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Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study
BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the poten...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365590/ https://www.ncbi.nlm.nih.gov/pubmed/37379069 http://dx.doi.org/10.2196/39895 |
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author | Stone, Haley Heslop, David Lim, Samsung Sarmiento, Ines Kunasekaran, Mohana MacIntyre, C Raina |
author_facet | Stone, Haley Heslop, David Lim, Samsung Sarmiento, Ines Kunasekaran, Mohana MacIntyre, C Raina |
author_sort | Stone, Haley |
collection | PubMed |
description | BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the potential for impacts on human and environmental health. The disruption of war has caused interruptions to normal preventive activities, and radiation monitoring sensors have been nonfunctional. Open-source intelligence can be informative when formal reporting and data are unavailable. OBJECTIVE: This paper aimed to demonstrate the value of open-source intelligence in Ukraine to identify signals of potential radiological events of health significance during the Ukrainian conflict. METHODS: Data were collected from search terminology for radiobiological events and acute radiation syndrome detection between February 1 and March 20, 2022, using 2 open-source intelligence (OSINT) systems, EPIWATCH and Epitweetr. RESULTS: Both EPIWATCH and Epitweetr identified signals of potential radiobiological events throughout Ukraine, particularly on March 4 in Kyiv, Bucha, and Chernobyl. CONCLUSIONS: Open-source data can provide valuable intelligence and early warning about potential radiation hazards in conditions of war, where formal reporting and mitigation may be lacking, to enable timely emergency and public health responses. |
format | Online Article Text |
id | pubmed-10365590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-103655902023-07-25 Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study Stone, Haley Heslop, David Lim, Samsung Sarmiento, Ines Kunasekaran, Mohana MacIntyre, C Raina JMIR Infodemiology Original Paper BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the potential for impacts on human and environmental health. The disruption of war has caused interruptions to normal preventive activities, and radiation monitoring sensors have been nonfunctional. Open-source intelligence can be informative when formal reporting and data are unavailable. OBJECTIVE: This paper aimed to demonstrate the value of open-source intelligence in Ukraine to identify signals of potential radiological events of health significance during the Ukrainian conflict. METHODS: Data were collected from search terminology for radiobiological events and acute radiation syndrome detection between February 1 and March 20, 2022, using 2 open-source intelligence (OSINT) systems, EPIWATCH and Epitweetr. RESULTS: Both EPIWATCH and Epitweetr identified signals of potential radiobiological events throughout Ukraine, particularly on March 4 in Kyiv, Bucha, and Chernobyl. CONCLUSIONS: Open-source data can provide valuable intelligence and early warning about potential radiation hazards in conditions of war, where formal reporting and mitigation may be lacking, to enable timely emergency and public health responses. JMIR Publications 2023-06-28 /pmc/articles/PMC10365590/ /pubmed/37379069 http://dx.doi.org/10.2196/39895 Text en ©Haley Stone, David Heslop, Samsung Lim, Ines Sarmiento, Mohana Kunasekaran, C Raina MacIntyre. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 28.06.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Infodemiology, is properly cited. The complete bibliographic information, a link to the original publication on https://infodemiology.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Stone, Haley Heslop, David Lim, Samsung Sarmiento, Ines Kunasekaran, Mohana MacIntyre, C Raina Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title | Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title_full | Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title_fullStr | Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title_full_unstemmed | Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title_short | Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study |
title_sort | open-source intelligence for detection of radiological events and syndromes following the invasion of ukraine in 2022: observational study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365590/ https://www.ncbi.nlm.nih.gov/pubmed/37379069 http://dx.doi.org/10.2196/39895 |
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