COVID-19 has spread to cities pushed by socio-economically weaker groups, study finds

Swiss researchers conducted a study showing that the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in cities is due to lower socio-economically groups with high mobility.

The SARS-CoV-2 virus is the causative agent of the 2019 coronavirus disease pandemic (COVID-19) that has affected the lives of billions of people and the economy around the world.

“Here, at very high spatio-temporal resolution, we analyzed the determinants of the transmission of SARS-CoV-2 in a medium-sized European city,” explains Adrian Egli of the University of Basel and his colleagues. “We combined detailed epidemiological, mobility and socio-economic data sets with whole genome sequencing during the first wave of SARS-CoV-2.”

Researchers have shown that it was not the elderly population that was responsible for the transmission of SARS-CoV-2 in the first wave.

Vaccinating this high-risk group could temporarily reduce the number of hospitalizations and intensive care admissions, according to the team. However, the pandemic could be contained more effectively by prioritizing vaccination in areas where it is not possible to trace the chains of transmission, as is the case with mobile and socio-economically weaker groups.

The researchers say that high-resolution epidemiological studies at the city level are essential for understanding chains of transmission and supporting vaccine distribution strategies at the municipal level.

Here, the researchers provide an example of such an analysis that can be easily translated to other cities.

A pre-printed version of the paper is available on the medRxiv * server, while the article is subject to peer review.

Efforts to cut the chains of transmission of SARS-CoV-2

Local interventions aimed at cutting the chains of transmission of SARS-CoV-2 within family, social and community networks are most effective when applied in well-defined clusters of infection.

However, most infections are acquired from unknown sources and transmitted encrypted along the chain of transmission and are the real drivers of the pandemic, ”says Egli and colleagues.

Identifying the main determinants and routes of transmission at the city level is essential to guide the planning of immunization programs.

For this, spatially and temporally highly resolved and diverse data is needed, including detailed information on chains of transmission and on determinants such as demographic, socio-economic and interaction patterns that influence both mobility of the population. population and social interaction behavior, ”the researchers write.

To date, no study has yet rigorously analyzed the socio-economic differences between city neighborhoods as determinants of transmission.

The team argues that an integrated model taking into account several factors, including geographic, mobility and socio-economic information, could better understand the underlying determinants of transmission, compared to focusing only on the dynamics of transmission. .

What was the current study?

Medium-sized cities of less than 300,000 inhabitants are home to a significant proportion (around 40%) of the urban population and therefore play an important role in the spread of SARS-CoV-2.

In this study, Basel, which has a population of approximately 175,350, is a representative example of such cities.

“As in most other European cities, the urban areas of Basel-City differ in terms of demography, socio-economic factors, housing structure and mobility,” explains Egli and his team.

The researchers combined detailed epidemiological, mobility and socio-economic data sets with very high-resolution whole-genome sequencing data in spatial (street, river, etc.) and temporal (day-to-day) resolution for each case of infection during the first pandemic wave (from 25^e February 2020 to 22^nd April 2020).

Out of 7,073 polymerase chain reaction (PCR) tests performed at the University Hospital Basel and an associated voluntary testing center, 750 were positive for SARS-CoV-2 (positivity rate of 10.6%) and all the genomes of 411 samples were successfully sequenced. .

Data were analyzed using a recovered sensitive-exposed-infected ordinary differential equation (ODE) model (SEIR).

“This model includes a city-wide mobility network of real-world measured data to identify transmission routes,” the team explains.

What did the study find?

The study found that socio-economic groups characterized by low median income and smaller living space per person resulted in transmission in the city more than socio-economically stronger groups.

This observation is consistent with the possibility that low socioeconomic status may be linked to jobs requiring higher personal contact and mandatory mobility, which increases the risk of infection by 76%, ”the team writes.

In contrast, the elderly population has not been found responsible for transmission. Cases of infection in this group have been grouped together, suggesting that contact tracing strategies would be effective, since chains of transmission can be detected and contained.

Simulated vaccination scenarios showed that the greatest reduction in infection cases would be achieved by prioritizing areas where chains of transmission cannot be traced, as is the case for mobile and socio-economic groups. weaker.

Model adapted to the time series of the number of cases. AC) Adjust the results for a partition based on median income. Data points are presented with model predictions based on undisturbed data (solid lines) and fifty bootstraps from disturbed data (bands) for the various tertiles T1 (low, A), T2 (intermediate, B) and T3 (high median income, C). DF) The dynamic variation of the effective number of reproduction for each of the tertiles indicated in AC. GJ) Histograms on all bootstraps for the effective reproductive number before locking for each socio-economic partition. Results are presented for partitions based on living space per person (G), median income (H), share of one-person households (I) and share of elderly residents (J).

What does the team advise?

“Although vaccinating high-risk groups would reduce the number of hospitalized patients and short-term intensive care, the spread of the pandemic would be more effectively contained by vaccinating the transmission factors,” said Egli and colleagues.

The team says the results could provide valuable information on how transmission dynamics could be harnessed to guide the vaccination strategy.

High resolution epidemiological studies at city level are essential to understand factors affecting chains of pandemic transmission, thus supporting public health information campaigns and vaccine distribution strategies at the municipal level, ”the researchers write. .

“We have given here an example of such an analysis in a European city and suggest that the results and modeling approaches presented can be easily translated in other cities”, they conclude.