» Articles » PMID: 34252364

Socioeconomic Position and the COVID-19 Care Cascade from Testing to Mortality in Switzerland: a Population-based Analysis

Overview
Specialty Public Health
Date 2021 Jul 12
PMID 34252364
Citations 58
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The inverse care law states that disadvantaged populations need more health care than advantaged populations but receive less. Gaps in COVID-19-related health care and infection control are not well understood. We aimed to examine inequalities in health in the care cascade from testing for SARS-CoV-2 to COVID-19-related hospitalisation, intensive care unit (ICU) admission, and death in Switzerland, a wealthy country strongly affected by the pandemic.

Methods: We analysed surveillance data reported to the Swiss Federal Office of Public Health from March 1, 2020, to April 16, 2021, and 2018 population data. We geocoded residential addresses of notifications to identify the Swiss neighbourhood index of socioeconomic position (Swiss-SEP). The index describes 1·27 million small neighbourhoods of approximately 50 households each on the basis of rent per m, education and occupation of household heads, and crowding. We used negative binomial regression models to calculate incidence rate ratios (IRRs) with 95% credible intervals (CrIs) of the association between ten groups of the Swiss-SEP index defined by deciles (1=lowest, 10=highest) and outcomes. Models were adjusted for sex, age, canton, and wave of the epidemic (before or after June 8, 2020). We used three different denominators: the general population, the number of tests, and the number of positive tests.

Findings: Analyses were based on 4 129 636 tests, 609 782 positive tests, 26 143 hospitalisations, 2432 ICU admissions, 9383 deaths, and 8 221 406 residents. Comparing the highest with the lowest Swiss-SEP group and using the general population as the denominator, more tests were done among people living in neighbourhoods of highest SEP compared with lowest SEP (adjusted IRR 1·18 [95% CrI 1·02-1·36]). Among tested people, test positivity was lower (0·75 [0·69-0·81]) in neighbourhoods of highest SEP than of lowest SEP. Among people testing positive, the adjusted IRR was 0·68 (0·62-0·74) for hospitalisation, was 0·54 (0·43-0·70) for ICU admission, and 0·86 (0·76-0·99) for death. The associations between neighbourhood SEP and outcomes were stronger in younger age groups and we found heterogeneity between areas.

Interpretation: The inverse care law and socioeconomic inequalities were evident in Switzerland during the COVID-19 epidemic. People living in neighbourhoods of low SEP were less likely to be tested but more likely to test positive, be admitted to hospital, or die, compared with those in areas of high SEP. It is essential to continue to monitor testing for SARS-CoV-2, access and uptake of COVID-19 vaccination and outcomes of COVID-19. Governments and health-care systems should address this pandemic of inequality by taking measures to reduce health inequalities in response to the SARS-CoV-2 pandemic.

Funding: Swiss Federal Office of Public Health, Swiss National Science Foundation, EU Horizon 2020, Branco Weiss Foundation.

Citing Articles

Socio-economic inequalities in access to COVID-19 tests in France in 2020: evidence from the EPICOV socio-epidemiological cohort.

Geoffard P, Jusot F, Sireyjol A, Warszawski J, Bajos N Front Public Health. 2025; 12:1434370.

PMID: 39917516 PMC: 11801222. DOI: 10.3389/fpubh.2024.1434370.


Spatial distribution of SARS-CoV-2 incidence, social inequality, housing conditions, and density in South-Eastern France: keys for future epidemics.

Marine Barjoan E, Prouvost-Keller B, Chaarana A, Festraets J, Geloen C, Legueult K Front Public Health. 2024; 12:1422112.

PMID: 39712297 PMC: 11659207. DOI: 10.3389/fpubh.2024.1422112.


Social health gradient and risk factors among patients hospitalized for COVID-19 and pre-pandemic respiratory infections. A linked national individual case-control study in Belgium.

Bruyneel A, Dauvergne J, Dauby N, Goffard J, Rea A, Racape J Front Public Health. 2024; 12:1426898.

PMID: 39529714 PMC: 11551126. DOI: 10.3389/fpubh.2024.1426898.


A serological survey of COVID-19 among predominantly aboriginal residents of a tourist island in southern Thailand.

Sripaew S, Yasharad K, Rahari D, Feng W, Qian Z, Thanh H Trop Med Health. 2024; 52(1):57.

PMID: 39232844 PMC: 11373474. DOI: 10.1186/s41182-024-00617-0.


Changes in Alcohol-Specific Mortality During the COVID-19 Pandemic in 14 European Countries.

Kilian C, Rehm J, Shield K, Manthey J Sucht. 2024; 69(6):285-293.

PMID: 39183774 PMC: 11343567. DOI: 10.1024/0939-5911/a000841.


References
1.
Drefahl S, Wallace M, Mussino E, Aradhya S, Kolk M, Branden M . A population-based cohort study of socio-demographic risk factors for COVID-19 deaths in Sweden. Nat Commun. 2020; 11(1):5097. PMC: 7547672. DOI: 10.1038/s41467-020-18926-3. View

2.
Johnson Sirleaf E, Clark H . Report of the Independent Panel for Pandemic Preparedness and Response: making COVID-19 the last pandemic. Lancet. 2021; 398(10295):101-103. PMC: 9751704. DOI: 10.1016/S0140-6736(21)01095-3. View

3.
Mackenbach J, Stirbu I, Roskam A, Schaap M, Menvielle G, Leinsalu M . Socioeconomic inequalities in health in 22 European countries. N Engl J Med. 2008; 358(23):2468-81. DOI: 10.1056/NEJMsa0707519. View

4.
Ward H, Atchison C, Whitaker M, Ainslie K, Elliott J, Okell L . SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic. Nat Commun. 2021; 12(1):905. PMC: 7876103. DOI: 10.1038/s41467-021-21237-w. View

5.
Hart J . The inverse care law. Lancet. 1971; 1(7696):405-12. DOI: 10.1016/s0140-6736(71)92410-x. View