Cargando…
Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine
Biomathematical models quantitatively describe human physiological responses to environmental and operational stressors and have been used for planning and real-time prevention of cold injury. These same models can be applied from a military tactical perspective to gain valuable insights into the he...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062240/ https://www.ncbi.nlm.nih.gov/pubmed/36989120 http://dx.doi.org/10.1080/22423982.2023.2194504 |
_version_ | 1785017448213250048 |
---|---|
author | Potter, Adam W. Looney, David P. Friedl, Karl E. |
author_facet | Potter, Adam W. Looney, David P. Friedl, Karl E. |
author_sort | Potter, Adam W. |
collection | PubMed |
description | Biomathematical models quantitatively describe human physiological responses to environmental and operational stressors and have been used for planning and real-time prevention of cold injury. These same models can be applied from a military tactical perspective to gain valuable insights into the health status of opponent soldiers. This paper describes a use case for predicting physiological status of Russian soldiers invading Ukraine using open-source information. In March 2022, media outlets reported Russian soldiers in a stalled convoy invading Ukraine were at serious risk of hypothermia and predicted these soldiers would be “freezing to death” within days because of declining temperatures (down to −20°C). Using existing Army models, clothing data and open-source intelligence, modelling and analyses were conducted within hours to quantitatively assess the conditions and provide science-based predictions. These predictions projected a significant increase in risks of frostbite for exposed skin and toes and feet, with a very low (negligible) risk of hypothermia. Several days later, media outlets confirmed these predictions, reporting a steep rise in evacuations for foot frostbite injuries in these Russian forces. This demonstrated what can be done today with the existing mathematical physiology and how models traditionally focused on health risk can be used for tactical intelligence. |
format | Online Article Text |
id | pubmed-10062240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-100622402023-03-31 Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine Potter, Adam W. Looney, David P. Friedl, Karl E. Int J Circumpolar Health Arctic Military Conference in Cold Weather Medicine Biomathematical models quantitatively describe human physiological responses to environmental and operational stressors and have been used for planning and real-time prevention of cold injury. These same models can be applied from a military tactical perspective to gain valuable insights into the health status of opponent soldiers. This paper describes a use case for predicting physiological status of Russian soldiers invading Ukraine using open-source information. In March 2022, media outlets reported Russian soldiers in a stalled convoy invading Ukraine were at serious risk of hypothermia and predicted these soldiers would be “freezing to death” within days because of declining temperatures (down to −20°C). Using existing Army models, clothing data and open-source intelligence, modelling and analyses were conducted within hours to quantitatively assess the conditions and provide science-based predictions. These predictions projected a significant increase in risks of frostbite for exposed skin and toes and feet, with a very low (negligible) risk of hypothermia. Several days later, media outlets confirmed these predictions, reporting a steep rise in evacuations for foot frostbite injuries in these Russian forces. This demonstrated what can be done today with the existing mathematical physiology and how models traditionally focused on health risk can be used for tactical intelligence. Taylor & Francis 2023-03-29 /pmc/articles/PMC10062240/ /pubmed/36989120 http://dx.doi.org/10.1080/22423982.2023.2194504 Text en This work was authored as part of the Contributor’s official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 USC 105, no copyright protection is available for such works under US Law. https://creativecommons.org/publicdomain/mark/1.0/This is an Open Access article that has been identified as being free of known restrictions under copyright law, including all related and neighboring rights (https://creativecommons.org/publicdomain/mark/1.0/). You can copy, modify, distribute, and perform the work, even for commercial purposes, all without asking permission. |
spellingShingle | Arctic Military Conference in Cold Weather Medicine Potter, Adam W. Looney, David P. Friedl, Karl E. Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title | Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title_full | Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title_fullStr | Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title_full_unstemmed | Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title_short | Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine |
title_sort | use case for predictive physiological models: tactical insights about frozen russian soldiers in ukraine |
topic | Arctic Military Conference in Cold Weather Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062240/ https://www.ncbi.nlm.nih.gov/pubmed/36989120 http://dx.doi.org/10.1080/22423982.2023.2194504 |
work_keys_str_mv | AT potteradamw usecaseforpredictivephysiologicalmodelstacticalinsightsaboutfrozenrussiansoldiersinukraine AT looneydavidp usecaseforpredictivephysiologicalmodelstacticalinsightsaboutfrozenrussiansoldiersinukraine AT friedlkarle usecaseforpredictivephysiologicalmodelstacticalinsightsaboutfrozenrussiansoldiersinukraine |