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Use of Open-Source Epidemic Intelligence for Infectious Disease Outbreaks, Ukraine, 2022

Authors :
Anjali Kannan
Rosalie Chen
Zubair Akhtar
Braidy Sutton
Ashley Quigley
Margaret J. Morris
C. Raina MacIntyre
Source :
Emerging Infectious Diseases, Vol 30, Iss 9, Pp 1865-1871 (2024)
Publication Year :
2024
Publisher :
Centers for Disease Control and Prevention, 2024.

Abstract

Formal infectious disease surveillance in Ukraine has been disrupted by Russia’s 2022 invasion, leading to challenges with tracking and containing epidemics. To analyze the effects of the war on infectious disease epidemiology, we used open-source data from EPIWATCH, an artificial intelligence early-warning system. We analyzed patterns of infectious diseases and syndromes before (November 1, 2021–February 23, 2022) and during (February 24–July 31, 2022) the conflict. We compared case numbers for the most frequently reported diseases with numbers from formal sources and found increases in overall infectious disease reports and in case numbers of cholera, botulism, tuberculosis, HIV/AIDS, rabies, and salmonellosis during compared with before the invasion. During the conflict, although open-source intelligence captured case numbers for epidemics, such data (except for diphtheria) were unavailable/underestimated by formal surveillance. In the absence of formal surveillance during military conflicts, open-source data provide epidemic intelligence useful for infectious disease control.

Details

Language :
English
ISSN :
10806040 and 10806059
Volume :
30
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Emerging Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.b8c023f638414d8aa33d1ba43bc36c1a
Document Type :
article
Full Text :
https://doi.org/10.3201/eid3009.240082