Please use this identifier to cite or link to this item: https://doi.org/10.3390/vaccines10122115
Title: Vaccine Vigilance System : Considerations on the Effectiveness of Vigilance Data Use in COVID-19 Vaccination
Authors: Arāja, Diāna
Krumina, Angelika
Nora-Krukle, Zaiga
Berkis, Uldis
Murovska, Modra
Institute of Microbiology and Virology
Department of Infectology
Development and Project Department
Keywords: pharmacovigilance;EudraVigilance;COVID-19 vaccines;adverse drug reactions (ADRs);chronic fatigue syndrome;neurological and autoimmune diseases;3.3 Health sciences;3.1 Basic medicine;1.1. Scientific article indexed in Web of Science and/or Scopus database;Drug Discovery;Infectious Diseases;Pharmacology (medical);Pharmacology;Immunology;SDG 3 - Good Health and Well-being
Issue Date: 10-Dec-2022
Citation: Arāja , D , Krumina , A , Nora-Krukle , Z , Berkis , U & Murovska , M 2022 , ' Vaccine Vigilance System : Considerations on the Effectiveness of Vigilance Data Use in COVID-19 Vaccination ' , Vaccines , vol. 10 , no. 12 , 2115 . https://doi.org/10.3390/vaccines10122115
Abstract: (1) Background: The safety of medicines has been receiving increased attention to ensure that the risks of taking medicines do not outweigh the benefits. This is the reason why, over several decades, the pharmacovigilance system has been developed. The post-authorization pharmacovigilance system is based on reports from healthcare professionals and patients on observed adverse reactions. The reports are collected in databases and progressively evaluated. However, there are emerging concerns about the effectiveness of the established passive pharmacovigilance system in accelerating circumstances, such as the COVID-19 pandemic, when billions of doses of new vaccines were administered without a long history of use. Currently, health professionals receive fragmented new information on the safety of medicines from competent authorities after a lengthy evaluation process. Simultaneously, in the context of accelerated mass vaccination, health professionals need to have access to operational information—at least on organ systems at higher risk. Therefore, the aim of this study was to perform a primary data analysis of publicly available data on suspected COVID-19 vaccine-related adverse reactions in Europe, in order to identify the predominant groups of reported medical conditions after vaccination and their association with vaccine groups, as well as to evaluate the data accessibility on specific syndromes. (2) Methods: To achieve the objectives, the data publicly available in the EudraVigilance European Database for Suspected Adverse Drug Reaction Reports were analyzed. The following tasks were defined to: (1) Identify the predominant groups of medical conditions mentioned in adverse reaction reports; (2) determine the relative frequency of reports within vaccine groups; (3) assess the feasibility of obtaining information on a possibly associated syndrome—myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). (3) Results: The data obtained demonstrate that the predominant medical conditions induced after vaccination are relevant to the following categories: (1) “General disorders and administration site conditions”, (2) “nervous system disorders”, and (3) “musculoskeletal and connective tissue disorders”. There are more reports for mRNA vaccines, but the relative frequency of reports per dose administered, is lower for this group of vaccines. Information on ME/CFS was not available, but reports of “chronic fatigue syndrome” are included in the database and accessible for primary analysis. (4) Conclusions: The information obtained on the predominantly reported medical conditions and the relevant vaccine groups may be useful for health professionals, patients, researchers, and medicine manufacturers. Policymakers could benefit from reflecting on the design of an active pharmacovigilance model, making full use of modern information technologies, including big data analysis of social media and networks for the detection of primary signals and building an early warning system.
Description: Funding Information: Funder—the Latvian Council of Science. Funding number—No. lzp-2019/1-0380, “Selection of biomarkers in ME/CFS for patient stratification and treatment surveillance/optimization” of the Fundamental and Applied Research Projects program. Publisher Copyright: © 2022 by the authors.
DOI: https://doi.org/10.3390/vaccines10122115
ISSN: 2076-393X
Appears in Collections:Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure

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