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The global epidemiology of botulism outbreaks from open-source intelligence, 2017–2024
Journal article   Open access   Peer reviewed

The global epidemiology of botulism outbreaks from open-source intelligence, 2017–2024

Damian Alexander Honeyman, David James Heslop and Chandini Raina MacIntyre
The American journal of emergency medicine, Vol.101, pp.71-78
03/2026
PMID: 41475035
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Abstract

Artificial intelligence Botulism Disease Epidemiology Surveillance
Background: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and the environment. In the absence of a global surveillance system, open-source intelligence (OSINT) offers real-time insight into botulism activity. Methods: Using the Artificial-Intelligence-driven OSINT early warning system EPIWATCH®, we extracted a dataset published between 31 December 2016 and 1 January 2025 and filtered by our search terms to identify botulism outbreaks. Data collected included country, event date, location, symptoms, outbreak type (human/animal), case numbers, hospitalisations, antitoxin treatment, deaths, source and origin of outbreak, botulism type, toxin strain, and time from exposure to symptom onset. Analyses were conducted using STATA/BE 17.0. Results: OSINT identified 296 botulism outbreaks, of which 259 (87.5 %) were in humans, totalling 1097 cases and 47 deaths. There were 37 animal outbreaks (12.5 %), accounting for 27,537 cases and 27,287 animal deaths. The highest number of human outbreaks occurred in Ukraine (56.0 %, n = 145), the Russian Federation (10.8 %, n = 28), and the United States of America (7.0 %, n = 18). Common symptoms included dysphagia (11.0 %), nausea (9.0 %), and generalised weakness (8.8 %). The primary transmission routes were foodborne (79.5 %), iatrogenic (3.1 %) and wound (3.1 %, n = 8). The most frequently implicated sources were dried fish (33.2 %), canned fish (5.4 %) and canned meat (4.6 %, n = 12). Toxin strain was rarely reported (97.7 %). Conclusion: OSINT-based surveillance, despite some limitations, provides a new mechanism for insight into global botulism patterns, particularly where traditional reporting is limited.

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