Does Socioeconomics Play a Role in Testing Positive, Mortality For SARS-CoV-2?

A Swiss population-based study showed more people in socioeconomically challenged places tested positive more frequently, saw higher hospitalizations, and greater mortality rates than those in higher socioeconomic places.


In looking at socioeconomics related to COVID-19, numerous studies have shown that populations who are challenged socioeconomically, have been disproportionately affected by the pandemic. In a very large population study done in Switzerland, investigators found that people who were in a higher socioeconomic position (SEP) were more likely to be tested for COVID-19, but had a lower incidence rate, less hospitalization, and lower mortality rates than those in a lower SEP.

“Among tested people, test positivity was lower (0·75 [0·69–0·81]) in neighborhoods of highest SEP than of lowest SEP,” the investigators reported. "Among people testing positive, the adjusted IRR was 0·68 (0·62–0·74) for hospitalization, was 0·54 (0·43–0·70) for ICU admission, and 0·86 (0·76–0·99) for death,” the investigators wrote.

The findings were published in The Lancet Microbe, and presented at the European Congress of Clinical Microbiology and Infectious Diseases Conference.

In addition, the investigators found the “associations between neighborhood SEP and outcomes were stronger in younger age groups and we found heterogeneity between areas.”

The investigators reviewed surveillance data reported to the Swiss Federal Office of Public Health from March 2020 to April 2021, and 2018 population data.

“We geocoded residential addresses of notifications to identify the Swiss neighborhood index of socioeconomic position (Swiss-SEP). The index describes 1·27 million small neighborhoods of approximately 50 households each on the basis of rent per m², education and occupation of household heads, and crowding,” the investigators wrote. “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.”

They adjusted models for sex, age, canton, and wave of the epidemic (before or after June 8, 2020). They used the general population, the number of tests, and the number of positive tests as the different denominators.

Analyses were based on 4129636 tests, 609782 positive tests, 26143 hospitalizations, 2432 ICU admissions, 9383 deaths, and 8221406 residents.

“The higher incidence of SARS-CoV-2 infections, combined with a higher prevalence of comorbidities in neighborhoods of lower SEP compared with higher SEP is likely to have contributed to worse outcomes, including the higher risk of hospitalization and death,” the investigators wrote.

The investigators did note that by June 2021, 40% of the Swiss population had received 1 dose of the COVID-19 vaccine and that gradual reducing of preventative measures was taking place.

They also said that the information provided from these types of studies needs to be applied to help reduce the inequities related to socioeconomics. “Governments and health-care systems should address this pandemic of inequality by taking measures to reduce health inequalities in their response to the SARS-CoV-2 pandemic.”