The data we analyzed are those available in the Population Screening Information System (SI-DEP) (see box). For our study, we considered the 70,990,478 RT-PCR tests for SARS-CoV-2 detection—including 5,000,972 positive results—recorded in this database between May 14, 2020, and May 5, 2021. The places of residence for each person who underwent an RT-PCR test were geocoded at the IRIS level, allowing us to assign a deprivation index to each of these geographic units. An IRIS is a geographic zone comprising approximately 2,000 people who are socioeconomically homogeneous.

We then calculated, for each week and at the level of each IRIS, three indicators standardized by age and sex: the incidence rate, the positivity rate, and the testing rate.

Social inequalities in health (SIH) are studied using deprivation indicators. Two of these are currently available at the IRIS level for the entire national territory: the FDEP (French DEPrivation Index) (2) and the EDI (European Deprivation Index). We used the latter, calculated based on the 2015 EDI, which consists of 10 environmental variables (relating to family composition, housing, and work, and defined at the level of a region, a locality, etc.) derived from census data and linked to individual deprivation levels. For each IRIS, the following percentages are thus taken into account: of foreign nationals, households without a car, people who are neither managers nor in intermediate professions, single-parent families, households with at least two people, households that do not own their housing, unemployed people, people without higher education (post-secondary), overcrowded housing, and unmarried people. This index is then categorized for each IRIS into five levels called quintiles, ranging from the lowest to the highest level of deprivation. The first quintile represents the most advantaged individuals, and the fifth the most disadvantaged.

SI-DEP at a Glance

SI-DEP (Population Screening Information System) is a surveillance system established on May 13, 2020, to track all tests (RT-PCR and antigen tests) performed in France for SARS-CoV-2 screening by private and hospital laboratories, pharmacies, nurses, and doctors. This database contains pseudonymized data regarding the patient (age, sex, place of residence) and the test (date of sample collection, result). The place of residence is geocoded to obtain the IRIS (Clustered Islands for Statistical Information).
This data is used to calculate incidence rates, positivity rates, and testing rates to monitor the progression of the epidemic in France at the national, regional, departmental, and sub-departmental levels.

Our findings show that individuals living in the most disadvantaged areas have the highest risk of infection and the lowest rate of testing. These results may reflect structural factors contributing to inequalities in access to healthcare in France and a reduced ability for disadvantaged populations to benefit from measures to protect against infection.

People living in the most disadvantaged areas had higher incidence and positivity rates and lower testing rates than those living in the least disadvantaged areas, with variations depending on population density.

In densely populated municipalities (>= 1,500 inhabitants/km²) and moderately populated municipalities (between 300 and 1,500 inhabitants/km²), the incidence and positivity rates for SARS-CoV-2 infection in the most socially disadvantaged areas were higher (1.148 (95% CI 1.138–1.158) and 1.283 (1.273–1.294), respectively) than in the more advantaged areas. The SARS-CoV-2 testing rate in the most socially disadvantaged areas was lower than in the more advantaged areas (0.905 (95% CI 0.904–0.907); with an unusual finding in studies on the ISS, which most often describe a linear gradient between quintiles: here, we observe a clear break between the fifth quintile (the most disadvantaged) and the other four quintiles. This result shows that in densely and moderately populated areas, the most disadvantaged 20% of the population bore the heaviest burden of the pandemic.

These differences are not found in sparsely or very sparsely populated municipalities (< 300 inhabitants/km²). The incidence rate and testing rate were lower in the bottom four quintiles of deprivation than in the top quintile. As for the positivity rate, it remained stable across all quintiles.

Furthermore, regarding the weekly trends of the three indicators, we observed that during the second and third lockdowns (October 29 to December 14, 2020, and April 3 to May 2, 2021), incidence and positivity rates were higher in the most disadvantaged neighborhoods within moderately and densely populated municipalities. In sparsely populated municipalities, the results were more mixed: incidence and positivity rates were higher in the most disadvantaged neighborhoods at the end of lockdown. The testing rate fluctuated during both lockdowns, regardless of the municipality’s population density. It should be noted, however, that it was higher in the most disadvantaged neighborhoods of sparsely and moderately populated municipalities during the third lockdown, but higher in the affluent neighborhoods of densely populated municipalities.

These findings can be explained by the influence of key social determinants of health, such as demographic, environmental, and socioeconomic factors (housing conditions, income, and employment), which play a decisive 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 jobs involving greater contact with the public and with fewer opportunities for teleworking—and are therefore at higher risk—which means 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 protective measures (particularly lockdowns). These findings highlight the role of structural determinants of health—particularly salient during the COVID-19 crisis—and the importance of monitoring changes in social inequality indicators over time when implementing prevention policies. An initiative is underway at Santé publique France to more systematically integrate social variables into surveillance systems and, thereby, the issue of social health inequalities. Integrating social variables will provide a better understanding of the role of social determinants in the burden of disease.
The goal is to integrate the well-being of disadvantaged social groups into all public health policies and to more effectively direct public health research and interventions toward these key issues of social inequality.

With the aim of combating COVID-19 among highly vulnerable populations, Santé publique France has launched a knowledge mobilization and sharing initiative (MobCo) involving more than 120 researchers, field practitioners, and decision-makers. The objective of this initiative is to collectively define appropriate approaches and courses of action, including COVID-19 testing and vaccination.
This initiative is part of one of the major priorities of Santé publique France’s work program, namely “Health inequalities and territorial vulnerabilities.” This priority echoes the recent publication of the Rio de Janeiro Call by IANPHI (International Association of National Public Health Institutes) on the role of national public health institutes in the fight against inequality.

The Rio de Janeiro Call, IANPHI, and Santé publique France

The recently published Rio de Janeiro Declaration by IANPHI (International Association of National Public Health Institutes) places national public health institutes at the heart of the fight against health inequalities. This text, initiated at the 2021 IANPHI annual meeting at the Oswaldo Cruz Foundation, Brazil’s public health agency (hence its name), was widely shared with its members and then reviewed by its board of directors.

“The post-pandemic period will offer a unique opportunity to prioritize the goal of reducing health inequities, a goal that must be shared by all national public health agencies, which are, in this regard, the key actors.”

IANPHI member organizations are invited to place the promotion of health equity at the heart of their work. Documenting existing inequalities through surveillance or dedicated observatories, measuring progress, and evaluating the effectiveness of interventions aimed at reducing these health inequalities, as well as supporting their implementation: these are the steps that must be taken to win this fight. This call also addresses decision-makers and policymakers, urging them to support the implementation and evaluation of these interventions.

This call echoes the theme of “health inequalities and territorial vulnerabilities” in the work program of Santé publique France, which serves as the scientific secretariat for IANPHI.

Learn more:

• The Rio de Janeiro Call

• IANPHI and Santé publique France