Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jan 11;227(2):193-201.
doi: 10.1093/infdis/jiac167.

Antibody Duration After Infection From SARS-CoV-2 in the Texas Coronavirus Antibody Response Survey

Affiliations

Antibody Duration After Infection From SARS-CoV-2 in the Texas Coronavirus Antibody Response Survey

Michael D Swartz et al. J Infect Dis. .

Abstract

Understanding the duration of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody Response Survey (Texas CARES) with at least 1 nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n = 4553) with 1 to 3 antibody tests over 11 months (1 October 2020 to 16 September 2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days postinfection, and predicts individuals may remain antibody positive from natural infection beyond 500 days depending on age, body mass index, smoking or vaping use, and disease severity (hospitalized or not; symptomatic or not).

Keywords: COVID-19; SARS-CoV-2; antibodies; antibody duration.

PubMed Disclaimer

Conflict of interest statement

Potential conflicts of interest. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

Figure 1.
Figure 1.
Plot of nucleocapsid antibody levels (N-test values) over time (unadjusted) with individual spaghetti plots. Time is measured in days since the self-reported coronavirus disease 2019 (COVID-19) infection. For each individual depicted, their infection date is day 0, and the date of their first and subsequent tests are chronologically arranged on the plot; later tests have longer days since infection.
Figure 2.
Figure 2.
Predicting nucleocapsid antibody status varying demographics in the reference model. The dashed line at 1 represents when the N-test reports a positive antibody response. N-test value ≥ 1 is a positive antibody response. The solid black line represents the reference prediction curve, that is for a 50 to 64-year-old non-Hispanic white woman without chronic conditions, with healthy BMI, who has insurance coverage, was asymptomatic in their infection, was not hospitalized, and did not use tobacco or vaping. The effect of varying a covariate across its domain is shown: (A) varying age, (B) varying race\ethnicity, and (C) category of BMI status. Abbreviations: BMI, body mass index; COVID-19, coronavirus disease 2019; N-test, nucleocapsid antibody test.
Figure 3.
Figure 3.
Predicting nucleocapsid antibody status by hospitalization and symptomatic status. The dashed line at 1 represents when the N-test reports a positive antibody response. N-test value ≥ 1 is a positive antibody response. The solid black line represents the reference prediction curve, that is for a 50 to 64-year-old non-Hispanic white woman without chronic conditions, with healthy BMI, who has insurance coverage, was asymptomatic in their infection, was not hospitalized, and did not use tobacco or vaping. The effect of varying a covariate across its domain is shown: (A) hospitalization status and (B) symptomatic/asymptomatic status. Abbreviations: BMI, body mass index; COVID-19, coronavirus disease 2019; N-test, nucleocapsid antibody test.

References

    1. Liu H, Zhang J, Cai J, et al. . Investigating vaccine-induced immunity and its effect in mitigating SARS-CoV-2 epidemics in China. BMC Med 2022; 20:37. - PMC - PubMed
    1. Kadkhoda K. Herd immunity to COVID-19: alluring and elusive. Am J Clin Pathol 2021; 155:471–2. - PMC - PubMed
    1. Dyer O. Covid-19: delta infections threaten herd immunity vaccine strategy. BMJ 2021; 374:n1933. - PubMed
    1. Fine P, Eames K, Heymann DL. Herd immunity": a rough guide. Clin Infect Dis 2011; 52:911–6. - PubMed
    1. Klaassen F, Chitwood MH, Cohen T, et al. . Population immunity to pre-omicron and omicron SARS-CoV-2 variants in US states and counties through December 1, 2021. medRxiv, doi: 10.1101/2021.12.23.21268272, 1 March 2022, preprint: not peer reviewed. - DOI - PMC - PubMed

Publication types

Substances