Health Impacts of the COVID-19 Lockdown Measure in a Low Socio-Economic Setting: A Cross-Sectional Study on Reunion Island.

In March 2020, the French government implemented nation-wide measures to reduce social contact and slow the progression of the emerging coronavirus responsible for COVID-19, the most significant being a complete home lockdown that lasted 8 weeks. Reunion Island is a French overseas department marked by large social inequalities. We draw the hypothesis that distancing and lockdown measures may have contributed to an increase in the social inequalities in health (SIH) on Reunion Island. The aim of our study was to describe the SIH during lockdown in the Reunionese population. We implemented a cross-sectional telephone survey conducted between 13 May and 22 July 2020, using a retrospective data collection on the lockdown period. A total of 892 adult participants (≥18 years) were recruited in the 114 large Reunionese neighborhoods using the quota method within the national "White Pages" telephone directory. Degraded psychological states, an increase in addictive behaviors, difficulties in accessing food, a decrease in physical activity, delayed medical appointments, violence against women, and health problems in children were driven by the socio-economic characteristics of the population, most often to the disadvantage of social groups exposed to poor living conditions. These results suggest that the COVID-19 lockdown contributed to an increase in SIH.

Neighbourhood socio-economic vulnerability and access to COVID-19 healthcare during the first two waves of the pandemic in Geneva, Switzerland: A gender perspective.

Background: Neighbourhood socio-economic inequities have been shown to affect COVID-19 incidence and mortality, as well as access to tests. This article aimed to study how associations of inequities and COVID-19 outcomes varied between the first two pandemic waves from a gender perspective. Methods: We performed an ecological study based on the COVID-19 database of Geneva between Feb 26, 2020, and June 1, 2021. Outcomes were the number of tests per person, the incidence of COVID-19 cases, the incidence of COVID-19 deaths, the positivity rate, and the delay between symptoms and test. Outcomes were described by neighbourhood socio-economic levels and stratified by gender and epidemic waves (first wave, second wave), adjusting for the proportion of inhabitants older than 65 years. Findings: Low neighbourhood socio-economic levels were associated with a lower number of tests per person (incidence rate ratio [IRR] of 0.88, 0.85 and 0.83 for low, moderate, and highly vulnerable neighbourhood respectively), a higher incidence of COVID-19 cases and of COVID-19 deaths (IRR 2.3 for slightly vulnerable, 1.9 for highly vulnerable). The association between socio-economic inequities and incidence of COVID-19 deaths was mainly present during the first wave of the pandemic, and was stronger amongst women. The increase in COVID-19 cases amongst vulnerable populations appeared mainly during the second wave, and originated from a lower access to tests for men, and a higher number of COVID-19 cases for women. Interpretation: The COVID-19 pandemic affected people differently depending on their socio-economic level. Because of their employment and higher prevalence of COVID-19 risk factors, people living in neighbourhoods of lower socio-economic levels, especially women, were more exposed to COVID-19 consequences. Funding: This research was supported by the research project SELFISH, financed by the Swiss National Science Foundation, grant number 51NF40-160590 (LIVES centre international research project call).

The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France: a population-based analysis.

BACKGROUND: Data on health inequalities related to the dynamic of SARS-CoV-2 infection in France are scarce. The aim of this study was to analyse the association between an area-based deprivation indicator and SARS-CoV-2 incidence, positivity, and testing rates between May 2020 and April 2021. METHODS: We analysed data reported to the Système d'Information de Dépistage Populationnel surveillance system between May 14, 2020 and April 29, 2021, which records the results of all SARS-CoV-2 tests in France. Residential addresses of tested individuals were geocoded to retrieve the associated aggregated units for the statistical information (IRIS) scale, corresponding to an area comprising 2000 inhabitants relatively homogenous in terms of socioeconomic characteristics. A social deprivation score was assigned to each area using the European Deprivation Index (EDI). We fitted negative binomial generalised additive models to model the age-standardised and sex-standardised ratios for SARS-CoV-2 incidence, positivity rates, and testing rates, and to estimate incidence rate ratios (IRRs) and 95% CIs of their association with EDI quintiles, using the first quintile (least deprived) as the reference category, adjusted for week, population density, and region. FINDINGS: Analyses were based on 70 990 478 SARS-CoV-2 tests, of which 5 000 972 were positive. SARS-CoV-2 incidence was higher in the most deprived areas than the least deprived areas (IRR 1·148 [95% CI 1·138-1·158]) and positivity rates were also higher (IRR 1·283 [1·273-1·294]), whereas testing rates were lower in the most deprived areas than the least deprived areas (IRR 0·905 [0·904-0·907]). SARS-CoV-2 incidence and positivity rates remained higher in the most deprived areas than the least deprived areas during the second and third national lockdowns, and variation in testing rate was observed according to population density. INTERPRETATION: Our results highlight a positive social gradient between deprivation and the risk of testing positive for SARS-CoV-2, with the highest risk among individuals living in the most deprived areas and a negative social gradient for testing rate. These findings might reflect structural barriers to health-care access in France and lower capacity of deprived populations to benefit from protective measures. FUNDING: None.

Risk of COVID-19 infection among men and women during the lockdown of spring 2020 in France

BackgroundIn the context of the Covid-19 pandemic, several factors such as age, chronic disease or obesity have been associated with adverse outcomes and mortality from Covid-19. However, the social distribution of Covid-19 infection among men and women was largely neglected in France, mainly due to a lack of data. The aim of this study is to describe and analyse the risk of Covid-19 infection in relation to sex, and the influence of other social factors, specifically occupation, in this association.MethodsWe used data from the citizen science initiative ‘Baromètre Covid-19’. Each week, an internet survey was administered to a sample of 5,000 people representative of the French mainland population aged 18 and over, using the quota method. A total of 25,001 participants were interviewed between 7 April and 11 May 2020. We used multivariable nested logistic regression modelling to study the relationship between sex, occupation and Covid-19 infection. Confounders included age, region of residence, population density, whether you worked outside of home during the lockdown, house overcrowding, comorbidities and body mass index.ResultsWomen reported a medical diagnosis of Covid-19 infection more often than men (4% vs. 3.2%). In a model adjusted for confounders, women were 23% more likely to report a medical diagnosis of Covid-19 infection than men (OR=1.23 [95%-CI=1.06–1.42]). Controlling for sex and socioeconomic variables (occupation), the risk of infection for women was reversed (OR=0.84 [95%-CI=0.59–1.19]). While most men, other than executives, were less likely to report the infection, this association was not observed amongst women.ConclusionOccupation was found to influence the relationship between sex and Covid-19 infection suggesting a gender effect. The differences in the risk of infection between men and women require exploration with regard to socioeconomic factors. The social roles of women and men are associated with a non-random distribution of the virus, potentially reflecting structural societal inequalities.

Risk factors for positive and negative COVID-19 tests: a cautious and in-depth analysis of UK biobank data.

BACKGROUND: The recent COVID-19 outbreak has generated an unprecedented public health crisis, with millions of infections and hundreds of thousands of deaths worldwide. Using hospital-based or mortality data, several COVID-19 risk factors have been identified, but these may be confounded or biased. METHODS: Using SARS-CoV-2 infection test data (n = 4509 tests; 1325 positive) from Public Health England, linked to the UK Biobank study, we explored the contribution of demographic, social, health risk, medical and environmental factors to COVID-19 risk. We used multivariable and penalized logistic regression models for the risk of (i) being tested, (ii) testing positive/negative in the study population and, adopting a test negative design, (iii) the risk of testing positive within the tested population. RESULTS: In the fully adjusted model, variables independently associated with the risk of being tested for COVID-19 with odds ratio >1.05 were: male sex; Black ethnicity; social disadvantage (as measured by education, housing and income); occupation (healthcare worker, retired, unemployed); ever smoker; severely obese; comorbidities; and greater exposure to particulate matter (PM) 2.5 absorbance. Of these, only male sex, non-White ethnicity and lower educational attainment, and none of the comorbidities or health risk factors, were associated with testing positive among tested individuals. CONCLUSIONS: We adopted a careful and exhaustive approach within a large population-based cohort, which enabled us to triangulate evidence linking male sex, lower educational attainment and non-White ethnicity with the risk of COVID-19. The elucidation of the joint and independent effects of these factors is a high-priority area for further research to inform on the natural history of COVID-19.

Importance of collecting data on socioeconomic determinants from the early stage of the COVID-19 outbreak onwards.

Disadvantaged socioeconomic position (SEP) is widely associated with disease and mortality, and there is no reason to think this will not be the case for the newly emerged coronavirus disease 2019 (COVID-19) that has reached a pandemic level. Individuals with a more disadvantaged SEP are more likely to be affected by most of the known risk factors of COVID-19. SEP has been previously established as a potential determinant of infectious diseases in general. We hypothesise that SEP plays an important role in the COVID-19 pandemic either directly or indirectly via occupation, living conditions, health-related behaviours, presence of comorbidities and immune functioning. However, the influence of socioeconomic factors on COVID-19 transmission, severity and outcomes is not yet known and is subject to scrutiny and investigation. Here we briefly review the extent to which SEP has been considered as one of the potential risk factors of COVID-19. From 29 eligible studies that reported the characteristics of patients with COVID-19 and their potential risk factors, only one study reported the occupational position of patients with mild or severe disease. This brief overview of the literature highlights that important socioeconomic characteristics are being overlooked when data are collected. As COVID-19 spreads worldwide, it is crucial to collect and report data on socioeconomic determinants as well as race/ethnicity to identify high-risk populations. A systematic recording of socioeconomic characteristics of patients with COVID-19 will be beneficial to identify most vulnerable groups, to identify how SEP relates to COVID-19 and to develop equitable public health prevention measures, guidelines and interventions.