The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France between May 2020 and April 2021

Publié le 11 mai 2022

The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France between May 2020 and April 2021 / L’impact de la défavorisation sociale sur la dynamique d’infection au SARS-CoV-2 en France entre mai 2020 et avril 2021.

We are now aware of how the COVID-19 health crisis brings existing social inequalities into sharper focus. People who are more socially disadvantaged have a higher risk of SARS-CoV-2 infection and of developing severe forms of COVID-19. The underlying mechanisms include differential exposure to the virus, greater susceptibility to infectious diseases and associated complications, and unequal access to care.

In France, seroprevalence studies have shown that during the first wave of the COVID-19 pandemic (March to May 2020), the risk of SARS-CoV-2 infection was twice as high in the most deprived urban neighbourhoods and among people living in collective housing, in closed institutions or in overcrowded accommodation (1).

Tracking the pandemic in real time and according to the diverse socio-economic characteristics of the general population requires data on individual social characteristics. In France, as in many other countries, there is a lack of such data in medical records and surveillance system databases. A few ad-hoc surveys describe the situation during the first two lockdowns, but studies investigating the temporal dynamics of SARS-CoV-2 incidence in relation to social inequalities, at national level and since the beginning of the pandemic, are scarce. In the report entitled "The COVID-19 health crisis and health inequity", published in October 2021, the French public health authority (Haut Conseil de la Santé Publique) concludes: "The management of the crisis has retained a biomedical character despite its major impact beyond the infectious aspect. During the crisis, health equality has remained a secondary objective" (2).

The study published this month in The Lancet Public Health [1], conducted by Santé publique France and the Inserm EQUITY team at CERCOP (Epidemiology and Population Health Research Centre), is the first to describe the dynamics of the SARS-CoV-2 pandemic in France between May 2020 and April 2021 in relation to social deprivation, using a national database.

Three questions for:  Stéphanie Vandentorren, Santé Publique France

Stéphanie Vantendorren

The objective of your study was to analyse health inequalities in relation to the dynamics of the pandemic in France between May 2020 and April 2021. What was your approach and methodology?

The data we analysed were those available in the Système d'Information de DEpistage Populationnel (SI-DEP: see box). Our study took into account the 70,990,478 RT-PCR tests for the detection of SARS-CoV-2 recorded in this database during the period from 14 May 2020 to 5 May 2021, of which 5,000,972 were positive. The places of residence of each person who had an RT-PCR test were geo-coded at the IRIS level [aggregated units for statistical information], making it possible to assign a deprivation index to each of these geographical units. The IRIS is a geographical area including approximately 2,000 people of similar socio-economic status.

For each week and at the level of each IRIS, we then calculated three age- and sex-standardised indicators: the incidence rate, the positivity rate and the screening rate. 

Health inequalities are studied by means of deprivation indicators. Two such indicators are currently available at the IRIS level for the whole of France: the FDEP (French DEPrivation Index) (2) and the EDI (European Deprivation Index). We used the latter, calculated from the EDI of 2015, which is composed of 10 ecological variables (relating to family composition, housing and work, and defined at the level of a given area, place, etc.) derived from census data and associated with a level of individual deprivation.  For each IRIS, percentages of the following categories are thus taken into account: people of foreign nationality, households without a car, people who do not hold managerial or intermediate occupations, single-parent families, households consisting of at least two people, households that do not own their home, unemployed people, people with no higher education, overcrowded housing, unmarried people. This index is then classified for each IRIS according to five levels called quintiles, ranging from the lowest to the highest level of deprivation. The first quintile represents the most advantaged people and the fifth the most disadvantaged. 

Box: What is SI-DEP ?

SI-DEP (Système d'Information de DEpistage Populationnel) is a French information system for population screening. This surveillance system was set up on 13 May 2020 to monitor all RT-PCR and antigenic tests for SARS-CoV-2 carried out by the country’s biological laboratories, pharmacies, nurses and doctors. This database contains pseudonymised data concerning the patient (age, sex, place of residence) and the test (date of sampling, result). The place of residence is geocoded to obtain aggregated units for statistical information known as IRIS (Îlots Regroupés pour l’Information Statistique). 
These data are used to calculate incidence rates, positivity rates and screening rates for monitoring the development of the epidemic in France at national, regional, departmental and sub-departmental levels.


What are the main findings of your study? What is new and original about your results compared to previous knowledge ?

Our results show that individuals living in the most deprived areas have the highest risk of infection and the lowest screening rate. These results may reflect structural factors of inequality in access to care in France and a reduced ability for disadvantaged populations to benefit from protective measures against infection.
People living in the most deprived areas showed higher incidence and positivity rates and lower screening rates than those living in the least deprived areas, with variations according to population density.

In densely populated (≥1,500 inhabitants/km2) and moderately populated (300–1,500 inhabitants/km2) municipalities, the incidence and positivity rates of SARS-CoV-2 infection were higher in the most socially deprived areas than in the most advantaged areas (1.148 [95%CI 1.138–1.158] and 1.283 [1.273-1.294] respectively). The SARS-CoV-2 screening rate in the most deprived areas (0.905 [95%CI 0.904–0.907]) was lower than in the most advantaged areas, and an observation uncommon for health inequality studies was made : where a linear gradient between quintiles is usually described, here we observe a real drop-off between the fifth (most deprived) quintile and the other four quintiles. This result shows that in densely and moderately populated areas, the poorest 20% of the population paid the highest price for the pandemic. 

These differences were not found in municipalities with a low/very low population density (<300 inhabitants/km2). The incidence and screening rates were lower in the last four deprivation quintiles than in the first quintile. The positivity rate remained stable in all quintiles.

Furthermore, concerning the weekly dynamics of the three indicators, we found that during the second and third lockdowns (29 October to 14 December 2020 and 3 April to 2 May 2021), the incidence and positivity rates were higher in the most deprived neighbourhoods of moderately and densely populated districts. In low-density municipalities, the results were more variable, with higher incidence and positivity rates in the most deprived neighbourhoods at the end of lockdown. The screening rate fluctuated during the two lockdowns, regardless of the density typology of the municipalities. However, it was higher in the most deprived neighbourhoods of low and moderately populated municipalities during the third lockdown, but higher in advantaged neighbourhoods of dense municipalities.

What are the main implications in terms of public health ? How does Santé publique France intend to make use of these results? What approaches or actions are being studied to address this issue of deprivation and to tackle health inequalities ?

These results can be explained by the effect of key social determinants of health, such as demographic factors, environmental factors and socio-economic factors (housing conditions, income, employment), which play a key role in the risk of SARS-Cov-2 infection. People living in densely populated communities also often live in overcrowded housing due to socio-spatial segregation, and are more likely to work in occupations that involve close contact with the population and fewer opportunities for teleworking. This means that it was more difficult for them to protect themselves during lockdowns.

Certain populations are thus extremely exposed to the risk of infection and its consequences in terms of morbidity, and are less protected by collective measures (notably lockdown). These results emphasise the role of structural health determinants, which are particularly significant during this COVID-19 crisis, and the importance of monitoring social inequality indicators over time when implementing prevention policies. An initiative is underway at Santé publique France to integrate social variables more systematically into surveillance systems, thus addressing the issue of health inequalities. Incorporating social variables will improve our knowledge of how social determinants affect the burden of disease.

The aim is to integrate the well-being of socially disadvantaged groups into any public health policy, and to direct public health research and interventions more effectively towards these key issues of social inequalities. 

In order to tackle the issue of COVID-19 among populations experiencing social precarity, Santé publique France launched a knowledge mobilisation and sharing initiative (MobCo) involving more than 120 researchers, field workers and decision-makers. The aim of this approach is to collectively define appropriate methods and strategies, notably for screening and vaccination against COVID-19. 

This project corresponds to one of the major challenges identified in the Santé publique France programme of work, namely "Health inequalities and regional vulnerabilities". This issue echoes the recent publication of the Rio de Janeiro Statement by IANPHI (International Association of National Public Health Institutes) on the role of national public health institutes in the fight against inequity (see box below).

The Rio de Janeiro Statement, IANPHI and Santé publique France

The Rio de Janeiro Statement, recently published by IANPHI (International Association of National Public Health Institutes), calls on national public health institutes to play a central role in the fight against health inequalities. The text was introduced during IANPHI's 2021 annual meeting at the Oswaldo Cruz Foundation, Brazil's public health agency (hence the title), where it was widely shared among the members and then reviewed by the board. 

The post-pandemic recovery will offer a unique and timely opportunity to make reducing health inequities a priority and national public health institutes can play a major role.

IANPHI's member organisations are urged to place the promotion of health equity at the core of their work. Documenting existing inequalities through surveillance or dedicated observatories, measuring progress and assessing the effectiveness of interventions to reduce health inequities, supporting the implementation of such schemes: these are the steps to be taken to win this fight. This call is also addressed to decision-makers and politicians, in order to gain their support in the deployment and evaluation of these actions.

This statement echoes the "Social Inequalities and Territorial Vulnerabilities" challenge in the work programme of Santé publique France, the institute that currently hosts the scientific secretariat for IANPHI.

For more information:

For more information

See also


[1] Vandentorren S, Smaïli S, Chatignoux E, Maurel M, Alleaume C, Neufcourt N, et al. The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France between May 2020 and April 2021.  Lancet Public Health 2022. 

Article commentary : 

1 Bajos N, Jusot F, Pailhé A, 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, 12 April 2021, 2021. ((accessed 25 Oct 2021).

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