Abstract
OBJECTIVES: The EPIWATCH artificial intelligence (AI) system scans open-source data using automated technology and can be used to detect early warnings of infectious disease outbreaks. In May 2022, a multicountry outbreak of Mpox in non-endemic countries was confirmed by the World Health Organization. This study aimed to identify signals of fever and rash-like illness using EPIWATCH and, if detected, determine if they represented potential Mpox outbreaks. STUDY DESIGN: The EPIWATCH AI system was used to detect global signals for syndromes of rash and fever that may have represented a missed diagnosis of Mpox from 1 month prior to the initial case confirmation in the United Kingdom (7 May 2022) to 2 months following. METHODS: Articles were extracted from EPIWATCH and underwent review. A descriptive epidemiologic analysis was conducted to identify reports pertaining to each rash-like illness, locations of each outbreak and report publication dates for the entries from 2022, with 2021 as a control surveillance period. RESULTS: Reports of rash-like illnesses in 2022 between 1 April and 11 July (n = 656 reports) were higher than in the same period in 2021 (n = 75 reports). The data showed an increase in reports from July 2021 to July 2022, and the Mann-Kendall trend test showed a significant upward trend (P = 0.015). The most frequently reported illness was hand-foot-and-mouth disease, and the country with the most reports was India. CONCLUSIONS: Vast open-source data can be parsed using AI in systems such as EPIWATCH to assist in the early detection of disease outbreaks and monitor global trends.