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Longitudinal dynamics of humoral immunity among health care workers in Portugal using mixed effects modelling
| dc.contributor.author | Saraiva, Ana Leonor | |
| dc.contributor.author | Afreixo, Vera | |
| dc.contributor.author | Machado, Ausenda | |
| dc.contributor.author | Gaio, Vânia | |
| dc.date.accessioned | 2026-01-22T16:08:24Z | |
| dc.date.available | 2026-01-22T16:08:24Z | |
| dc.date.issued | 2025-09-10 | |
| dc.description.abstract | Introduction: The emergence of COVID-19 in 2019 led to the rapid development of vaccines and diagnostic tests. To assess antibody responses in healthcare workers (HCWs), a 2021–2022 cohort study was conducted across three Portuguese hospitals. Antibody levels were measured at six intervals: pre-vaccination, post-first dose, at 3, 6, and 12 months after the second dose, and post-booster. Each hospital utilized a different assay: Abbott’s CMIA,, Roche’s Elecsys® ECLIA, and Siemens’ ADVIA Centaur®, leading to challenges in data comparability. The study aimed to harmonize serological data across these hospitals and, through mixed-effects modeling, jointly analyze the longitudinal dynamics of humoral immunity among HCWs in Portugal. Methods: To ensure adequate conversion of antibody titers from different laboratory methods, quantile harmonization, and Deming regression were applied. After harmonization, linear mixed-effects models (LMER) assessed the relationship between antibody levels and covariates, accounting for fixed and random effects. The models included variables such as prior infection, age, hospital, smoking status, contact with COVID-19 patients, and chronic conditions. Sensitivity analyses included models excluding outliers, removing influential points, and applying multiple imputation for missing data. Results: The mixed-effects models demonstrated significant increases in antibody levels following vaccination (β = 21,234; 95% CI: 14,014–28,454; p < 0.001), with an even greater rise observed after the booster dose (β = 33,185; 95% CI: 25,939–40,430; p < 0.001) when compared to the pre-vaccination baseline. Significant differences between hospitals were also evident, as Roche’s Elecsys® ECLIA showed a notably smaller increase at 3 months compared to Abbott’s CMIA (β = -3,285; 95% CI: -5,511 to -1,058; p = 0.004). Interaction plots highlighted how covariates influenced antibody levels over time, revealing higher antibody responses post-vaccination and booster among individuals with prior infection, younger age groups, non-smokers, healthcare workers with direct patient contact, and those without chronic conditions. Sensitivity analyses, such as removing outliers and influential points and applying multiple imputation for missing data, confirmed the robustness and reliability of these findings. Conclusions: The harmonization of antibody measurements enabled a clear evaluation of immune response dynamics among healthcare workers. Vaccination and booster doses significantly increased antibody levels, while differences between hospitals and individual characteristics influenced the magnitude of these responses. These findings enhance our understanding of factors shaping humoral immunity and may guide future vaccination strategies. | eng |
| dc.description.sponsorship | The data of the study were originally collected as part of the project ‘Developing an infrastructure and performing vaccine effectiveness studies for COVID- 19 vaccine in the EU/EEA’ (Contract ECD.11486 Lot3 (HCW) and amendment Nº ECD.11486), and the Enhanced laboratory support to perform assessment of vaccine effectiveness against SARS- CoV- 2 infection (ECD.12175) and the ‘Vaccine Effectiveness, Burden and Impact Studies (VEBIS) of COVID- 19 and Influenza’, funded by the European Centre for Disease Prevention and Control through a service contract with Epiconcept (ECD.12609). | |
| dc.identifier.uri | http://hdl.handle.net/10400.18/10745 | |
| dc.language.iso | eng | |
| dc.peerreviewed | n/a | |
| dc.relation | VEBIS Lot 3 | |
| dc.rights.uri | N/A | |
| dc.subject | SARS-Cov-2 | |
| dc.subject | Humoral Immunity | |
| dc.subject | Healthcare Workers | |
| dc.subject | Estado de Saúde e de Doença | |
| dc.subject | Determinantes de Saúde | |
| dc.subject | Infecções Respiratórias | |
| dc.subject | Portugal | |
| dc.title | Longitudinal dynamics of humoral immunity among health care workers in Portugal using mixed effects modelling | eng |
| dc.type | conference poster | |
| dspace.entity.type | Publication | |
| oaire.citation.conferenceDate | 2025-09 | |
| oaire.citation.title | 6th ESCMID Conference on Vaccines, 10-13 September 2025 | |
| oaire.version | http://purl.org/coar/version/c_be7fb7dd8ff6fe43 | |
| person.familyName | Machado | |
| person.familyName | Gaio | |
| person.givenName | Ausenda | |
| person.givenName | Vânia | |
| person.identifier.ciencia-id | 1217-6076-5D88 | |
| person.identifier.ciencia-id | A71A-17AF-30C7 | |
| person.identifier.orcid | 0000-0002-1849-1499 | |
| person.identifier.orcid | 0000-0001-7626-4991 | |
| person.identifier.scopus-author-id | 56080468200 | |
| relation.isAuthorOfPublication | 544ad266-0c22-4a50-9ebc-86acc08d6666 | |
| relation.isAuthorOfPublication | 59791814-187c-4b34-b3a2-6ad67a213814 | |
| relation.isAuthorOfPublication.latestForDiscovery | 544ad266-0c22-4a50-9ebc-86acc08d6666 |
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