IntroductionSocio-demographic factors are known to influence epidemic dynamics. The town of Nice, France, displays major socio-economic inequalities, according to the National Institute of Statistics and Economic Studies (INSEE), 10% of the population is considered to live below the poverty threshold, i.e.60% of the median standard of living.ObjectiveTo identify socio-economic factors related to the incidence of SARS-CoV-2 in Nice, France.MethodsThe study included residents of Nice with a first positive SARS-CoV-2 test (January 4-February 14, 2021). Laboratory data were provided by the National information system for Coronavirus Disease (COVID-19) screening (SIDEP) and socio-economic data were obtained from INSEE. Each case’s address was allocated to a census block to which we assigned a social deprivation index (French Deprivation index, FDep) divided into 5 categories. For each category, we computed the incidence rate per age and per week and its mean weekly variation. A standardized incidence ratio (SIR) was calculated to investigate a potential excess of cases in the most deprived population category (FDep5), compared to the other categories. Pearson’s correlation coefficient was computed and a Generalized Linear Model (GLM) applied to analyse the number of cases and socio-economic variables per census blocks.ResultsWe included 10,078 cases. The highest incidence rate was observed in the most socially deprived category (4001/100,000 inhabitantsvs2782/100,000 inhabitants for the other categories of FDep). The number of observed cases in the most social deprivated category (FDep5:N= 2019) was significantly higher than in the others (N= 1384); SIR = 1.46 [95% CI:1.40–1.52;p< 0.001]. Socio-economic variables related to poor housing, harsh working conditions and low income were correlated with the new cases of SARS-CoV-2.ConclusionSocial deprivation was correlated with a higher incidence of SARS-CoV-2 during the 2021 epidemic in Nice. Local surveillance of epidemics provides complementary data to national and regional surveillance. Mapping socio-economic vulnerability indicators at the census block level and correlating these with incidence could prove highly useful to guide political decisions in public health.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12889-023-15917-z.