Segregation Fuels Faster Spread of Infectious Diseases

[Vienna, May 21, 2025] – Structural inequalities, including wealth inequality and social segregation, not only make certain groups more vulnerable during public health crises but also accelerate the spread of infectious diseases through society, according to a team of international researchers. 

In a study published in Nature Scientific Reports, the researchers introduce a novel computational model that drew from two comprehensive US data sets—one based on economic and social network data from 404 metropolitan areas in the United States and another using daily Covid-19 infection data from Chicago—to better understand the relationship between socioeconomic factors and epidemic dynamics.

“As social segregation increases, it exacerbates not only the health inequality but also the overall prevalence of the disease. In that case, everyone will be worse off,” says first author Sina Sajjadi, from the Complexity Science Hub.

“We found this surprising because high segregation and low interaction among groups might appear to limit transmission across socioeconomic groups, resulting in a lower infection rate,” explains Sajjadi. “In fact, it's not like that. According to our model, such high segregation will result in an explosion of the disease, which will ultimately infect others.”

“Our model shows that when people can’t effectively quarantine—especially in communities where many are closely connected—the risk of infection goes up. This close contact can lead to a rapid outbreak that spreads through the neighborhood and beyond,” adds co-author Fariba Karimi, CSH's Algorithmic Fairness team leader and professor at Graz University of Technology. 

The computational model also predicts the appearance of a second peak in infection rates. Due to a false sense of safety, higher-income individuals, who can afford to quarantine, return to normal activities prematurely once infection rates in lower-income groups decline. This dynamic sets the stage for renewed outbreaks.

In addition, the results confirm that wealth inequality widens the infection gap. Low-income individuals, with fewer resources to self-quarantine, are more likely to be exposed to infections, leading to higher infection rates in disadvantaged communities. 

On the other hand, the researchers considered a hypothetical “ideal” scenario for each metropolitan area, in which all groups were homogeneously mixed. “We found that, without segregation, infection rates were lower in most metropolitan areas. A nonsegregated community would be better able to protect everyone from infectious diseases”, points out Sajjadi. 

According to the researchers, the findings underscore the urgent need for policies that address income inequality and social segregation, particularly during pandemics. “By reducing these disparities, governments can mitigate the health impacts of future crises and protect vulnerable populations,” say Sajjadi and Karimi, who worked with researchers from Turkey, the United States, and Inserm Institute in France.

The study “Structural inequalities exacerbate infection disparities,” by Sina Sajjadi, Pourya Toranj Simin, Mehrzad Shadmangohar, Basak Taraktas, Ulya Bayram, Maria V. Ruiz-Blondet & Fariba Karimi, was published in Nature Scientific Reports and is available online (https://doi.org/10.1038/s41598-025-91008-w).

The Complexity Science Hub (CSH) is Europe’s research center for the study of complex systems. We derive meaning from data from a range of disciplines—economics, medicine, ecology, and the social sciences—as a basis for actionable solutions for a better world. Established in 2015, we have grown to over 70 researchers, driven by the increasing demand to gain a genuine understanding of the networks that underlie society, from healthcare to supply chains. Through our complexity science approaches linking physics, mathematics, and computational modeling with data and network science, we develop the capacity to address today’s and tomorrow’s challenges.