Seroprevalence, seroconversion, and seroreversion of infection-induced SARS-CoV-2 antibodies among a cohort of children and adolescents in Montreal, Canada
Bibliographic record
Abstract
ABSTRACT Importance Repeated serological testing for SARS-CoV-2 allows the monitoring of antibody dynamics in populations, including detecting infections that are missed by RT-PCR or antigen testing. Understanding the factors associated with seroconversion and seroreversion as well as the duration of infection-induced antibodies can also inform public health recommendations regarding disease prevention and mitigation efforts. Objective To use serological testing to assess the prevalence, seroconversion, and seroreversion of infection-induced SARS-CoV-2 antibodies in children and adolescents in Montreal, Canada. Design This analysis reports on three rounds of data collection from a prospective cohort study (Enfants et COVID-19: Étude de séroprévalence [EnCORE]). The study rounds occurred as follows: Round 1 October 2020-March 2021, Round 2 May to July 2021, and Round 3 November 2021 to January 2022. Most Round 3 samples were collected prior to the spread of the Omicron BA.1 variant in Quebec. Setting Population-based sample. Participants Children and adolescents aged 2 to 17 years in Montreal, Canada. Exposure Potential exposure to SARS-CoV-2. Main Outcomes and Measures Participants provided dried blood spots (DBS) for antibody detection and parents completed online questionnaires for sociodemographics and COVID-19 symptoms and testing history. The serostatus of participants was determined by enzyme-linked immunosorbent assays (ELISAs) using the receptor-binding domain (RBD) from the spike protein and the nucleocapsid protein (N) as antigens. We estimated seroprevalence for each round of data collection and by participant and household characteristics. Seroconversion rates were calculated as were the likelihoods of remaining seropositive at six months and one year. Results The study included DBS samples from 1 632, 936, and 723 participants in the first, second, and third rounds of data collection, respectively. The baseline seroprevalence was 5·8% (95% CI 4·8-7·1), which increased to 10·5% and 10·9% for the respective follow-ups (95% CI 8·6-12·7; 95% CI 8·8-13·5). The overall average crude rate of seroconversion over the study period was 12·7 per 100 person-years (95% CI 10·9-14·5). Adjusted hazard rates of seroconversion by child and household characteristics showed higher rates in children who were female, whose parent identified as a racial or ethnic minority, and in households with incomes less than 100K. The likelihood of remaining seropositive at six months was 67% (95% CI 59-76) and dropped to 19% (95% CI 11%-33%) at one year. Conclusions and Relevance The data reported here provide estimates of pre-Omicron seroprevalence, seroconversion rates and time to seroreversion in a population-based cohort of children and adolescents. Serological studies continue to provide valuable contributions for infection prevalence estimates and help us better understand the dynamics of antibody levels following infection. Continued study of seroconversion and seroreversion can inform public health recommendations such as COVID-19 vaccination and booster schedules. KEY POINTS Question What was the rate of seroconversion and time to seroreversion for SARS-CoV-2 antibodies among children and adolescents in Montreal between October 2020 to January 2022? Findings The overall average crude rate of seroconversion was 12·7 per 100 person-years (95% CI 10·9-14·5). We observed higher rates of seroconversion in children who were female, whose parent identified as a racial or ethnic minority, and in households with incomes less than 100K. Among all children who seroconverted, 71% had not been previously diagnosed with COVID-19. Median time to seroreversion was 7·5 months. Meaning Even before the emergence of the Omicron variants, we observed a high rate of seroconversion for infection-induced SARS-CoV-2 antibodies along with widespread antibody waning by one year. Many children and adolescents seroconverted despite not receiving a prior COVID-19 diagnosis, indicating that RT-PCR and antigen testing continue to underestimate true disease prevalence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".