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

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.

Authors

Publication Details

Journal
Emerging infectious diseases
Published
2024-08-23
DOI
https://doi.org/10.3201/eid3009.240082
Citations
7
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
2.71

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article

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

Anjali Kannan, Zubair Akhtar, Ashley Quigley, Braidy Sutton et al.
7 citations
Emerging infectious diseases
Data-Driven Disease Surveillance
2.71
article

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

Anjali Kannan, Zubair Akhtar, Ashley Quigley, Braidy Sutton, Rosalie Chen, C. Raina MacIntyre, Margaret J. Morris
article en
7 citations

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.

Emerging infectious diseasesVol. 30(9)
Medical Research Council, National Health and Medical Research Council
Good health and well-being
Openalex Percentile: Top 9%
Data-Driven Disease Surveillance
2.71
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Use of Open-Source Epidemic Intelligence for Infectious Disease Outbreaks, Ukraine, 2022 — Anjali Kannan, Zubair Akhtar, et al. · Emerging infectious diseases (2024) | TGRS Research Map | TGRS