Risk of SARS-CoV-2 infection in professional settings, shops, shared transport, and leisure activities in France, 2020–2022

Abstract

Purpose
The aim of the study was to identify settings associated with SARS-CoV-2 transmission throughout the COVID-19 pandemic in France.

Methods
Cases with recent SARS-CoV-2 infection were matched with controls (4:1 ratio) on age, sex, region, population size, and calendar week. Odds ratios for SARS-CoV-2 infection were estimated for nine periods in models adjusting for socio-demographic characteristics, health status, COVID-19 vaccine, and past infection.

Results
Between October 27, 2020 and October 2, 2022, 175,688 cases were matched with 43,922 controls. An increased risk of infection was documented throughout the study for open-space offices compared to offices without open space (OR range across the nine periods: 1.12 to 1.57) and long-distance trains (1.25 to 1.88), and during most of the study for convenience stores (OR range in the periods with increased risk: 1.15 to 1.44), take-away delivery (1.07 to 1.28), car-pooling with relatives (1.09 to 1.68), taxis (1.08 to 1.89), airplanes (1.20 to 1.78), concerts (1.31 to 2.09) and night-clubs (1.45 to 2.95). No increase in transmission was associated with short-distance shared transport, car-pooling booked over platforms, markets, supermarkets and malls, hairdressers, museums, movie theatres, outdoor sports, and swimming pools. The increased risk of infection in bars and restaurants was no longer present in restaurants after reopening in June 2021. It persisted in bars only among those aged under 40 years.

Conclusion
Closed settings in which people are less likely to wear masks were most affected by SARS-CoV-2 transmission and should be the focus of air quality improvement.

ClinicalTrials.gov (03/09/2022)
NCT04607941.

Full text

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Galmiche et al. BMC Public Health (2024) 24:2411
https://doi.org/10.1186/s12889-024-19651-y BMC Public Health
*Correspondence:
Simon Galmiche
simon.galmiche@pasteur.fr
1Emerging Diseases Epidemiology Unit, Institut Pasteur, Université Paris
Cité, 25 rue du Docteur Roux, Paris 75015, France
2Sorbonne Université, Ecole Doctorale Pierre Louis de Santé Publique,
Paris 75006, France
3Clinical Research Coordination Oce, Institut Pasteur, Université Paris
Cité, Paris 75015, France
4Department of Public Aairs – Public Statistics, Institut Ipsos, Paris
75013, France
5Santé Publique France, Saint-Maurice 94410, France
6Sorbonne Université, Inserm, IPLESP, Hôpital Saint-Antoine, AP-HP,
Paris 75012, France
7Unité PACRI, Conservatoire National des Arts et Métiers, Paris
75003, France
Abstract
Purpose The aim of the study was to identify settings associated with SARS-CoV-2 transmission throughout the
COVID-19 pandemic in France.
Methods Cases with recent SARS-CoV-2 infection were matched with controls (4:1 ratio) on age, sex, region,
population size, and calendar week. Odds ratios for SARS-CoV-2 infection were estimated for nine periods in models
adjusting for socio-demographic characteristics, health status, COVID-19 vaccine, and past infection.
Results Between October 27, 2020 and October 2, 2022, 175,688 cases were matched with 43,922 controls. An
increased risk of infection was documented throughout the study for open-space oces compared to oces without
open space (OR range across the nine periods: 1.12 to 1.57) and long-distance trains (1.25 to 1.88), and during most
of the study for convenience stores (OR range in the periods with increased risk: 1.15 to 1.44), take-away delivery
(1.07 to 1.28), car-pooling with relatives (1.09 to 1.68), taxis (1.08 to 1.89), airplanes (1.20 to 1.78), concerts (1.31 to
2.09) and night-clubs (1.45 to 2.95). No increase in transmission was associated with short-distance shared transport,
car-pooling booked over platforms, markets, supermarkets and malls, hairdressers, museums, movie theatres,
outdoor sports, and swimming pools. The increased risk of infection in bars and restaurants was no longer present in
restaurants after reopening in June 2021. It persisted in bars only among those aged under 40 years.
Conclusion Closed settings in which people are less likely to wear masks were most aected by SARS-CoV-2
transmission and should be the focus of air quality improvement.
ClinicalTrials.gov (03/09/2022) NCT04607941.
Keywords SARS-CoV-2, Case-control studies, Infectious disease transmission, Occupational exposure, Workplace,
Travel, Leisure activities
Risk of SARS-CoV-2 infection in professional
settings, shops, shared transport, and leisure
activities in France, 2020–2022
SimonGalmiche1,2*, TianyCharmet1, ArthurRakover1, OliviaChény3, FaïzaOmar4, ChristopheDavid4,
AlexandraMailles5, FabriceCarrat6 and ArnaudFontanet1,7
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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Galmiche et al. BMC Public Health (2024) 24:2411
Introduction
Identifying settings where transmission of SARS-CoV-2
occurs and quantifying their respective contribution has
been central to advise evidence-based mitigation strate-
gies such as social distancing policy, testing practices,
contact tracing, and information to the public [1]. As
the impact of the pandemic recedes in most countries,
knowledge on the settings of transmission can help guide
improvement in air quality and individual protection
approaches, particularly for elderly or immunocompro-
mised people. Furthermore, drawing all available infor-
mation from the SARS-CoV-2 pandemic is essential
to preparedness efforts: in case of emergence of a new
respiratory virus, knowledge derived from SARS-CoV-2
will support a timely and evidence-based public health
response.
roughout the pandemic, numerous factors poten-
tially affecting where SARS-CoV-2 transmission may
occur have undergone significant changes, including
non-pharmaceutical interventions, vaccine coverage, or
the circulating strain.
Several study designs have been used to address this
question. Outbreak reports have generated crucial early
evidence, particularly in settings with low community
transmission, allowing accurate contact tracing [2–6].
Other studies have aimed to screen all contacts of a series
of cases and identify in which settings contacts were
more likely to result in transmission [7, 8]. ese designs
often require the correct identification of contacts, which
can be difficult for SARS-CoV-2 in case of long-distance
airborne transmission [9] or superspreading event: a
study in Hong Kong reported that approximately 20% of
cases were responsible for 80% of secondary cases [10].
It is especially challenging in locations where unrelated
people interact closely, for instance in public transport.
Other studies have estimated the risk or odds ratios of
infection associated with different settings, through
cross-sectional seroprevalence estimates [11–13] or case-
control designs [14–17].
While many studies have identified the risk associated
with venues such as bars, night-clubs, or public trans-
port, none have provided a long-term outlook to assess
potential changes through the pandemic. In the present
study, which was conducted over a two-year period, we
used a case-control design to identify settings associ-
ated with the risk of SARS-CoV-2 infection in France and
assess how these evolved through the pandemic.
Methods
We conducted an online case-control study in mainland
France from October 2020 to October 2022. e meth-
ods of the study have been reported before [18–20]. We
included cases aged 18 and above with recently diag-
nosed SARS-CoV-2 infection reported in a national
information system: all cases diagnosed through RT-PCR
or rapid antigen tests were centralized by the national
health insurance system (Caisse nationale d’assurance
maladie, CNAM). e CNAM sent email invitations
to cases identified within the past week who had previ-
ously provided their email address (approximately 55%
of all people affiliated with the CNAM, who represent
about 89% of the population of mainland France). Both
RT-PCR and rapid antigen tests were available free of
charge without prescription for the whole duration of the
study. After providing consent, participants completed
an online questionnaire about sociodemographic infor-
mation, health status, household description, and recent
exposures of interest. e questions focused on the 10
days preceding the onset of the symptoms (or testing if
asymptomatic). is period was reduced to 7 days after
the emergence of the omicron variant given its shorter
incubation period [21]. Following the participation of
the cases, controls were enrolled by Ipsos, a market and
opinion research company, and matched with cases using
a frequency-matched procedure. Matching criteria were
age (18–29, 30–54, ≥ 55 years old), sex (male or female as
self-reported), region (largest administrative subnational
division), size of population in the area of residence,
and week of exposure to account for local transmission
dynamics.
We did not include potential cases and controls who
were under a legal status of curatorship or guardian-
ship at the time of participation. Until February 2021,
we included only controls without a past episode of
SARS-CoV-2 infection. Eligibility for controls was then
extended to people without ongoing SARS-CoV-2 infec-
tion. We excluded cases and controls reporting an epi-
sode of SARS-CoV-2 infection in the past two months
(other than the one leading to their participation for
cases). To limit recall errors, we excluded cases who filled
the questionnaire over 30 days after the onset of symp-
toms (or testing if asymptomatic). We allowed repeated
participation after at least two months since the last par-
ticipation from January 2022.
To study the evolution of the risk associated with the
exposures of interest over the course of the study, we
divided the study period into nine shorter periods, based
on incidence, important non-pharmaceutical interven-
tions (stay-at-home orders, curfews, sanitary pass, i.e.
a proof of COVID-19 vaccination, past infection, or a
recent negative test required to visit a series of places),
and the circulating strain (see supplementary methods
for further description of periods and non-pharmaceuti-
cal interventions throughout the study).
Statistical analysis
For a better matching of controls with cases on the tim-
ing of exposure, considering that controls were initially
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Galmiche et al. BMC Public Health (2024) 24:2411
included after the screening of cases, we proceeded to
an exact matching procedure of four cases for one con-
trol on the calendar week of the outcome date (symptom
onset or testing if asymptomatic for cases, questionnaire
completion for controls). To account for the random
selection of cases in the matching procedure, as those
outnumbered controls more than four times, we gener-
ated 100 databases of series of four cases matched with
one control for each period.
We fitted unconditional logistic regression models to
estimate the odds ratios of SARS-CoV-2 infection for the
exposures of interest in a model including the matching
variables, as well as health-related variables, including
COVID-19 vaccine status, past SARS-CoV-2 infection,
sociodemographic characteristics (level of education,
socio-professional category) and household description.
e choice of the adjusting variables was guided by sub-
ject matter knowledge to include all measured causes of
the exposures, the outcome (SARS-CoV-2 infection), or
both, relying on the disjunctive cause criterion [22]. e
exposures of interest were included as follows: workplace
(work in an office, open-space arrangement, complete or
partial remote office), gatherings (professional, private,
or religious), retail settings (shops, hairdresser, beauty
salon), shared transport (short-distance or long-dis-
tance transport, car-pooling), and leisure activities (cul-
tural venues, sports facilities, bars, restaurants, parties,
divided into night-clubs or private parties from period 5
onward). No estimate was produced for bars, restaurants,
indoor sports facilities, and cultural venues for periods 2
and 3 as they were mostly closed then (odds ratios were
estimated for the first period thanks to the inclusion of
participants before the start of the stay-at-home orders).
ese models were fitted for each of the 100 databases
per period. We extracted the coefficients, exponentiated
them and retained the median for the point estimate
and the 2.5th and 97.5th percentiles for the 95% confi-
dence interval. In complementary models, we explored
potential interactions of bars, restaurants, and parties
with age categorized as < 40 or ≥ 40 years (p-value for
interaction estimated with the median of the 100 esti-
mates). To investigate how viral circulation in the coun-
try of destination could affect the risk associated with
airplane travel, we calculated the mean daily incidence
rate obtained from Ourworldindata.org in the country of
destination over period 4 (summer of 2021, emergence of
the delta variant) [23].
All statistical analyses were performed using Stata 16.0
(StataCorp, College Station, USA). (See supplementary
methods for further description of statistical analysis.)
Ethics approval
is study received ethics approval from the ethics com-
mittee Comité de Protection des Personnes Sud Ouest et
Outre Mer 1 on September 21, 2020 as required by French
regulation on clinical research. e data protection
authority, the Commission Nationale de l’Informatique et
des Libertés (CNIL) authorized the processing of data on
October 21, 2020. Informed consent was obtained from
all participants.
is report follows the STROBE reporting guidelines
for observational studies.
Results
From October 27, 2020 to October 2, 2022, we sent
11,612,450 email invitations to people with recent SARS-
CoV-2 infection, and included 691,454 cases (6.0%) and
57,065 controls. After exclusion of participants with a
reported episode of infection in the past two months and
cases who responded to the questionnaire over 30 days
after symptom onset, and matching of four cases for
one control, we included 175,688 cases and 43,922 con-
trols (Fig. 1). e main socio-demographic and health
status characteristics are summarized in Table 1. e
study population was characterized by a lower propor-
tion of men (33.8% vs. 47.6% in the general population
aged 20 and over in France), a higher representation of
people aged between 40 and 49 years (26.8% vs. 16.7%)
and of residents of the Ile-de-France region (where Paris
is located) (22.7% vs. 18.3%).
We identified several settings associated with an
increased risk of infection, including professional set-
tings, shops, shared transport, and leisure activities
(Fig.2, Tables S1-S3).
Regarding the workplace, we found a consistently
increased risk associated with working in an open-
space office compared with a non-open-space office
environment (OR range through the nine periods of the
study: 1.12 to 1.57). Remote office was associated with a
decreased risk of infection when done only partially in
the preceding days (0.72 to 0.90), but often not when the
few days spent at the workplace were in an open-space
environment (0.72 to 1.09). e risk varied through the
study for people reporting working fully remotely, with
an OR ranging between 0.67 and 1.64 depending on the
period.
e visit of shops was overall not associated with
any increased risk of infection. e only exceptions are
convenience stores and take-away deliveries for which
the risk remained increased through most of the study
(periods 4 to 9, OR range: 1.15 to 1.44, and 1.07 to 1.28,
respectively). Notably, we found no increased risk in
retail facilities involving closer and longer contacts such
as hairdressers or beauty salons.
Analyses on shared transport show that most short-
distance transport such as buses, tramways or short-dis-
tance trains did not increase the risk of infection, except
for the metro in which the risk was regularly moderately
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Galmiche et al. BMC Public Health (2024) 24:2411
increased (periods 3, and 7 to 9, OR range: 1.07 to 1.19).
On the other hand, long-distance trains and airplanes
were associated with a notably increased risk, consis-
tently for train (1.25 to 1.88) and for most of the study for
airplanes (periods 2 to 6, and 9, OR range: 1.20 to 1.78).
e models were adjusted on abroad travel, suggesting
that the effect for airplane was not mediated through visit
to a high-incidence country. In a sensitivity analysis, the
risk for airplane travel remained increased after adjust-
ment on the mean incidence in the country of destination
(period 4: OR 1.58, 95%CI 1.41–1.78, compared with OR
1.67, 95%CI 1.52–1.88 without adjustment). Car travels
also appeared to favor transmission in certain circum-
stances, with increased risks for taxi rides throughout the
study in the periods when they were investigated (periods
3 to 9, OR range: 1.08 to 1.89), as well as for car-pooling,
but only when traveling with relatives (periods 4 to 9, OR
range: 1.09 to 1.68), not when the car-pooling was orga-
nized with unrelated persons through a dedicated plat-
form (periods 4 to 9, OR range: 0.45 to 0.59).
Of all the cultural and sports facilities we investigated,
we found an increased risk mainly for the attendance of
concerts (periods 5 to 9, OR range: 1.31 to 2.09), and less
consistently for theatres (periods 6, 7, and 9, OR range:
1.20 to 1.45) and the practice of sports indoors (periods 1,
5, and 7, OR range: 1.11 to 1.23). We found no increased
risk associated with other settings such as museums,
movie theatres, swimming pools, or martial arts facilities.
We initially identified an increased risk associated
with bars and restaurants (as the questionnaire did not
distinguish them at first): period 1, OR 1.97 (95%CI
1.84–2.07). As bars and restaurants reopened in the
spring of 2021, we found an increased risk for bars (OR
1.57, 95%CI 1.50–1.64) but not for restaurants (OR 0.95,
95%CI 0.89–0.99). e risk gradually decreased afterward
for bars, and they were no longer at risk from October
2021 (period 6) onward. However, there were significant
interactions of bars with age categorized as under 40
years or 40 and above, with a persistently increased risk
in those aged under 40 until the first omicron BA.1 wave
(periods 4 to 7, OR range: 1.23 to 2.17) (Tables S5, S6).
Attending parties was initially consistently associated
with an increased risk, particularly in those aged under
40 (periods 1 to 4, OR range: 1.33 to 3.24) (Tables S4, S5).
When we could distinguish private parties from parties
in night-clubs, as those reopened in the summer of 2021,
we found no increased risk for private parties (no inter-
action with age, Tables S5, S6). In contrast, the risk was
high for night-clubs (e.g., in period 6, OR 2.95, 95%CI
2.64–3.28). It decreased gradually through the various
omicron waves in 2022 but remained increased in the
last period of the study (omicron BA.4/5 wave, OR 1.54,
95%CI 1.41–1.66), regardless of the age category (Tables
S5, S6).
Discussion
is case-control study provides a long-term perspective
on the settings most associated with the risk of SARS-
CoV-2 infection in mainland France between October
2020 and October 2022. We identified increased risks for
Fig. 1 Flow chart of participant enrollment and matching of cases and controls. Legend: Study conducted in mainland France between October 2020
and October 2022
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Galmiche et al. BMC Public Health (2024) 24:2411
Total Cases, n (%) Controls, n (%) p-value
175,688 43,922
Male sex 59,380 (33.8) 14,845 (33.8) > 0.99
Age (years)
18–29 21,244 (12.1) 5311 (12.1) > 0.99
30–39 31,888 (18.2) 7972 (18.2)
40–49 47,032 (26.8) 11,758 (26.8)
50–59 37,960 (21.6) 9490 (21.6)
60–69 24,796 (14.1) 6199 (14.1)
≥ 70 12,768 (7.3) 3192 (7.3)
Population in the area of residence
< 5000 inhabitants 44,828 (25.5) 11,207 (25.5) > 0.99
5000–19,999 inhabitants 13,984 (8.0) 3496 (8.0)
20,000–99,999 inhabitants 17,800 (10.1) 4450 (10.1)
Over 100,000 inhabitants 61,956 (35.3) 15,489 (35.3)
Greater Paris area 37,120 (21.1) 9280 (21.1)
Region of residence
Ile-de-France 39,848 (22.7) 9962 (22.7) > 0.99
Auverge-Rhône-Alpes 23,384 (13.3) 5846 (13.3)
Occitanie 17,860 (10.2) 4465 (10.2)
Provence-Alpes-Côte d’Azur and Corsica 15,788 (9.0) 3947 (9.0)
Grand Est 15,336 (8.7) 3834 (8.7)
Nouvelle-Aquitaine 15,132 (8.6) 3783 (8.6)
Hauts-de-France 14,800 (8.4) 3700 (8.4)
Pays de la Loire 8580 (4.9) 2145 (4.9)
Bretagne 8324 (4.7) 2081 (4.7)
Normandie 6124 (3.5) 1531 (3.5)
Bourgogne-Franche-Comté 5876 (3.3) 1469 (3.3)
Centre-Val de Loire 4636 (2.6) 1159 (2.6)
Education level
No diploma 3682 (2.1) 767 (1.7) < 0.001
Pre-high school diploma 25,995 (14.8) 7722 (17.6)
High-school diploma 31,741 (18.1) 10,559 (24.0)
Bachelor’s degree 62,909 (35.8) 16,340 (37.2)
Master’s degree or higher 45,149 (25.7) 7056 (16.1)
Missing 6212 (3.5) 1478 (3.4)
Health conditions
Diabetes mellitus 6157 (3.5) 2304 (5.2) < 0.001
Hypertension 20,476 (11.7) 5773 (13.1) < 0.001
Chronic respiratory disease 14,650 (8.3) 3132 (7.1) < 0.001
Coronary artery disease 2114 (1.2) 431 (1.0) < 0.001
Body-mass index (kg/m²)
Healthy weight (≥ 18.5 & <25) 89,392 (50.9) 20,909 (47.6) < 0.001
Underweight (< 18.5) 5409 (3.1) 1880 (4.3)
Overweight (≥ 25 & <30) 52,824 (30.1) 13,111 (29.9)
Obesity (≥ 30) 28,061 (16.0) 8023 (18.3)
Housing
Individual house 106,786 (60.8) 25,775 (58.7) < 0.001
Apartment 68,223 (38.8) 18,004 (41)
Shelter 585 (0.3) 118 (0.3)
Nursing home 92 (0.1) 25 (0.1)
Living with a child
Attending daycare 4946 (2.8) 928 (2.1) < 0.001
Table 1 Socio-demographic description of the study population (case-control study in mainland France, October 2020 to October
2022)
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Galmiche et al. BMC Public Health (2024) 24:2411
on-site office work, particularly in open space environ-
ments, professional meetings, concerts, theatres, long-
distance public transit, as well as bars and night-clubs.
On the other hand, we found no increased risk for most
sports and cultural activities, religious gatherings, shops,
and short-distance public transport.
All settings associated with an increased risk of infec-
tion in our study are characterized by varying degrees of
common characteristics: mostly indoor settings with lit-
tle air renewal, where contacts are close, numerous, often
maskless, sometimes including singing or shouting, and
usually last more than a mere few minutes. ese fac-
tors are in line with knowledge on the conditions allow-
ing transmission of SARS-CoV-2, through direct contact,
large droplets, or fine aerosols [9, 24], often indoors [25].
Apart from bars, restaurants, and night-clubs for which
the risk decreased through the course of the study, the
associations remained overall relatively stable. Following
the implementation of the sanitary pass in most indoor
places and long-distance transport in August 2021
(period 5 onwards), we observed a slight decrease in the
risk associated with airplane travel, long-distance train,
and bars, suggesting the sanitary pass contributed to
decrease the risk of transmission in those environments.
e odds ratios increased again in period 6 (October 2
to December 19, 2021). While this increase must be
interpreted with caution given its limited amplitude, it
may also result from a rapidly waning vaccine effective-
ness on SARS-CoV-2 transmission [26], as the majority
of the adult population was vaccinated between June and
August 2021. Other factors could explain the decrease of
the risk for bars and restaurants: night-clubs were closed
from March 2020 until July 2021, and people may have
been more prone to attend parties with closer and longer
interactions in bars and restaurants during that time than
in the later periods. e interaction of parties and bars
Total Cases, n (%) Controls, n (%) p-value
175,688 43,922
Attended for by a professional in-home caregiver 5772 (3.3) 904 (2.1) < 0.001
Attending preschool 16,467 (9.4) 3327 (7.6) < 0.001
Attending primary school 29,027 (16.5) 6185 (14.1) < 0.001
Attending middle school 26,795 (15.3) 6183 (14.1) < 0.001
Attending high school 21,990 (12.5) 5447 (12.4) 0.54
Attending university 14,711 (8.4) 4075 (9.3) < 0.001
Past SARS-CoV-2 infection
No past infection 165,798 (94.4) 37,376 (85.1) < 0.001
Past infection 61–180 days 8085 (4.8) 2968 (7.1)
Past infection > 180 days 1805 (1.1) 3578 (8.5)
COVID-19 vaccine, time since last dose
Unvaccinated 49,989 (28.5) 13,503 (30.7) < 0.001
1 dose, < 90 days 3288 (2.0) 870 (2.1)
1 dose, 90–179 days 552 (0.4) 260 (0.7)
1 dose, > 179 days 615 (0.4) 264 (0.8)
2 doses, < 90 days 7301 (4.9) 3024 (8.1)
2 doses, 90–179 days 13,718 (9.2) 3150 (8.5)
2 doses, > 179 days 7254 (5.2) 2092 (6.0)
3 doses, < 90 days 26,324 (17.7) 6794 (18.3)
3 doses, 90–179 days 40,047 (32.4) 6810 (22.0)
3 doses, > 179 days 16,697 (13.5) 2925 (9.5)
4 doses, < 90 days 2728 (2.4) 560 (2.0)
Missing date of last dose 7162 (4.8) 3669 (9.9)
Study period (onset date)
1 (10/01/2020) 7308 (4.2) 1827 (4.2)
2 (12/04/2020) 19,636 (11.2) 4909 (11.2)
3 (04/09/2021) 9008 (5.1) 2252 (5.1)
4 (06/14/2021) 11,264 (6.4) 2816 (6.4)
5 (08/14/2021) 4820 (2.7) 1205 (2.7)
6 (10/02/2021) 11,248 (6.4) 2812 (6.4)
7 (12/20/2021) 44,136 (25.1) 11,034 (25.1)
8 (03/18/2022) 39,652 (22.6) 9913 (22.6)
9 (05/20/2022) (end date: 10/02/2022) 28,616 (16.3) 7154 (16.3)
Table 1 (continued)
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Galmiche et al. BMC Public Health (2024) 24:2411
Fig. 2 Adjusted odds ratios of SARS-CoV-2 infection in a case- control study in France. Legend: The study period was divided in nine shorter study periods
based on incidence, the circulating strains (two strains are indicated when the period includes the rise of a new strain), and the main non-pharmaceutical
interventions. The colors of the cells refer to 95% condence intervals’ width: in shades of blue if the upper bound of the 95% CI is < 1, in shades of red
if the lower bound of the 95% CI is > 1. Cells are uncolored if the 95% condence interval includes 1. The empty cells reect the modications of the
questionnaire through the course of the study. Cases and controls were matched with a 4:1 ratio on sex (female or male), age (in 10-year-age categories),
region, size of population of the area of residence, and week of exposure. To account for random selection of cases as those outnumbered controls more
than four times, we generated 100 databases for each period with matched sets of 4 cases per control. The odds ratios were estimated in multivariable
logistic regression models for each of the periods, adjusting for all the variables shown in the gure as well as the matching variables, household char-
acteristics (number of people in the household, presence of children, type of housing), professional category, health status (body-mass index, smoking
status, hypertension, diabetes mellitus, chronic respiratory disease, coronary artery disease, immunosuppression), past episode of infection (categorized
as 61–180 days prior or > 180 days prior), and COVID-19 vaccine status (number of doses and time since last dose divided in < 90 days, 90–179 days, ≥
180 days). The odds ratio and the 95% condence intervals estimates were inferred through the 50th, 2.5th, and 97.5th percentiles of the 100 estimates
for each period. All variables shown here are dummy variables except for one combined variable regarding the workplace. (a): The stay-at-home orders
started on 10/30/2020; bars, restaurants, night-clubs, non-essential shops, and cultural venues were then closed. (b): The sanitary pass was a proof of vac-
cine, past infection, or a recent negative test to enter a series of public spaces; the vaccine pass was implemented on 01/24/2022 to include only proofs
of vaccine or past infection. (c): Estimated in people exposed before the start of the stay-at-home orders on 10/30/2020
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 8 of 11
Galmiche et al. BMC Public Health (2024) 24:2411
with age, with higher odds ratios observed for people
aged under 40, suggests the role of behavioral patterns
in those environments. e summer of 2021 was also
characterized by an important football European com-
petition, during which public viewing in bars was popu-
lar and likely contributed to viral circulation. Another
hypothesis is that the transmission of the more conta-
gious delta and omicron variants did not require as favor-
able conditions as the previous strains, leading to a less
differentiated risk between people visiting these settings
and people who avoided them. Studies on the evolution
of settings of transmission through the emergence of the
various strains in other countries would help explore this
hypothesis.
Findings of other studies on settings of transmission
are overall consistent with ours. e decreased risk for
people reporting working remotely was also shown in
several other studies [16, 27–29], whereas the role of
open-space offices has been little studied [30]. e fact
that people working in open-space offices while also
working partially remotely were not at lower risk of infec-
tion suggests that the benefit of remote office was offset
by the increased risk in open-space offices. e vary-
ing results for complete remote office suggest residual
confounding in our analysis; these people were possibly
exposed to SARS-CoV-2 transmission in other settings
that they were more likely to visit, or in the household, in
ways that our models could not account for. e absence
of increased risk for retail facilities, as well as hairdress-
ers and beauty salons, also reported by others [14–17,
27, 31–33], suggests that these facilities had low enough
density and stringent enough measures to effectively
limit transmission. Findings on shared transport, often
studied altogether without distinction of the duration
of the trip, have yielded conflicting evidence [12, 14, 27,
32, 34, 35]. A contact-tracing study on air travel in Ire-
land has underlined the role of the duration of the flight,
with secondary attack rates reaching 14.9% for flights
lasting over 5h vs. 6.3% for shorter ones [36]. e con-
trast we found between short- and long-distance shared
transport supports the importance of the duration spent
onboard. Long-distance bus travels were inconsistently at
increased risk, which might result from better air renewal
Fig. 2 (Continued)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 9 of 11
Galmiche et al. BMC Public Health (2024) 24:2411
during the mandatory driving breaks compared to other
shared transport.
Consistent with several other studies, we found no
increased risk for cultural venues, sports facilities, and
religious gatherings, apart from a slightly increased risk
in theaters, concerts, and indoor sports facilities [14, 15,
17, 27, 31, 37]. Findings on dining and partying venues
often reported an increased risk for bars [14, 15, 17, 27,
38, 39], night-clubs and parties [17, 27, 39], whereas find-
ings are more conflicted for restaurants [15, 27, 31, 32,
38, 40]. In a case-control study in Denmark conducted in
June 2021, Munch and colleagues found an increased risk
for the attendance of restaurants or cafés only for peo-
ple reporting alcohol consumption [31]. is highlights
the role of behaviors within those settings on the risk of
transmission. Two randomized trials conducted in France
found no increased risk of SARS-CoV-2 infection in par-
ticipants of mass gatherings with strict requirements for
attendance, one at a concert [41] and one in a nightclub
[42]. ese experimentations offer clues for continuation
of mass indoor gatherings in case of an emerging respira-
tory pathogen.
Our findings suggest a graduation in the risk of trans-
mission which combines degree of air renewal and
behaviors. We did not observe excess transmission in
indoor places where consistent mask-wearing was pos-
sible such as museums, movie theatres, shopping malls,
or beauty salons. In bars and restaurants, reopening in
mid-2021 was associated with recommendations for
spacing tables and opening doors and windows. In this
context, increased risk of transmission was observed
only for those younger than 40 years of age, or during
special events like the European soccer championship,
suggesting that opening doors and windows might have
been protective provided individuals avoided staying too
close to one another, and talking loudly or shouting. In
closed spaces where opening doors and windows may
be absent or limited, and mask wearing not maintained
systematically (e.g., during meals in long-distance trains,
or drinks in night-clubs), increased risk of transmission
was observed. In such places, investment in improving
air renewal or filtration would be essential to improve
air quality and decrease transmission risk. ese invest-
ments are costly but have potential long-term benefits on
population health [43] and should be properly evaluated
for their feasibility and effectiveness.
e main limitation of the present study lies in the low
participation rate (6.0%). As in other studies conducted
online, we observed notable differences between our
study population and the source population: we included
a more female population, often in intermediary age
groups, and with a higher education level [44, 45]. ese
demographic factors were included in our matching
procedure or in the adjusted models, thus limiting the
risk of recruitment bias. is does however decrease
the generalizability of our findings. Furthermore, unex-
pected findings such as the intermittently increased risk
associated with complete remote office, with take-away
delivery, or the decreased risk for supermarkets illus-
trate potential recruitment bias, residual confounding,
or result from the multiplicity of comparisons. ese
biases are difficult to avoid entirely in a case-control
study. We chose this design nonetheless as it enabled us
to modify the questionnaire whenever necessary (intro-
ducing questions on the vaccine status, variants, etc.).
It provided results soon after the beginning of the study
which helped evidence-based decision-making in a time
of high burden of SARS-CoV-2 in France [18, 20]. Since
the incubation period of COVID-19 only lasts a few days,
we considered the risk of recall bias, a frequent limitation
of case-control studies, would be low, although we can-
not rule out that cases recalled exposures more precisely
than controls as they retrospectively tried to identify the
circumstances of infection. Cases and controls differed
significantly regarding past infection status, an inclusion
bias whose impact was likely mitigated by the adjustment
on past infection status in the multivariable models. e
consistency of the present findings with those of other
studies using different designs, such as cross-sectional
seroprevalence estimates or prospective cohorts, also
supports the validity of our approach. Despite signifi-
cant power, our study could not assess finer exposures
or behaviors associated with certain settings. We can-
not exclude for instance that the increased risk associ-
ated with train or air travel was caused by exposures at
the train station or the airport, or that specific partying
venues might have been safe provided they implemented
distancing or testing practices.
Overall, this case-control study shows that the work-
place, long-distance shared transport, and several leisure
activities were likely settings of effective SARS-CoV-2
transmission during the pandemic in mainland France.
ese findings will help focusing efforts on improve-
ment in air quality and inform pandemic preparedness
strategies.
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12889-024-19651-y.
Supplementary Material 1
Acknowledgements
We thank all those who participated in the study. We thank the Caisse
nationale d’assurance maladie, in particular Sophie Martin, Anne Lévy,
and Carole Blanc for their collaboration. We thank the Ipsos public aairs
department, particularly Nathan Jeandet. We also thank Cassandre von
Platen at the Clinical research coordination oce at the Institut Pasteur.
This study has been labeled as a National Research Priority by the National
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 10 of 11
Galmiche et al. BMC Public Health (2024) 24:2411
Orientation Committee for Therapeutic Trials and other research on Covid-19
(CAPNET). The investigators would like to acknowledge ANRS | Emerging
infectious diseases for their scientic support, the French Ministry of Health
and Prevention and the French Ministry of Higher Education, Research and
Innovation for their funding and support.
Author contributions
AF, SG, TC, FO, CD, FC, and AM designed the investigation.SG, TC, AF, and AM
developed the study questionnaire.TC, FO, and CD managed the online data
collection.OC, SG, and TC oversaw the adherence of the study to regulatory
requirements.TC oversaw the collection of the data and maintained the
database.SG, TC, AR and AF performed the statistical analyses.SG and AF
drafted the rst versions of the manuscript.SG, TC, AR, and AF had full access
to the data reported in this study.SG and AF take responsibility for the integrity
of the data and the accuracy of the data analysis.All authors critically reviewed
and approved the nal version of the manuscript.
Funding
The study was funded by Institut Pasteur, Research, Action Emerging
Infectious Diseases (REACTing), and the French Agency Agence nationale
de recherches sur le sida et les hépatites virales - Maladies Infectieuses
Emergentes (ComCor project). AF’s laboratory receives support from the LabEx
Integrative Biology of Emerging Infectious Diseases (IBEID) (ANR-10-LABX-
62-IBEID) and the INCEPTION project (PIA/ANR-16-CONV-0005) for studies on
emerging viruses. SG is funded by the INCEPTION program “Investissement
d’Avenir grant ANR-16-CONV-0005”.
Data availability
The data that support the ndings of this study are available from Institut
Pasteur. Restrictions apply to the availability of these data, which were used
under authorized agreement for this study from the data protection authority,
the Commission Nationale de l’Informatique et des Libertés (CNIL). Access to
these pseudonymized data would therefore require prior authorization by the
CNIL.
Declarations
Ethics approval and consent to participate
This study was performed in line with the principles of the Declaration of
Helsinki. This study received ethics approval from the ethics committee Comité
de Protection des Personnes Sud Ouest et Outre Mer 1 on September 21, 2020,
as required by French regulation on clinical research. Informed consent was
obtained from all participants included in the study.
Consent for publication
Not applicable.
Competing interests
Fabrice Carrat declares consulting fee from Sano on inuenza epidemiology.
Authors declare no further interests.
Received: 18 January 2024 / Accepted: 30 July 2024
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