7] 1.8 [1.3–2.5] 2.0 [1.8–2.2] 1.6 [1.4–1.8]
Socially deprived neighbourhood P = 0.024 P = 0.35 <0.001 P = 0.009
    No ref ref ref ref
    Yes 2.0 [1.1–3.7] 1.4 [0.7–2.6] 2.0 [1.5–2.6] 1.4 [1.1–1.9]
Number of people in household P<0.001 P = 0.003 P<0.001 P<0.001
    1 ref ref ref ref
    2 1.3 [0.8–2.1] 1.4 [0.9–2.3] 1.0 [0.8–1.1] 1.0 [0.8–1.2]
    3 2.5 [1.6–4.1] 2.0 [1.2–3.6] 1.3 [1.1–1.5] 1.1 [1.0–1.4]
    4 3.6 [2.2–5.8] 2.5 [1.4–4.4] 1.6 [1.3–1.9] 1.4 [1.1–1.6]
    5 or more 4.4 [2.5–7.6] 3.4 [1.7–6.6] 2.1 [1.7–2.6] 1.4 [1.1–1.7]

1. Home sampling by finger prick/Euroimmun ELISA-S test

2. People aged 15 years or over residing in mainland France, outside nursing homes and prisons.

3. The sampling design is taken into account for the estimation of prevalence, confidence intervals (logit transformation), crude and adjusted odds ratios, confidence intervals and statistical tests, with the SAS procsurvey procedure. The percentages are weighted by sampling weight (the inverse of inclusion probability), corrected for non-response weigts and calibrated on the margin of the census. The prevalences are not equal to n/N.

4. Migratory status: Majority population = persons born in France who are neither first nor second-generation immigrants / First-generation immigrants: born non-French outside France and living permanently in France (including those who subsequently acquired French nationality) / Second-generation immigrants: born and living in France, with at least one parent being a first-generation immigrant

5. Self-Reported in round 1: a) Healthcare professions Included medical and paramedical professionals, firefighters, pharmacists and ambulance drivers (but not including hospital cleaners, for example); b) Other essential professions included: home helps or housekeepers, food shop workers, delivery drivers, public transportation drivers, cab drivers, bank customer service or reception staff, petrol station employees, police officers, postal workers, cleaning staff, security guards, construction workers, truck drivers, farmers and social workers), also self-reported.

In order to understand the overexposure of non-European immigrants and their descendants in November 2020, detailed analyses were performed (S2 Table), taking into account behaviours related to social distancing strategies self-reported over the week before the interview (number of prolonged contacts, mask use in the street, family or festive outings) and BMI. Associations with migration status remained unchanged. The analysis was also restricted to highly densely populated areas, and the overexposure of the second generation immigrants from outside Europe remained.

Results from the analysis of incidence of new infections between May and November was consistent with changes in seroprevalence (S3 Table). Overall, 3.8% [3.1–4.7%] of 7 515 people with no IgG antibodies in May were positive in November. The proportion of new infections was the highest in the 18–24 age group, among second-generation immigrants from outside Europe, among people living in socially deprived neighbourhoods, and among health-care professionals. Neither household size, diploma nor family income were associated with new infections between May and November.

Discussion

Seroprevalence in France increased slowly from the end of the first lockdown to the second, from 4.5% [95%CI: 4.0–5.1%] in May 2020 to 6.2% [5.9–6.6%] in November 2020. Seroprevalence estimated in November probably underestimates the cumulate incidence from the start of the epidemic, as the level of antibodies wanes with time [1315]. However only 8.3% [7.3–9.4] of participants tested twice were positive at least once, and the highest prevalence rates were under 20% even in the most affected regions. At the end of 2020, the level of herd immunity in the general population in France remained low. Wide geographical disparities, with continental eastern and central areas the most affected, and western oceanic areas the least, could partly reflect the residual impact of the first strict national lockdown which stopped the spread of the virus from the north-east [16].

Between May and November 2020 seroprevalence increased much more among young people, while the middle-aged population was mainly affected during the first wave. This change is likely to be explained by more infections during the summer holidays and autumn, consistent with the higher positivity rate on PCR and antigenic tests reported to French Si-Dep surveillance systems between June and November 2020, ranging from 4.7% among 20-29-year-olds to 3.1% among 40-59-year-olds and 1.7% among 70-79-year-olds.

The second major change was the increased seroprevalence among descendants of non-European immigrants (second-generation immigrants), independently of their younger age. In May 2020, seroprevalence was twice as high among first-generation immigrants from outside Europe as in the majority population, i.e. neither immigrants nor their descendants, and this was mainly explained by residence in a densely-populated area and a large household. In November 2020, prevalence was three times higher among both non-European immigrants and their descendants, reflecting a strong increase in new infections in the second generation between May and November. Adjustment for age accounted for only part of this increase. Mostly, the association remained independent of socio-economic and living conditions, geographical area, mask use and number of prolonged contacts. Nor was this explained by differences in tobacco use, comorbidities or BMI. Similar results were observed when the analysis was restricted to highly-densely populated municipalities, and urban areas where most immigrants reside, or to areas the most affected by Covid-19.

African Americans, Hispanics, and other ethnic minority groups were disproportionately affected by SARS-CoV-2, as mostly documented during the first epidemic wave in terms of diagnosed infection, hospitalization [68] and mortality [7, 8]. Among potential reasons for higher incidence or severity related to ethnicity, biological susceptibilities have been hypothesized [1719] but without evidence [20]. Inequalities in mortality could be primarily driven by differences in exposure to infection [21]. In England, there was a marked reduction in the difference in age-standardized COVID-19 mortality between people from black ethnic backgrounds and people from the white group between first and second wave [9]. Some minority ethnic populations have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the white population, even after taking account of differences in socio-demographic, clinical, and household characteristics [22].

Our study, based on repeated general population seroprevalence measures, showed that while the overexposure to Covid-19 infection of first-generation immigrants was strongly linked to their living conditions at the beginning of the epidemic, the overexposure observed six months later for the first and especially the second generation, who have more social contacts more than their elders, is not the result of a lesser respect for barrier gestures or of more frequent outings than the native-born (S1 Table). It could result from micro-social structural effects, because of the phenomena of socio-spatial segregation [23] and territorialized socialization [24]. Second-generation immigrants are very often grouped together, facilitating the circulation of the virus in social groups where the prevalence is higher.

Relationships between seropositivity and population density in the residence area, family income and diploma tended to be weaker in November than in May. This could suggest a protective role of the widespread use of masks in working and public areas, and testing strategies before visiting family. In a national survey in the UK, having patient-facing role and working outside home was an important risk factor in the first but not the second wave [25]. However, despite wide availability of surgical masks after severe shortage during the first epidemic wave, seroprevalence among healthcare professionals remained twice as high as among individuals with other occupations in November, similar to May, with the highest rates among hospital physicians, nurses and assistant nurses. The seroprevalence was similar in May and November while the proportion of new infections was much higher than in other occupations, which could suggest that health-care professionals were infected early during the first wave, with possibly higher proportions of seroreversion in that population because IgG levels decrease with time. This increased risk was not explained by socio-demographic or living conditions, except for medical students where the association was partly explained by their younger age. The 11% seroprevalence found in May is in line with the 8.5% found in Europe during the first wave in a meta-analysis [26], with few studies on the risk of nosocomial transmission among health-care worker [27].

Strengths

The EpiCov cohort is one of the largest socio-epidemiological random population-based cohorts providing Covid-19 seroprevalence estimate among individuals aged 15 years and over. Most seroprevalence surveys were conducted during the first epidemic wave [2830]. The two other national serological studies based on random general population samples was conducted in Spain [31] and England [21] and reported prevalence of same magnitude than in France. EpiCov identified the population most affected by the spread of the virus in the population since initial spread, providing a basis for evaluating subsequent changes in light with epidemiological context and access to preventive strategies. People living below the poverty line were intentionally over-represented in the sampling, and detailed socio-economic and migration data was obtained. We were therefore able to perform a powerful analysis focusing on social inequalities.

The home self-sampling with DBS detection of SARS CoV-2 antibodies was ideally suited to the context of the first lockdown to limit self-selection bias.

The estimates provided here were weighted for non-response. Many auxiliary demographic and socio-economic variables were available from the sampling framework, which made it possible to correct a large part of the non-response bias.

Limitations

The EpiCov study had several limitations. It does not cover elderly people living in nursing homes. The Euroimmun ELISA-S test has a sensitivity of 94.4%, according to the manufacturer’s cutoff. It has been evaluated in various studies, which reported specificity ranging from 96.2% to 100% and sensitivity ranging from 86.4% to 100% [32, 33]. Anti-Sars-Cov2 IgG antibody levels have been reported to decline more or less rapidly, particularly among the elderly and subjects with mild or asymptomatic forms [1315]. However, such decline seems not to be a source of bias to study changes is population exposed to covid between the two epidemic waves: our results were similar when analysing factors associated with new Covid infections between May and November in the subsample tested in both rounds, and changes in factors associated with seroprevalence between these two periods.

Conclusion

The role of living conditions on the risk of SARS-CoV-2 infection decreased between the first and second epidemic waves, possibly partly due to the widespread availability of masks and virological tests at population level. Nevertheless, in November 2020, in a context of less restricted social contacts than during the first lockdown, seroprevalence remained higher among healthcare professionals than among other professionals, and strongly increased among young people and racial minorities. These populations need special attention, especially for adherence to vaccination policies.

Supporting information

S1 Table. Seroprevalence (ELISA-S > 1.11) according to départment in November 2020 among people living in mainland France.

The national EpiCov cohort, 2020 November round.

(DOCX)

S2 Table. Factors associated with seropositivity (ELISA-S > 1.1) in November 2020 among people living in mainland France.

The national EpiCov cohort, 2020 November round–Univariate and multivariate analysis including detailed occupation, detailed living conditions and self-reported distancing behaviours over the last 7 days.

(DOCX)

S3 Table. Proportion of new infections between May and November 2020: Proportion of positive serologies in November among people seronegative in May—The national EpiCov cohort.

(DOCX)

Acknowledgments

Epicov Team: Josiane Warszawski (co-principal investigator) and Nathalie Bajos (co-principal investigator), Guillaume Bagein, François Beck, Emilie Counil, Florence Jusot, Nathalie Lydie, Claude Martin, Laurence Meyer, Philippe Raynaud, Alexandra Rouquette, Ariane Pailhé, Delphine Rahib, Patrick Sicard, Rémy Slama, Alexis Spire.

Lead : Josiane Warszawski, INSERM CESP U1018, AP-HP Epidemiology and Public Health Service, S Université Paris-Saclay, Le Kremlin-Bicêtre, France Mail Josiane.warszawski@universite-paris-saclay.fr

Nathalie Bajos (co-lead), Iris–Institut de Recherche Interdisciplinaire sur les enjeux sociaux, Inserm, Aubervilliers, France ; Ecole des Hautes Etudes en Sciences Sociales, Paris, France

Guillaume Bagein, DREES—Direction de la Recherche, des Etudes, de l’évaluation et des statistiques, Paris, France

François Beck, Santé Publique France, Saint-Maurice France

Emilie Counil, French Institute for Demographic Studies (INED)

Florence Jusot, Université Paris Dauphine, Paris, France

Nathalie Lydie, Santé Publique France, Saint-Maurice France

Claude Martin, ARENES UMR 6051, CNRS, EHESP, Rennes, Franc

Laurence Meyer, INSERM CESP U1018, AP-HP Epidemiology and Public Health Service, S Université Paris-Saclay, Le Kremlin-Bicêtre, France Mail Josiane.warszawski@universite-paris-saclay.fr

Philippe Raynaud, DREES—Direction de la Recherche, des Etudes, de l’évaluation et des statistiques, Paris, France

Alexandra Rouquette, INSERM CESP U1018, AP-HP Epidemiology and Public Health Service, S Université Paris-Saclay, Le Kremlin-Bicêtre, France Mail Josiane.warszawski@universite-paris-saclay.fr

Ariane Pailhé,, French Institute for Demographic Studies (INED)

Delphine Rahib, Santé Publique France, Saint-Maurice France

Patrick Sillard, Institut National de la statistique et des études économiques, Montrouge, France

Rémy Slama, Institut thématique de Santé Publique, INSERM, Paris France, Inserm, CNRS, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Institute for Advanced Biosciences, University Grenoble Alpes, Grenoble, France

Alexis Spire, Iris–Institut de Recherche Interdisciplinaire sur les enjeux sociaux, Inserm, Aubervilliers, France

We sincerely thank all the participants in the EpiCoV study.

We warmly thank the INSERM staff, including, in particular, Carmen Calandra, Karim Ammour, Jean-Marc Boivent, Jean-Marie Gagliolo, Frédérique Le Saulnier, and Frédéric Robergeau, who worked with considerable dedication and commitment to make it possible to develop, in record time, and to maintain all regulatory, budgetary, technical, and logistical aspects of the EpiCov study.

We warmly thank the staff of Santé publique France, and especially Lucie Duchesne, who played a major role in organisation and quality assurance for the seroprevalence component of the EpiCov study.

We thank the CRB biobanks staff, and especially their heads, Dr Isabelle Pellegrin, and Julien Jeanpetit (Centre Hospitalier Universitaire Robert Pellegrin, Bordeaux, France), Pr Edouard Tuaillon Centre de Ressources Biologiques du CHU de Montpellier), Dr Yves-Edouard Herpe (Centre de Ressources Biologiques Biobanque de Picardie), Pr Jacqueline Deloumeaux (Centre biologique du CHU de la Guadeloupe), Dr Rémi Neviere (CeRBiM, Centre de Ressources Biologiques de la Martinique), Julien Eperonnier, Estelle Nobecourt (Centre de Ressources Biologiques de la Réunion) for the quality of DBS sample management of the EpiCov study. We thank the biobank team in Inserm SC10, particularly Sophie Circosta.

We also thank the staff of the UVE virology department, for the high-quality management of such a large number of serological assays.

We thank the staff of DREES and INSEE, for their collaboration in the implementation of the study, methodological input, sample selection, and the complex development of weights to correct for non-response.

We thank the Ipsos staff, including Christophe David and Valérie Blineau in particular, for their major contribution to the quality of data collection.

The EPICOV study group

Josiane Warszawski1,2, Nathalie Bajos9 (joint principal investigators), Guillaume Bagein, François Beck4, Emilie Counil10, Florence Jusot11,, Nathalie Lydié4, Claude Martin12, Laurence Meyer,2, Philippe Raynaud7, Alexandra Rouquette1,2, Ariane Pailhé10, Delphine Rahib4, Patrick Sillard8, Alexis Spire12.

INSERM CESP U1018, Université Paris-Saclay, Le Kremlin-Bicêtre, France

2 AP-HP Epidemiology and Public Health Service, Service, Hôpitaux Universitaires Paris-Saclay, Le Kremlin-Bicêtre, France

3 Unité des Virus Emergents, UVE, Aix Marseille Univ, IRD 190, INSERM 1207, IHU Méditerranée Infection, Marseille, France

4 Santé Publique France, Saint-Maurice France

5 Institut thématique de Santé Publique, INSERM, Paris France

6 Inserm, CNRS, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Institute for Advanced Biosciences, University Grenoble Alpes, Grenoble, France

7 DREES—Direction de la Recherche, des Etudes, de l’évaluation et des statistiques, Paris, France

8 Institut National de la statistique et des études économiques, Montrouge, France

9 IRIS, INSERM, EHESS, CNRS Aubervilliers, France

10 INED, France

11 Université Paris Dauphine, France

12 CNRS, France

The EPICOV study group: J Warszawski, N Bajos (Co-PI), G Bagein, F Beck, E Counil, F Jusot,, N Lydié, C Martin, L Meyer, P Raynaud, A Rouquette, A Pailhé, D Rahib, P Sillard, A Spire.

Data Availability

All anonymous aggregated data concerning the results presented in this paper are available online and on supporting information files. The EpiCov study is available for research purpose after submission to approval of French Ethics and Regulatory Committee procedure (Comité du Secret Statistique, CESREES and CNIL). Access procedure is available on CASD (https://www.casd.eu/). Additional information can be addressed to the corresponding author.

Funding Statement

This research was supported by research grants from Inserm (Institut National de la Santé et de la Recherche Médicale) and the French Ministry for Research, by Drees-Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques, and the French Ministry for Health, and by the Région Ile de France. Dr. Bajos has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [856478]) This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016167, ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Bambra C, Riordan R, Ford J, Matthews F. The COVID-19 pandemic and health inequalities. J Epidemiol Community Health. 2020. Jun 13;jech-2020-214401. doi: 10.1136/jech-2020-214401 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Dorn A van Cooney RE, Sabin ML. COVID-19 exacerbating inequalities in the US. The Lancet. 2020. Apr 18;395(10232):1243–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Bajos N, Jusot F, Pailhé A, Spire A, Martin C, Meyer L, et al. When lockdown policies amplify social inequalities in COVID-19 infections: evidence from a cross-sectional population-based survey in France. BMC Public Health. 2021. Apr 12;21:705. doi: 10.1186/s12889-021-10521-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Pareek M, Bangash MN, Pareek N, Pan D, Sze S, Minhas JS, et al. Ethnicity and COVID-19: an urgent public health research priority. Lancet Lond Engl. 2020;395(10234):1421–2. doi: 10.1016/S0140-6736(20)30922-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Hayward SE, Deal A, Cheng C, Crawshaw A, Orcutt M, Vandrevala TF, et al. Clinical outcomes and risk factors for COVID-19 among migrant populations in high-income countries: A systematic review. J Migr Health. 2021;3:100041. doi: 10.1016/j.jmh.2021.100041 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Sze S, Pan D, Nevill CR, Gray LJ, Martin CA, Nazareth J, et al. Ethnicity and clinical outcomes in COVID-19: A systematic review and meta-analysis. EClinicalMedicine. 2020. Dec;29:100630. doi: 10.1016/j.eclinm.2020.100630 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Mackey K, Ayers CK, Kondo KK, Saha S, Advani SM, Young S, et al. Racial and Ethnic Disparities in COVID-19–Related Infections, Hospitalizations, and Deaths: A Systematic Review. Ann Intern Med. 2021. Mar;174(3):362–73. doi: 10.7326/M20-6306 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Mude W, Oguoma VM, Nyanhanda T, Mwanri L, Njue C. Racial disparities in COVID-19 pandemic cases, hospitalisations, and deaths: A systematic review and meta-analysis. J Glob Health. 11:05015. doi: 10.7189/jogh.11.05015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Nafilyan V, Islam N, Mathur R, Ayoubkhani D, Banerjee A, Glickman M, et al. Ethnic differences in COVID-19 mortality during the first two waves of the Coronavirus Pandemic: a nationwide cohort study of 29 million adults in England. Eur J Epidemiol. 2021. Jun;36(6):605–17. doi: 10.1007/s10654-021-00765-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Warszawski J, Bajos N, Barlet M, Lamballerie X de, Rahib D, Lydié N, et al. A national mixed-mode seroprevalence random population-based cohort on SARS-CoV-2 epidemic in France: the socio-epidemiological EpiCov study. medRxiv. 2021. Feb 26;2021.02.24.21252316. [Google Scholar]
  • 11.Rao JN, Scott AJ. On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Ann Stat. 1984;46–60. [Google Scholar]
  • 12.Skinner CJ, Holt D, Smith TMF. Analysis of complex surveys [Internet]. John Wiley & Sons; 1989. [cited 2022 Feb 12]. 328 p. Available from: https://eprints.soton.ac.uk/34690/ [Google Scholar]
  • 13.Arkhipova-Jenkins I, Helfand M, Armstrong C, Gean E, Anderson J, Paynter RA, et al. Antibody Response After SARS-CoV-2 Infection and Implications for Immunity: A Rapid Living Review. Ann Intern Med. 2021. Jun;174(6):811–21. doi: 10.7326/M20-7547 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Pérez-Olmeda M, Saugar JM, Fernández-García A, Pérez-Gómez B, Pollán M, Avellón A, et al. Evolution of antibodies against SARS-CoV-2 over seven months: experience of the Nationwide Seroprevalence ENE-COVID Study in Spain [Internet]. Infectious Diseases (except HIV/AIDS); 2021. Mar [cited 2021 Jun 9]. Available from: http://medrxiv.org/lookup/doi/10.1101/2021.03.11.21253142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Shioda K, Lau MSY, Kraay ANM, Nelson KN, Siegler AJ, Sullivan PS, et al. Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies. Epidemiology. 2021. Jul;32(4):518–24. doi: 10.1097/EDE.0000000000001361 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Cauchemez S, Kiem CT, Paireau J, Rolland P, Fontanet A. Lockdown impact on COVID-19 epidemics in regions across metropolitan France. Lancet Lond Engl. 2020;396(10257):1068–9. doi: 10.1016/S0140-6736(20)32034-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Khunti K, Singh AK, Pareek M, Hanif W. Is ethnicity linked to incidence or outcomes of covid-19? BMJ. 2020. Apr 20;369:m1548. doi: 10.1136/bmj.m1548 [DOI] [PubMed] [Google Scholar]
  • 18.Kalyanaraman B. Do free radical NETwork and oxidative stress disparities in African Americans enhance their vulnerability to SARS-CoV-2 infection and COVID-19 severity? Redox Biol. 2020. Sep 15;37:101721. doi: 10.1016/j.redox.2020.101721 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Singh U, Hernandez KM, Aronow BJ, Wurtele ES. African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors associated with immunologic functions and environmental exposures. Sci Rep. 2021. May 10;11:9905. doi: 10.1038/s41598-021-89224-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Raisi-Estabragh Z, McCracken C, Bethell MS, Cooper J, Cooper C, Caulfield MJ, et al. Greater risk of severe COVID-19 in Black, Asian and Minority Ethnic populations is not explained by cardiometabolic, socioeconomic or behavioural factors, or by 25(OH)-vitamin D status: study of 1326 cases from the UK Biobank. J Public Health Oxf Engl. 2020. Aug;42(3):451–60. doi: 10.1093/pubmed/fdaa095 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Ward H, Atchison C, Whitaker M, Ainslie KEC, Elliott J, Okell L, et al. SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic. Nat Commun. 2021. Dec;12(1):905. doi: 10.1038/s41467-021-21237-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Mathur R, Rentsch CT, Morton CE, Hulme WJ, Schultze A, MacKenna B, et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet Lond Engl. 2021. May 8;397(10286):1711–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Floch J-M. Standards of living and segregation in twelve French metropolises. Econ Stat. 2017;497(1):73–96. [Google Scholar]
  • 24.Hipp JR, Faris RW, Boessen A. Measuring ‘neighborhood:Constructing network neighborhoods. Soc Netw [Internet]. 2012. [cited 2021 Sep 1];34(1). Available from: https://escholarship.org/uc/item/28d4217b. [Google Scholar]
  • 25.Pouwels KB, House T, Pritchard E, Robotham JV, Birrell PJ, Gelman A, et al. Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey. Lancet Public Health. 2021. Jan;6(1):e30–8. doi: 10.1016/S2468-2667(20)30282-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.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. Feb;108:120–34. doi: 10.1016/j.jhin.2020.11.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Abbas M, Robalo Nunes T, Martischang R, Zingg W, Iten A, Pittet D, et al. Nosocomial transmission and outbreaks of coronavirus disease 2019: the need to protect both patients and healthcare workers. Antimicrob Resist Infect Control. 2021. Jan 6;10(1):7. doi: 10.1186/s13756-020-00875-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Rostami A, Sepidarkish M, Leeflang MMG, Riahi SM, Nourollahpour Shiadeh M, Esfandyari S, et al. SARS-CoV-2 seroprevalence worldwide: a systematic review and meta-analysis. Clin Microbiol Infect. 2021. Mar;27(3):331–40. doi: 10.1016/j.cmi.2020.10.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lai C-C, Wang J-H, Hsueh P-R. Population-based seroprevalence surveys of anti-SARS-CoV-2 antibody: An up-to-date review. Int J Infect Dis. 2020. Dec;101:314–22. doi: 10.1016/j.ijid.2020.10.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Bobrovitz N, Arora RK, Cao C, Boucher E, Liu M, Donnici C, et al. Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis. PloS One. 2021;16(6):e0252617. doi: 10.1371/journal.pone.0252617 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Pollán M, Pérez-Gómez B, Pastor-Barriuso R, Oteo J, Hernán MA, Pérez-Olmeda M, et al. Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study. The Lancet. 2020. Aug;396(10250):535–44. doi: 10.1016/S0140-6736(20)31483-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Patel EU, Bloch EM, Clarke W, Hsieh Y-H, Boon D, Eby Y, et al. Comparative Performance of Five Commercially Available Serologic Assays To Detect Antibodies to SARS-CoV-2 and Identify Individuals with High Neutralizing Titers. J Clin Microbiol. 2021. Jan 21;59(2):e02257–20. doi: 10.1128/JCM.02257-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Kohmer N, Westhaus S, Rühl C, Ciesek S, Rabenau HF. Clinical performance of different SARS-CoV-2 IgG antibody tests. J Med Virol. 2020. Oct;92(10):2243–7. doi: 10.1002/jmv.26145 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Dong Keon Yon

22 Dec 2021

PONE-D-21-33692Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort – EPICOV Evidence from the national socio-epidemiological cohort – EPICOVPLOS ONE

Dear Dr. Warszawski,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Feb 05 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Dong Keon Yon, MD, FACAAI

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following financial disclosure: 

"This research was supported by research grants from Inserm (Institut National de la Santé et de la Recherche Médicale) and the French Ministry for Research, by Drees-Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques, and  the French Ministry for Health,  and by the Région Ile de France.

Dr. Bajos has  received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [856478])

This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016167, ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic)."

  

Please state what role the funders took in the study.  If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 

If this statement is not correct you must amend it as needed. 

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

3. Thank you for stating the following in the Financial Disclosure Section of your manuscript: 

"This research was supported by research grants from Inserm (Institut National de la Santé et de la Recherche Médicale) and the French Ministry for Research, by Drees-Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques, and  the French Ministry for Health,  and by the Région Ile de France.

Dr. Bajos has  received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [856478])

This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016167, ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic)."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. 

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: 

"This research was supported by research grants from Inserm (Institut National de la Santé et de la Recherche Médicale) and the French Ministry for Research, by Drees-Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques, and  the French Ministry for Health,  and by the Région Ile de France.

Dr. Bajos has  received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [856478])

This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016167, ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic)."

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

4. Please amend either the title on the online submission form (via Edit Submission) or the title in the manuscript so that they are identical.

5. One of the noted authors is a group or consortium Epicov Team. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

6. We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

7. Please upload a new copy of Figure 2 as the detail is not clear. Please follow the link for more information: https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/" https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/

8. We note that Figure 2 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figure 2 to publish the content specifically under the CC BY 4.0 license.  

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

Additional Editor Comments:

Please address the excellent comments from the reviewers.

Minor comments

1. please disucss the paper below.

Lee SW, Yuh WT, Yang JM, Cho YS, Yoo IK, Koh HY, Marshall D, Oh D, Ha EK, Han MY, Yon DK. Nationwide Results of COVID-19 Contact Tracing in South Korea: Individual Participant Data From an Epidemiological Survey. JMIR Med Inform. 2020 Aug 25;8(8):e20992. doi: 10.2196/20992. PMID: 32784189; PMCID: PMC7470235.

2. Title

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socioepidemiological cohort – EPICOV Evidence from the national socio-epidemiological cohort – EPICOV

->

Trends in social exposure to SARS-Cov-2: Results from the French Nationwide Cohort

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socioepidemiological cohort – EPICOV Evidence from the national socio-epidemiological cohort – EPICOV

Title is adequate.

The abstract is well described and objective.

Keywords: I suggest to the authors to exclude some keywords as “random sample” and include keywords that remind the country the study was conducted.

Introduction: Very adequate.

“African, Asian and other ethnic minorities were disproportionately affected by SARS-CoV-2 in Europe and North America during the first epidemic wave.” Please include “Latin-American individuals”.

“France has been severely affected by COVID-19. The first wave peaked two weeks after the first lockdown initiated on 17th March” Please describe here the year. Also please describe in the text if it was a national lockdown or regional lockdown.

“The second wave started slowly at the end of August,” Same observation as described above regarding the year.

“but leaving more opportunities to get together from the summer.” Please clarify this statement .

Aim of the study is adequate and well-described.

Methods:

Please describe what is “FIDELI administrative sampling framework” ?

“Residents in nursing homes for elderly persons were excluded.” Please describe why.

Study design is very adequate.

In the Exposure section were evaluated medical conditions of the participants? It is not clear for me.

Results section is well-described. Tables are adequate too. I would suggest to exclude table 4 and describe its information in the text, due to a lot of tables in the study.

Discussion: The discussion section is well argued. I miss other data in the literature on serological surveys in France and in countries that have adopted the lockdown, such as England and Spain.

Strenghts and limitations are adequately described. Conclusion is adequate.

Reviewer #2: Thanks to extensive and well conducted epidemiological study in France, this work has revealed an increased risk of SARS-CoV-2 transmission in young people and second-generation migrants when restrictions were less stringent between the first two pandemic waves. However, the statistic analysis has not been well detailed in the manuscript. The authors talk about univariate and multivariate analyses, but a much more extensive explanation should be provided. Which statistical tests have been applied, how, and why? Do the data fulfill all requirements to apply these tests? What about the statistical potency? I guess it is high due to the very high sample number. Please, show all details. Please, present the data in an APA format or similar, associating the statistica value to the p-values that appear in tables. I guess the t-test has been applied because the confidence intervals are given, but statistical analysis is of utmost importance here and should be explained very rigorously. I guess that it has been properly performed, but an idea only exist as far as it is written, as Jacques Monod highlighted. The a priori chosen level of statistical significance should be indicated. The same is applicable to correlation and logistic regression analysis and inference.

As the authors point out in the "Limitations" section, circulating antibody titles may vary and decay over time, and even they disappear in certain cases. However, memory B cell analysis is not feasible in this context. In lines 385 through 387, the authors highlight consistency between factors associated to incidence and prevalence. However, this does not solve the limitation, and this should be also pointed out. In this sentence, "of new infections" should be removed, because this is included in the "incidence" concept.

Please, remove an extra space after period in line 391. There are also some extra spaces to remove in the supplementary file. Please, carefully review this.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Vicente Sperb Antonello

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2022 May 25;17(5):e0267725. doi: 10.1371/journal.pone.0267725.r002

Author response to Decision Letter 0


25 Mar 2022

Editor comments

Q2 and 3 Financial disclosure :

Role of the funders:

Response: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Place in the manuscript:

Response: the contains is strictly similar to those provided in the online Funding Statement and we removed it from the manuscript, and we will add the above sentence about the role of the funders

Added in the cover letter

This research was supported by research grants from Inserm (Institut National de la Santé et de la Recherche Médicale) and the French Ministry for Research, by Drees-Direction de la Recherche, des Etudes, de l’Evaluation et des Statistiques, and the French Ministry for Health, and by the Région Ile de France.

Dr. Bajos has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [856478])

This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016167, ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Q4 Title : Please amend either the title on the online submission form (via Edit Submission) or the title in the manuscript so that they are identical.

Response: keep title in the manuscript

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort – EPICOV

Q5 Group epicov : One of the noted authors is a group or consortium Epicov Team. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address

Response: Done

Q6 “data not shown” in the manuscript :

Response: Such data are not necessary for the current paper and they are developed in a submitted paper currently in revision elsewhere. We then suppressed the sentence which referred to it as it is not necessary. Our discussion and conclusion are entirely supported by data included in the paper (line 336 to 341).

We suppressed the unnecessary sentence in the discussion “Populations of non-European first and second-generation immigrants were as compliant with barrier measures as others in March and November (data not shown)”.

Q7 and 8 Please upload a new copy of Figure 2 as the detail is not clear. We note that Figure 2 in your submission contain [map/satellite] images which may be copyrighted.

� Response: It was too difficult to obtain total copyright. This figure is not needed as the Table 1 and the supplementary table (as referred) bring geographical seroprevalence.

� We suppressed the figure 2

Additional Editor Comments:

Minor comments

1. please disucss the paper below.

Lee SW, Yuh WT, Yang JM, Cho YS, Yoo IK, Koh HY, Marshall D, Oh D, Ha EK, Han MY, Yon DK. Nationwide Results of COVID-19 Contact Tracing in South Korea: Individual Participant Data From an Epidemiological Survey. JMIR Med Inform. 2020 Aug 25;8(8):e20992. doi: 10.2196/20992. PMID: 32784189; PMCID: PMC7470235.

Response : please, can you explain what is expected as discussion?

2.Title

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socioepidemiological cohort – EPICOV Evidence from the national socio-epidemiological cohort – EPICOV->

Trends in social exposure to SARS-Cov-2: Results from the French Nationwide Cohort

Response: we retain “Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort – EPICOV”

Reviewer #1

I thank the reviewer for the comments and enclose here our responses to proposals or questions.

Com1 : Keywords: I suggest to the authors to exclude some keywords as “random sample” and include keywords that remind the country the study was conducted.

Response: We think that the specificity of such design is very important to mention in keywords and propose to replace random sample by “probability sample design”. The country is mentioned in the title.

Keyword : random sample replaced by “probability sampling design”

Com2 : “African, Asian and other ethnic minorities were disproportionately affected by SARS-CoV-2 in Europe and North America during the first epidemic wave.” Please include “Latin-American individuals”

Response: Done

Added L62: African, Asian, Latin-American and other ethnic minorities were disproportionately affected by SARS-CoV-2 in Europe and North America during the first epidemic wave

Com3 : “France has been severely affected by COVID-19. The first wave peaked two weeks after the first lockdown initiated on 17th March” Please describe here the year. Also please describe in the text if it was a national lockdown or regional lockdown. The second wave started slowly at the end of August,” Same observation as described above regarding the year.

Response: Done

The first national lockdown initiated on 17th March 2020 (line 68)

A second national lockdown was instated from 30 October to 15 December 2020 (line 76)

Com6 : “ but leaving more opportunities to get together from the summer.” Please clarify this statement

Response: I agree that it is not very clear. the paragraph was clarified

Change line 77-82 : Unlike the first lockdown which caused widespread suspension of both social and professional life, the second was less restrictive, with no school closure and extended list of shops authorized to remain open. Between the first and second lockdown, teleworking was encouraged, measures maintaining barriers to extra-professional social life remained, especially face covering and maximum numbers admitted to access attractions, coffees and restaurant, but which let more opportunities to get together, especially during the summer.

Com7 : Please describe what is “FIDELI administrative sampling framework” ?

Response: done

102 to 105 : FIDELI is the national database on housing and individuals issued from tax files, containing demographic information on people and household structure and income, and additional contextual data about the living place of people.

Com7 : “Residents in nursing homes for elderly persons were excluded.” Please describe why.

Response: done

� Added in lines 107 to 108 : Residents in nursing homes for elderly persons were excluded, as it was not feasible to obtain help from caregivers to facilitate telephone or web contact with them during the first lockdown.

Com9: In the Exposure section were evaluated medical conditions of the participants? It is not clear for me.

Response: Self reported symptoms and comorbidities were collected in the questionnaire. For this analysis, we did not include data on symptoms. Adjustment for some comorbidities to study the relation of seropositivity with migration status was performed and presented in supplemental material.

We added in line 136 : Individual characteristics included …, body max index and comorbidities…..

Com9: Results section is well-described. Tables are adequate too. I would suggest to exclude table 4 and describe its information in the text, due to a lot of tables in the study.

Response: done

� The Table 4 was removed and added to supplemental data S3

Com11: Discussion: The discussion section is well argued. I miss other data in the literature on serological surveys in France and in countries that have adopted the lockdown, such as England and Spain.

Response: done

Added in line 424 et 425 (with two added references) : The two other national serological studies based on random general population samples was conducted in Spain (ref Pollan) and England (ref Ward) and reported prevalence of same magnitude than in France.

Reviewer #2

I thank the reviewer for the comments and enclose here our responses to proposals or questions.

Com1 : The authors talk about univariate and multivariate analyses, but a much more extensive explanation should be provided. Which statistical tests have been applied, how, and why? Do the data fulfill all requirements to apply these tests? What about the statistical potency? I guess it is high due to the very high sample number. Please, show all details. Please, present the data in an APA format or similar, associating the statistical value to the p-values that appear in tables. I guess the t-test has been applied because the confidence intervals are given, but statistical analysis is of utmost importance here and should be explained very rigorously. I guess that it has been properly performed, but an idea only exist as far as it is written, as Jacques Monod highlighted. The a priori chosen level of statistical significance should be indicated. The same is applicable to correlation and logistic regression analysis and inference.

Response:

I agree with the importance to add more details on the statistical methods used in this paper (that I reduce because of the limits of words).

The methodology is adapted to complex sample design, as standard procedures based upon classical SRS (simple random sample) and IID (Independent and identically distributed random variables) are generally not appropriate in such design. There is a large amount of methodological literature and I added two major classical references on the principle of the méthods in that domain, with large discussion on design-based or model-based approach:

� Skinner CJ, Holt D, Smith TMF. Analysis of complex surveys [Internet]. John Wiley & Sons; 1989 [cited 2022 Feb 12]. 328 p. Available from: https://eprints.soton.ac.uk/34690/

� Rao JN, Scott AJ. On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Ann Stat. 1984;46–60.

We used here the design-based statistical methods, classically used in many population-based study, using procedure developed and validated in Stata (svy procedures), SAS (proc survey), or R (package survey)

I am not used to add the value of the statistics value with the p-value, and which is rarely presented in epidemiologic papers. Statistical value is not interpretable here as it does not correspond to classical tests. Moreover tests and confidence intervals cannot be calculated from frequency presented in the tables as weighting is applied for point estimate, and design is taken into account for variance estimation.

I rewrited the methodological paragraph with reference to the two papers, and hope it will be sufficient.

Paragraph rewritten (line 171-177): The unequal probabilities sampling design, and final calibrated weights were taken into account, with the specific design-based “proc survey” procedures of SAS and “svy” procedures of STATA. Prevalences were estimated, using weighted percentages, and logit transformed confidence limits were used to remain within the interval [0,1]. The design-based Pearson chi-squared test statistic developed by Rao was used for multiway contingency tables (12). Crude and adjusted odds ratios were estimated with logistic regression models based on design-based methods (11). The significance threshold was 0.05.

Com2 : What about the statistical potency? I guess it is high due to the very high sample number.

Response: Sample size was initially calculated so as to ensure sufficient precision for the seroprevalence estimate, the goal being to obtain a 95% confidence interval of 2 points for a prevalence of 5% in administrative subdivisions of 600,000 inhabitants (department or metropolitan area). Moreover individuals living in a household below the poverty line were overrepresented to have sufficient powerful to study relation of exposure with social disadvantage (as indicated in line 107-108)

Com3 : As the authors point out in the "Limitations" section, circulating antibody titles may vary and decay over time, and even they disappear in certain cases. However, memory B cell analysis is not feasible in this context. In lines 385 through 387, the authors highlight consistency between factors associated to incidence and prevalence. However, this does not solve the limitation, and this should be also pointed out. In this sentence, "of new infections" should be removed, because this is included in the "incidence" concept.

Response: We agree that the decline of antibodies should be a limitation to study trends in prevalence. However, our objective was to study whether there were changes in population exposed to Covid between first and second epidemic waves. As our conclusions are very similar when analyzing new infection between May and November and when comparing factors associated with prevalences at each period, we can conclude than decline in antibodies was not a source of bias for our main results.

Paragraph changed in 412-16 : However, such decline seems not to be a source of bias to study changes is population exposed to covid between the two epidemic waves: our results were similar when analysing factors associated with new Covid infections between May and November in the subsample tested in both rounds, and changes in factors associated with seroprevalence between these two periods.

Attachment

Submitted filename: 0-Rebutal_letter_24March2022_plosone.docx

Decision Letter 1

Dong Keon Yon

14 Apr 2022

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort – EPICOV

PONE-D-21-33692R1

Dear Dr. Warszawski,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Dong Keon Yon, MD, FACAAI

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

This is an excellent paper.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I have carefully read the review carried out by the authors. All my questions were answered properly and adjustments were made. Therefore, I recommend this article for publication in Plos One.

Reviewer #2: In my opinion, the manuscript is now ready for publication because all isues raised have been adequately addressed and the manuscript improved accordingly.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Vicente Sperb Antonello

Reviewer #2: No

Acceptance letter

Dong Keon Yon

28 Apr 2022

PONE-D-21-33692R1

Trends in social exposure to SARS-Cov-2 in France. Evidence from the national socio-epidemiological cohort – EPICOV

Dear Dr. Warszawski:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Dong Keon Yon

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Seroprevalence (ELISA-S > 1.11) according to départment in November 2020 among people living in mainland France.

    The national EpiCov cohort, 2020 November round.

    (DOCX)

    S2 Table. Factors associated with seropositivity (ELISA-S > 1.1) in November 2020 among people living in mainland France.

    The national EpiCov cohort, 2020 November round–Univariate and multivariate analysis including detailed occupation, detailed living conditions and self-reported distancing behaviours over the last 7 days.

    (DOCX)

    S3 Table. Proportion of new infections between May and November 2020: Proportion of positive serologies in November among people seronegative in May—The national EpiCov cohort.

    (DOCX)

    Attachment

    Submitted filename: 0-Rebutal_letter_24March2022_plosone.docx

    Data Availability Statement

    All anonymous aggregated data concerning the results presented in this paper are available online and on supporting information files. The EpiCov study is available for research purpose after submission to approval of French Ethics and Regulatory Committee procedure (Comité du Secret Statistique, CESREES and CNIL). Access procedure is available on CASD (https://www.casd.eu/). Additional information can be addressed to the corresponding author.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES