New York City, with a population of 8.5 million people, was one of the locations most heavily affected by the first wave of the COVID-19 pandemic in North America and Europe. A large body of research has shown that those individuals who are of lower average socioeconomic status were especially affected by the pandemic and experienced a much higher rate of viral infection.
In a study recently published in PLOS Pathogens, corresponding author, Tetyana Vasylyeva, DPhil, assistant professor of population health and disease prevention at the UC Irvine Program in Public Health, and team analyzed the correlation of these disparities and its connection to the second wave in New York City (NYC), focusing on late 2020 and early 2021.
Using genetic data from the NYC Public Health Laboratory and the NYC Pandemic Response Laboratory, Vasylyeva and team analyzed nearly 18,500 positive COVID-19 samples from across NYC between November 2020 to June 2021. Seroprevalence level (or the proportion of people who have been infected before) and epidemiological data were layered on top of the COVID-19 samples to conduct statistical analyses on COVID-19 cases by location.
By focusing on the time preceding the emergence of the Delta and Omicron variants, we show that the consequences of socio-economic disparities in an outbreak can have a ripple effect that can last into subsequent outbreaks, providing an important lesson for future epidemic preparedness and mitigation efforts.”
– Tetyana Vasylyeva, DPhil
From the initial wave to the second wave, the study found that higher positivity rates were observed in areas with greater poverty and a higher proportion of Black and Hispanic or Latino residents. This suggests that these communities experienced a higher burden of disease during the first wave, leading to greater pre-existing immunity. This led to a higher prevalence of Iota-E484K and Iota COVID-19 variants, which are immune evasive variants, in those same areas during the second wave of the epidemic. These variants disproportionally affected areas with Black and Hispanic or Latino residents because those residents had higher pre-existing immunity levels that made them more susceptible to this variant compared to the variants without immune-evasive properties. Conversely, a negative correlation was observed between seropositivity and the prevalence of Alpha and B.1-like genomes which means that even though it was more prevalent in NYC it was not among Black and Hispanic or Latino residents.
The second wave of COVID-19 in NYC highlighted the significant role of socio-economic disparities in shaping COVID-19 landscape. Areas with high positivity rates, resulting from higher disease burden during the first wave, provided an environment conducive to the spread of immune-evasive COVID-19 variants like Iota-E484K. The study underscores the importance of considering socio-economic factors and pre-existing immunity in understanding and managing the dynamics of viral variant spread.
“We wouldn’t be able to replicate this study today in a multiple variant COVID-19 era and also because the majority of the population have a mixture of acquired natural and/or vaccine-induced immunity,” says Vasylyeva. “By focusing on the time preceding the emergence of the Delta and Omicron variants, we show that the consequences of socio-economic disparities in an outbreak can have a ripple effect that can last into subsequent outbreaks, providing an important lesson for future epidemic preparedness and mitigation efforts.”
Additional authors include co-corresponding author Joel O. Wertheim from the UCSD School of Medicine; graduate student Jennifer L. Havens from UCSD; associate statistician Gabriel W. Hassler from the RAND Corporation; and Elizabeth Luoma, Jade C. Wang, Helly Amin, Steve Di Lonardo, Faten Taki, Enoma Omoregie, and Scott Hughes, all from the New York City Department of Health and Mental Hygiene.
