Detection of unreported infections based on seroprevalence of SARS-CoV-2 antibodies

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 the United States in late January 2020. The emergence of highly infectious SARS-CoV-2 variants such as B.1.617.2 (Delta) and B.1.1.529 (Omicron) caused 19 waves.

The burden of COVID-19 will be monitored over time based on the number of infections, deaths, hospital visits and hospitalizations. In contrast, seroprevalence within a population is determined at specific time points.

study: SARS-CoV-2 Antibody Seroprevalence Trends and Reported Cases Estimated from a Repeated Cross-Sectional Study in 50 US States and the District of Columbia from October 25, 2020 to February 26, 2022 Relationship with prevalenceImage credit: Cryptographer / Shutterstock.com

Background

Serosurveillance studies, whether cohort or cross-sectional based, have been challenged by their inability to determine the public burden of COVID-19. One of the reasons for this limitation is that serosurveillance is conducted in rural geographic areas or targeted to specific patient populations.

new Lancet Regional Health The study combined data from all cross-sectional, national, repeatable, and all-age SARS-CoV-2 seroprevalence studies to elucidate national temporal trends in COVID-19 prevalence. was analyzed. The primary aim of this study was to determine trends in overall antibody seroprevalence in various subgroups based on age, sex, and urbanity. In addition, the authors analyzed changes in serological estimates across different phases of the pandemic and geographic regions.

About research

Remnant serum samples were collected from a commercial laboratory between October 25, 2020 and February 26, 2022. These laboratories routinely obtained serum specimens from all 50 US states and the District of Columbia (DC) for routine screening, diagnostic, or clinical care.

These serum samples were used to measure SARS-CoV-2 antibodies using a commercially available test kit with Emergency Use Authorization from the U.S. Food and Drug Administration (FDA).

Initially, SARS-CoV-2 antibodies were estimated every other week. Antibodies were tested monthly after a 56-day rest period.

The authors obtained additional data such as sex, age, state, postal code, and date of sample collection. However, this study did not include vaccination status, race, or ethnicity.

Survey results

A total of 1,469,792 remnant serum samples were obtained during the study period, of which 58.9% were female.

The most significant proportion of the sample belonged to individuals aged 18 to 49 and the smallest proportion to those aged 0 to 17. In addition, most samples were from metropolitan areas and several waves of SARS-CoV-2 infection were recorded.

Interestingly, seroprevalence due to infection correlated with age, with the youngest group aged 0–17 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 in people over the age of 65. Both men and women showed similar infection-induced seroprevalence estimates.

Metropolitan areas consistently showed lower seropositivity rates compared with non-metropolitan areas. Conversely, the highest seroprevalence was in the Midwest and Southern regions of the United States.

Throughout the study period, a convex pattern was observed in the rate of change, defined as the ratio of seroprevalence change to reported case prevalence change. For example, in the southern US states, he had the highest ratio at 3.2 during the winter months, compared to around 1.5 during other periods.

implication

Analysis of serosurveillance data is important as it provides insight into infectious load. Rates of change help understand the infection burden based on officially reported case rates.

Rapid increase in infection rate casts doubt on vaccines EffectivenessIn the current study, researchers observed the highest rate of change during periods of high viral infection, especially in the winter.

As home testing for COVID-19 becomes available and used, changes in seroprevalence may be observed compared to changes in reported cases. This highlights the importance of continuous seromonitoring, which can provide better insight into the actual infectious load.

Serosurveys help detect and target interventions to population subgroups at highest risk of infection. For example, seroprevalence in children is usually underestimated compared to adults, but children have the highest seroprevalence and high infection rates.

Conclusion

Current studies have many limitations, including the lack of probabilistic sampling, a potential source of bias in serosurveys. Furthermore, excluding samples from individuals frequently undergoing SARS-CoV-2 antibody testing may lead to underestimation of seroprevalence.

Nonetheless, current studies show that serosurveillance data do not fully capture the SARS-CoV-2 infection burden in the United States through late 2020 and early 2022.

Serum surveillance data are essential for understanding vaccine efficacy. We also better understand the impact of his COVID-19 at the community level and identify subgroups at high risk of infection. This information could help scientists and policy makers develop better strategies to protect vulnerable populations.