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Postvaccination SARS-CoV-2 Infections among Healthcare Professionals: A Real World Evidence Study.

ABSTRACT: Due to the COVID-19 pandemic, all countries with a global mobilization started to produce and authorize vaccines, prioritizing healthcare professionals (HCPs) to reduce transmission. The aim of this study was to assess post-vaccination infections' occurrence among HCPs and their correlation with symptom onset. A retrospective cohort study was carried out in the Campania Region from December 2020 to April 2021. Data were retrieved from the Regional Health Information System of the Campania Region (Sinfonia). The study cohort included subjects that had all received at least one vaccine dose. Risk ratios (RRs) adjusted for age and sex (95% confidence intervals) were performed to assess differences in the prevalence between HCPs who tested positive or negative for COVID-19. Univariate and multivariate logistic regression models were used to evaluate the association between symptoms and vaccination status. Findings revealed that HCPs had a lower risk of contracting COVID-19 after receiving at least one vaccine dose, and this risk decreased with age. Furthermore, not having full vaccination coverage may predict a severe/critical evolution of the disease. This study provides a snapshot of the initial state of the Italian vaccination campaign on HCPs. A surveillance approach using Big Data matched to clinical conditions could offer a real analysis in the categorization of subjects most at risk.

SUBMITTER: Perrella A

PROVIDER: S-EPMC9024651 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Postvaccination SARS-CoV-2 Infections among Healthcare Professionals: A Real World Evidence Study.

Perrella Alessandro A Mucherino Sara S Guarino Ilaria I Nerilli Mariagiovanna M Maraolo Alberto Enrico AE Capoluongo Nicolina N Coscioni Enrico E Trama Ugo U Menditto Enrica E Orlando Valentina V

Vaccines 20220325 4

Due to the COVID-19 pandemic, all countries with a global mobilization started to produce and authorize vaccines, prioritizing healthcare professionals (HCPs) to reduce transmission. The aim of this study was to assess post-vaccination infections' occurrence among HCPs and their correlation with symptom onset. A retrospective cohort study was carried out in the Campania Region from December 2020 to April 2021. Data were retrieved from the Regional Health Information System of the Campania Region ...[more]

PMID: 35455260

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Project description:BackgroundAdverse events (AEs) associated with vaccination have traditionally been evaluated by epidemiological studies. More recently, they have gained attention due to the emergency use authorization of several COVID-19 vaccines. As part of its responsibility to conduct postmarket surveillance, the US Food and Drug Administration continues to monitor several AEs of interest to ensure the safety of vaccines, including those for COVID-19.ObjectiveThis study is part of the Biologics Effectiveness and Safety Initiative, which aims to improve the US Food and Drug Administration's postmarket surveillance capabilities while minimizing the burden of collecting clinical data on suspected postvaccination AEs. The objective of this study was to enhance active surveillance efforts through a pilot platform that can receive automatically reported AE cases through a health care data exchange.MethodsWe detected cases by sharing and applying computable phenotype algorithms to real-world data in health care providers' electronic health records databases. Using the fast healthcare interoperability resources standard for secure data transmission, we implemented a computable phenotype algorithm on a new health care system. The study focused on the algorithm's positive predictive value, validated through clinical records, assessing both the time required for implementation and the accuracy of AE detection.ResultsThe algorithm required 200-250 hours to implement and optimize. Of the 6,574,420 clinical encounters across 694,151 patients, 30 cases were identified as potential myocarditis/pericarditis. Of these, 26 cases were retrievable, and 24 underwent clinical validation. In total, 14 cases were confirmed as definite or probable myocarditis/pericarditis, yielding a positive predictive value of 58.3% (95% CI 37.3%-76.9%). These findings underscore the algorithm's capability for real-time detection of AEs, though they also highlight variability in performance across different health care systems.ConclusionsThe study advocates for the ongoing refinement and application of distributed computable phenotype algorithms to enhance AE detection capabilities. These tools are crucial for comprehensive postmarket surveillance and improved vaccine safety monitoring. The outcomes suggest the need for further optimization to achieve more consistent results across diverse health care settings.

Dataset Information

Postvaccination SARS-CoV-2 Infections among Healthcare Professionals: A Real World Evidence Study.

Publications

Postvaccination SARS-CoV-2 Infections among Healthcare Professionals: A Real World Evidence Study.

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