Empowering African Expertise: Enhancing Safety Data Integration and Signal Detection for COVID-19 Vaccines Through the African Union Smart Safety Surveillance Joint Signal Management Group

Victoria Prudence Nambasa*, Hannah May Gunter, Modupe Bamidele Adeyemo, Neetesh Yanish Bhawaneedin, Marc Blockman, George Tsey Sabblah, John Owusu Gyapong, Eric Muriithi Guantai, Tamrat Abebe, Workeabeba Abebe, Henry Jeremy Lawson, Mercedes Chawada Leburu, Abdullahi Mohammed, Kwame Amponsa-Achiano, Mafora Florah Matlala, Uchenna Geraldine Elemuwa, Hudu Mogtari, Alexander Kwadwo Nyarko, Marione Schönfeldt, Mercy KamupiraKerrigan McCarthy, Yohannes Lakew Tefera, Asnakech Alemu, Kabir Mawashi Yusuf, Obi Emelife, Ladji Sidibe, Kudakwashe Dandajena, Kenneth Onu, Mojisola Christianah Adeyeye, Delese Mimi Darko, Heran Gerba, Boitumelo Semete, Fred Siyoi, Aggrey Ambali, Johanna Catharina Meyer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: The COVID-19 pandemic accelerated new vaccine development. Limited safety data necessitated robust global safety surveillance to accurately identify and promptly communicate potential safety issues. The African Union Smart Safety Surveillance (AU-3S) program established the Joint Signal Management (JSM) group to support identification of potential vaccine safety concerns in five pilot countries (Ethiopia, Ghana, Kenya, Nigeria, South Africa), accounting for approximately 35% of the African population. Objective: Our objective was to provide an overview of the JSM group’s role in supporting signal management activities for the AU-3S program during the COVID-19 pandemic. Methods: Spontaneous, electronically reported COVID-19 vaccine adverse events following immunization (AEFI) from each country's safety data were integrated into the interim Data Integration and Signal Detection system. Statistical disproportionality methods were used to identify and review vaccine–event combinations (VECs) for potential safety concerns. The JSM group—which comprised pharmacovigilance and subject matter experts from National Medicine Regulatory Authorities, Expanded Programs on Immunization, and vaccine safety committees—conducted signal detection activities on cross-country safety data and provided recommendations. Results: From April 2021 to December 2023, a total of 48,294 spontaneously reported AEFI were analyzed for six COVID-19 vaccines (NRVV Ad [ChAdOx1 nCoV-19]; Ad26.COV2.S; Elasomeran; Tozinameran; Covid-19 vaccine [Vero Cell], Inactivated; NRVV Ad26 [Gam-Covid-Vac]) administered in Ethiopia (34.6%), Nigeria (30.3%), South Africa (16.9%), Ghana (13.5%), and Kenya (4.7%). Overall, 2,742 VECs were validated. A causal association between the COVID-19 vaccines and the reported AEFI cannot be inferred, as data were reported spontaneously. JSM group recommendations included monitoring for further evidence, no immediate action required, engaging marketing authorization holder(s) for additional information, or sensitizing healthcare providers and/or the public about events. Although no new safety signals were identified, nine safety-related recommendations were issued, including patient and healthcare provider education. Conclusions: The JSM group established a scalable and replicable model for future signal management of other priority health products in low- and middle-income countries, fostering ongoing collaboration and capacity building. Knowledge and experience gained from this pilot initiative will guide stakeholders in future safety surveillance initiatives within the African continent.

Original languageEnglish
Article numbere0171470
Pages (from-to)233-249
Number of pages17
JournalDrug Safety
Volume48
Issue number3
DOIs
Publication statusPublished - Mar 2025

Fingerprint

Dive into the research topics of 'Empowering African Expertise: Enhancing Safety Data Integration and Signal Detection for COVID-19 Vaccines Through the African Union Smart Safety Surveillance Joint Signal Management Group'. Together they form a unique fingerprint.

Cite this