Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region

Landier, Jordi; Bassez, Lea; Bendiane, Marc-Karim; Chaud, P.; Franke, Florian; Nauleau, S.; Danjou, Fabrice; Malfait, P; Gaudart, Jean

doi:10.3389/fpubh.2023.1162711

Cited by 5 publications

(5 citation statements)

References 32 publications

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“…In their systematic review of socioeconomic COVID-19 impacts, Benita et al (2022) 17 list only nine UK-specific studies, and report a global trend of mixed and inconclusive findings as to the impact of poverty metrics on COVID-19 infection. The trend we have shown in Figure 1B, of differences in case incidence by deprivation quantiles seeming pronounced in some time periods, before reversing in others is seen in multiple other countries 18,19 .…”

Section: Discussionmentioning

confidence: 56%

“…19 cases data were taken from the UK Health Security Agency (UKHSA) national line list, collected by the Department of Health and Social Care as part of surveillance activities and shared with us. Only pillar 2 cases (swab testing of the wider population, not setting-specific) confirmed via PCR were used to account for changes in the availability of lateral flow devices (LFDs).…”

mentioning

confidence: 99%

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The impact of health inequity on regional variation of COVID-19 transmission in England

Rawson,

Hinsley,

Sonabend

et al. 2024

Preprint

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Considerable spatial heterogeneity has been observed in COVID-19 transmission across administrative regions of England throughout the pandemic. This study investigates what drives these differences. We constructed a probabilistic case count model for 306 administrative regions of England across 95 weeks, fit using a Bayesian evidence synthesis framework. We include the mechanistic impact of acquired immunity, of spatial exportation of cases, and 16 spatially-varying socio-economic, socio-demographic, health, and mobility variables. Model comparison assesses the relative contributions of these respective mechanisms. We find that regionally-varying and time-varying differences in week-to-week transmission were definitively associated with differences in: time spent at home, variant-of-concern proportion, and adult social care funding. However, model comparison demonstrates that the mechanistic impact of these terms was of negligible impact compared to the role of spatial exportation between regions. While these results confirm the impact of some, but not all, measures of regional inequity in England, our work corroborates the finding that observed differences in regional disease transmission during the pandemic were predominantly driven by underlying epidemiological factors rather than the demography and health inequity between regions.

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Section: Discussionmentioning

confidence: 56%

mentioning

confidence: 99%

The impact of health inequity on regional variation of COVID-19 transmission in England

Rawson,

Hinsley,

Sonabend

et al. 2024

Preprint

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“…These IRIS correspond to contiguous geographical areas grouping between 1,000 and 5,000 inhabitants. Marseille is densely populated and exhibits significant income disparities between neighbourhoods located in the northern (13th to 16th districts) and central (1st to 5th districts) parts of the city, and the neighbourhoods in the south (6th to 9th districts) and east (10th to 12th districts) ( 11 , 13 , 14 ). Nearly a quarter of the housing stock is over-occupied in the northern and centre neighbourhoods.…”

Section: Methodsmentioning

confidence: 99%

“…The hotspot identification was based on the incidence rate of positive tests (+1 point if >80th percentile), the test positivity rate (+1 > 80th percentile) and the acceleration of the incidence rate (+1 > 80th percentile) over the past 15 days, which combined score (from 0 to 3) defined four hotspot levels: no hotspot, level 1, level 2 and level 3. Hotspot identification was complemented by the identification of IRIS areas with socio-economic deprivation and/or under-testing during the second wave of COVID-19 in 2020 ( 11 ). Briefly, 2017 general census data (including population age groups, population density, occupational categories, percentage of immigrants and foreigners) were analysed using principal component analysis followed by hierarchical clustering to define IRIS profiles describing local socio-demographic characteristics.…”

Section: Methodsmentioning

confidence: 99%

“…However, the city was heavily affected by the subsequent waves. Marseille is also characterised by a high population density and poverty, particularly in the centre and northern districts ( 11 , 13 , 14 ). As soon as 2020, several medical-social outreach initiatives emerged to provide support for suspected cases or contacts in SARS-CoV-2 screening and isolation.…”

Section: Introductionmentioning

confidence: 99%

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Reviving health mediation during the COVID-19 crisis and beyond: an implementation study in deprived neighbourhoods of Marseille, France

Fruleux,

Gaudart,

Franke

et al. 2024

Front. Public Health

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IntroductionIn 2020, during France’s COVID-19 response, healthcare professionals from a hospital and an association initiated health mediation interventions in Marseille’s vulnerable neighbourhoods, funded by the regional health authorities. This mixed method research evaluates the CORHESAN program that lasted until June 2022.MethodsWe examined CORHESAN documents and reports, conducted interviews, and analysed activity data, comparing it to the COVID-19 hotspots identified on a weekly basis at the neighbourhood level, using generalised linear mixed models (GLMMs).ResultsCORHESAN was implemented by a team of up to nine health mediators, six private nurses hired on an ad hoc basis, supervised by a general coordinator and two part-time medical and nursing coordinators. Multiple partnerships were established with shelters, associations, social-housing landlords and local institutions. The team accompanied 6,253 people affected by COVID-19 or contact in the practical implementation of their isolation and contact tracing. Of the 5,180 nasopharyngeal samples for RT-PCR and 1,875 for antigenic testing: 12% were taken at home and 27% in partner facilities in the targeted neighbourhoods; 32% were taken from symptomatic patients and 30% in the context of contact tracing; and 40% were positive. Multiple awareness sessions on prevention methods and distributions of personal protection kits and self-diagnostic tests were conducted in the streets, in shelters, in associations or at home. A total of 5,929 doses of COVID-19 vaccine were administered in a walk-in vaccination centre, at temporary street vaccination posts, during operations at partner facilities, or during home-visits to patients with limited autonomy. GLMMs showed that the intervention significantly targeted its testing interventions in neighbourhoods with socioeconomic disadvantage and/or past under-testing (adjusted odds ratio (aOR), 2.75 [1.50–5.00]) and those with high hotspot level (aOR for level-3 versus level-0, 1.83 [1.24–2.71]).DiscussionThe pandemic emphasised the potential of health mediation interventions to address health disparities. Building on this, a new program began in July 2022, aiming at enhancing cancer screening and vaccinations in deprived areas of Marseille. Evaluations are ongoing to assess its activities and impact, and provide evidence to future implementation initiatives.

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Geographical coverage of SARS-CoV-2 screening and care centers in Haiti: what do national surveillance data tell us?

Presume,

Gaudart,

Michel

et al. 2024

BMC Public Health

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Summary Background In Haiti, reported incidence and mortality rates for COVID-19 were lower than expected. We aimed to analyze factors at communal and individual level that might lead to an underestimation of the true burden of the COVID-19 epidemic in Haiti during its first two years. Methods We analyzed national COVID-19 surveillance data from March 2020 to December 2021, to describe the epidemic using cluster detection, time series, and cartographic approach. We performed multivariate Quasi-Poisson regression models to determine socioeconomic factors associated with incidence and mortality. We performed a mixed-effect logistic regression model to determine individual factors associated with the infection. Results Among the 140 communes of Haiti, 57 (40.7%) had a COVID-19 screening center, and the incidence was six times higher in these than in those without. Only 22 (15.7%) communes had a COVID-19 care center, and the mortality was five times higher in these than in those without. All the richest communes had a COVID-19 screening center while only 30.8% of the poorest had one. And 75% of the richest communes had a COVID-19 care center while only 15.4% of the poorest had one. Having more than three healthcare workers per 1000 population in the commune was positively associated with the incidence (SIR: 3.31; IC95%: 2.50, 3.93) and the mortality (SMR: 2.73; IC95%: 2.03, 3.66). At the individual level, male gender (adjusted OR: 1.11; IC95%: 1.01, 1.22), age with a progressive increase of the risk compared to youngers, and having Haitian nationality only (adjusted OR:2.07; IC95%: 1.53, 2.82) were associated with the infection. Conclusions This study highlights the weakness of SARS-CoV-2 screening and care system in Haiti, particularly in the poorest communes, suggesting that the number of COVID-19 cases and deaths were probably greatly underestimated.

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Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region

Cited by 5 publications

References 32 publications

The impact of health inequity on regional variation of COVID-19 transmission in England

The impact of health inequity on regional variation of COVID-19 transmission in England

Reviving health mediation during the COVID-19 crisis and beyond: an implementation study in deprived neighbourhoods of Marseille, France

Geographical coverage of SARS-CoV-2 screening and care centers in Haiti: what do national surveillance data tell us?

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