EPIWATCH®: A Rapid Epidemic Surveillance Tool for Detecting Early Signals of the First-ever Marburg Virus Outbreak in Equatorial Guinea
DOI:
https://doi.org/10.31646/gbio.279Keywords:
Marburg virus, Disease outbreak, haemorrhagic fever, diseases or outbreaks monitoring, enhanced surveillance, early signs, Disease Detection, EpiWATCH dataAbstract
Background: On February 13, 2023, Equatorial Guinea identified the Marburg virus for the first time, leading to the declaration of a Marburg virus disease (MVD) outbreak, characterized by a high fatality rate. EPIWATCH® is a rapid surveillance tool that employs artificial intelligence (AI) to detect early signals of outbreaks and the emergence of infectious diseases in real time.
Aims: This study aimed to use EPIWATCH® to identify early warning indicators of MVD in Equatorial Guinea during the three months before its official declaration by the World Health Organization (WHO) and local health authorities. Additionally, it sought to examine reported syndromes across regional Africa during the same period to explore potential signals of MVD from the neighboring countries.
Methods: We conducted a retrospective analysis using EPIWATCH® to collect syndromic surveillance data from November 2022 to February 2023 in Equatorial Guinea and across Sub-Saharan Africa.
Results: There was a notable absence of EPIWATCH® reports regarding Equatorial Guinea in the three months preceding the official declaration of the MVD outbreak, from November 2022 to early February 2023. Additionally, EPIWATCH® reports from neighboring countries did not reveal any syndromic signals of MVD across other regions of Africa during this timeframe. However, a report documenting the syndrome “hemorrhagic fever” in Equatorial Guinea was identified on February 10, 2023, before the diagnosis of the first case on February 12, 2023, serving as the early signal of the 2023 MVD outbreak.
Conclusion: The absence of early warning indicators in Equatorial Guinea and across Sub-Saharan Africa in the three months leading up to the official declaration of the outbreak remained unknown. Additional investigations, such as genome analysis or phylogenetic studies, may be required to investigate the outbreak's emergence. AI-based surveillance tools like EPIWATCH® could supplement traditional public health surveillance methods in detecting a wide range of infectious diseases worldwide.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 The Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Accepted 2024-10-05
Published 2025-02-27
