Persistence of Anti-SARS-CoV-2 Antibodies in Long Term Care Residents Over Seven Months After Two COVID-19 Outbreaks
Bibliographic record
Abstract
Background: As part of the public health outbreak investigations, serological surveys were carried out following two COVID-19 outbreaks in April 2020 and October 2020 in one long term care facility (LTCF) in British Columbia, Canada. This study describes the serostatus of the LTCF residents and monitors changes in their humoral response to SARS-CoV-2 and other human coronaviruses (HCoV) over seven months. Methods: A total of 132 serum samples were collected from all 106 consenting residents (aged 54-102) post-first outbreak (N=87) and post-second outbreak (N=45) in one LTCF; 26/106 participants provided their serum following both COVID-19 outbreaks, permitting longitudinal comparisons between surveys. Health-Canada approved commercial serologic tests and a pan-coronavirus multiplexed immunoassay were used to evaluate antibody levels against the spike protein, nucleocapsid, and receptor binding domain (RBD) of SARS-CoV-2, as well as the spike proteins of HCoV-229E, HCoV-HKU1, HCoV-NL63, and HCoV-OC43. Statistical analyses were performed to describe the humoral response to SARS-CoV-2 among residents longitudinally. Findings: Survey findings demonstrated that among the 26 individuals that participated in both surveys, all 10 individuals seropositive after the first outbreak continued to be seropositive following the second outbreak, with no reinfections identified among them. SARS-CoV-2 attack rate in the second outbreak was lower (28.6%) than in the first outbreak (40.2%), though not statistically significant (P>0.05). Gradual waning of anti-nucleocapsid antibodies to SARS-CoV-2 was observed on commercial (median Δ=-3.7, P=0.0098) and multiplexed immunoassay (median Δ=-169579, P=0.014) platforms; however, anti-spike and anti-receptor binding domain (RBD) antibodies did not exhibit a statistically significant decline over 7 months. Elevated antibody levels for beta-HCoVs OC43 (P<0.0001) and HKU1 (P=0.0027) were observed among individuals seropositive for SARS-CoV-2 compared to seronegative individuals. Conclusion: Our study utilized well-validated serological platforms to demonstrate that humoral responses to SARS-CoV-2 persisted for at least 7 months. Elevated OC43 and HKU1 antibodies among SARS-CoV-2 seropositive individuals may be attributed to cross reaction and/or boosting of humoral response.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".