Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Sisk, Anna, Bamwine, Patricia, Day, Judy, Fefferman, Nina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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
_version_ 1784832900089249792
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
work_keys_str_mv AT siskanna linkingimmunoepidemiologyprinciplestoviolence
AT bamwinepatricia linkingimmunoepidemiologyprinciplestoviolence
AT dayjudy linkingimmunoepidemiologyprinciplestoviolence
AT feffermannina linkingimmunoepidemiologyprinciplestoviolence