In the United States, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, was first detected in late January 2020. Since then, several COVID- 19 waves have occurred due to the emergence of highly infectious variants of SARS-CoV-2, such as B.1.617.2 (Delta) and B.1.1.529 (Omicron ).
The burden of COVID-19 is monitored over time based on the number of infections, deaths, hospital visits, and hospital admissions. In contrast, seroprevalence within a population is determined at a specific point in time.
Study: Estimated trends in SARS-CoV-2 antibody seroprevalence and relationship to prevalence of reported cases from a replicated cross-sectional study in the 50 states and the District of Columbia, United States, from October 25, 2020 to February 26, 2022. Image credit: Cryptographer / Shutterstock.com
background
Serovigilance studies, whether cohort-based or cross-sectional, have been questioned due to their inability to determine the national burden of COVID-19. One of the reasons for this limitation is that serosurveillance is performed in sub-national geographic areas or targets a specific patient population.
A new study in The Lancet Regional Health analyzed data from all cross-sectional, national, repeat, and seroprevalence studies of SARS-CoV-2 for all ages to elucidate national-scale temporal trends in the prevalence of COVID-19 . The primary objective of this study was to determine global trends in antibody seroprevalence in different subgroups based on age, sex, and urbanicity. In addition, the authors analyzed changes in serological estimates in different phases of the pandemic and between geographic areas.
About the study
The remaining serum samples were collected from commercial laboratories between October 25, 2020, and February 26, 2022. These laboratories routinely obtained serum samples from all 50 US states and the District of Columbia (DC) for detection, diagnosis or routine clinical care.
These serum samples were used to determine SARS-CoV-2 antibodies using commercially available test kits that received emergency use authorization from the US Food and Drug Administration (FDA).
Initially, SARS-CoV-2 antibodies were estimated biweekly. After a 56-day break, antibodies were tested monthly.
The authors obtained additional data including sex, age, state, zip code, and specimen collection dates. However, the study did not include vaccination status, race, and ethnicity.
Results of the study
During the study period, a total of 1,469,792 residual serum samples were obtained, of which 58.9% belonged to women.
The most significant percentage of the samples corresponded to individuals aged between 18 and 49 years, while the smallest percentage was between 0 and 17 years. In addition, most samples came from metropolitan areas and several waves of SARS-CoV-2 infection were recorded.
Interestingly, infection-induced seroprevalence was correlated with age, with the youngest group aged zero to 17 years having the highest seroprevalence. An increase in seroprevalence from 10.4% to 75.7% was observed during the study period. An increase in seroprevalence from 9.2% to 64.5% was observed in individuals aged 18–49 years.
The lowest seroprevalence was found in people aged 65 years and older. Both men and women showed similar infection-induced seroprevalence estimates.
Compared to nonmetropolitan areas, metropolitan areas consistently showed lower seroprevalence. Conversely, the highest seroprevalence prevailed in the Midwestern and Southern regions of the US
Over the study period, a convex pattern was observed in the ratio of changes, defined as the ratio of the change in seroprevalence to the change in the prevalence of reported cases. For example, southern US states had the highest ratios during winters at 3.2 compared to about 1.5 during other periods.
Implications
Analysis of serosurveillance data is critical because it provides information on the burden of infection. The change ratio helps to understand the burden of infection based on officially reported case rates.
A sudden increase in the rate of infection also calls into question the effectiveness of the vaccine. In the current study, the researchers observed that the turnover ratio was highest during periods of high viral transmission, especially in winter.
A change in seroprevalence may be observed in relation to changes in reported cases due to the availability and use of home tests for COVID-19. This emphasizes the importance of continuous serosurveillance, which can provide better insight into the true burden of infection.
Serological surveys could help detect population subgroups at higher risk of infection and target them for interventions. Children, for example, had the highest seroprevalence and the highest infection-to-case ratios, although seroprevalence in children is usually underestimated compared to adults.
Conclusions
The current study has many limitations, including the lack of probability sampling, a potential source of bias in serological surveys. In addition, excluding samples from individuals frequently tested for SARS-CoV-2 antibodies could lead to an underestimation of seroprevalence.
However, the current study indicated that serosurveillance data did not fully capture the burden of SARS-CoV-2 infection in the US between late 2020 and early 2022.
Serovigilance data are crucial to understanding vaccine efficacy. It also provides a better understanding of the effect of COVID-19 at the community level and identifies subgroups at higher risk of infection. This information could help scientists and policymakers formulate better strategies to protect vulnerable populations.
Journal reference:
- Wiegand, ER, Deng, Y., Deng, X., et al. (2022) Estimated trends in SARS-CoV-2 antibody seroprevalence and relationship to prevalence of reported cases from a replicated cross-sectional study in the 50 states and the District of Columbia, United States, October 25, 2020 at 26 February 2022. Lancet Regional Health 18. doi:10.1016/j.lana.2022.100403