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Linking Immuno-Epidemiology Principles to Violence
BACKGROUND: Societies have always struggled with violence, but recently there has been a push to understand violence as a public health issue. This idea has unified professionals in medicine, epidemiological, and psychology with a goal to end violence and heal those exposed to it. Recently, analogie...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673202/ https://www.ncbi.nlm.nih.gov/pubmed/36401175 http://dx.doi.org/10.1186/s12889-022-14472-3 |
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author | Sisk, Anna Bamwine, Patricia Day, Judy Fefferman, Nina |
author_facet | Sisk, Anna Bamwine, Patricia Day, Judy Fefferman, Nina |
author_sort | Sisk, Anna |
collection | PubMed |
description | BACKGROUND: Societies have always struggled with violence, but recently there has been a push to understand violence as a public health issue. This idea has unified professionals in medicine, epidemiological, and psychology with a goal to end violence and heal those exposed to it. Recently, analogies have been made between community-level infectious disease epidemiology and how violence spreads within a community. Experts in public health and medicine suggest an epidemiological framework could be used to study violence. METHODS: Building upon results from community organizations which implement public health-like techniques to stop violence spread, we look to formalize the analogies between violence and infectious diseases. Then expanding on these ideas and using mathematical epidemiological principals, we formulate a susceptible-exposed-infected model to capture violence spread. Further, we ran example numerical simulations to show how a mathematical model can provide insight on prevention strategies. RESULTS: The preliminary simulations show negative effects of violence exposure have a greater impact than positive effects of preventative measures. For example, our simulation shows that when the impact of violence exposure is reduced by half, the amount of violence in a community drastically decreases in the long-term; but to reach this same outcome through an increase in the amount of after exposure support, it must be approximately fivefold. Further, we note that our simulations qualitatively agree with empirical studies. CONCLUSIONS: Having a mathematical model can give insights on the effectiveness of different strategies for violence prevention. Based on our example simulations, the most effective use of community funding is investing in protective factors, instead of support after violence exposure, but of course these results do not stand in isolation and will need to be contextualized with the rest of the research in the field. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14472-3. |
format | Online Article Text |
id | pubmed-9673202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96732022022-11-18 Linking Immuno-Epidemiology Principles to Violence Sisk, Anna Bamwine, Patricia Day, Judy Fefferman, Nina BMC Public Health Research BACKGROUND: Societies have always struggled with violence, but recently there has been a push to understand violence as a public health issue. This idea has unified professionals in medicine, epidemiological, and psychology with a goal to end violence and heal those exposed to it. Recently, analogies have been made between community-level infectious disease epidemiology and how violence spreads within a community. Experts in public health and medicine suggest an epidemiological framework could be used to study violence. METHODS: Building upon results from community organizations which implement public health-like techniques to stop violence spread, we look to formalize the analogies between violence and infectious diseases. Then expanding on these ideas and using mathematical epidemiological principals, we formulate a susceptible-exposed-infected model to capture violence spread. Further, we ran example numerical simulations to show how a mathematical model can provide insight on prevention strategies. RESULTS: The preliminary simulations show negative effects of violence exposure have a greater impact than positive effects of preventative measures. For example, our simulation shows that when the impact of violence exposure is reduced by half, the amount of violence in a community drastically decreases in the long-term; but to reach this same outcome through an increase in the amount of after exposure support, it must be approximately fivefold. Further, we note that our simulations qualitatively agree with empirical studies. CONCLUSIONS: Having a mathematical model can give insights on the effectiveness of different strategies for violence prevention. Based on our example simulations, the most effective use of community funding is investing in protective factors, instead of support after violence exposure, but of course these results do not stand in isolation and will need to be contextualized with the rest of the research in the field. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14472-3. BioMed Central 2022-11-18 /pmc/articles/PMC9673202/ /pubmed/36401175 http://dx.doi.org/10.1186/s12889-022-14472-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sisk, Anna Bamwine, Patricia Day, Judy Fefferman, Nina Linking Immuno-Epidemiology Principles to Violence |
title | Linking Immuno-Epidemiology Principles to Violence |
title_full | Linking Immuno-Epidemiology Principles to Violence |
title_fullStr | Linking Immuno-Epidemiology Principles to Violence |
title_full_unstemmed | Linking Immuno-Epidemiology Principles to Violence |
title_short | Linking Immuno-Epidemiology Principles to Violence |
title_sort | linking immuno-epidemiology principles to violence |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673202/ https://www.ncbi.nlm.nih.gov/pubmed/36401175 http://dx.doi.org/10.1186/s12889-022-14472-3 |
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