Linking Immuno-Epidemiology Principles to Violence.

Mathematical model Protective factors Public health Violence exposure

Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
18 11 2022
Historique:
received: 13 10 2021
accepted: 26 10 2022
entrez: 19 11 2022
pubmed: 20 11 2022
medline: 23 11 2022
Statut: epublish

Résumé

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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 36401175
doi: 10.1186/s12889-022-14472-3
pii: 10.1186/s12889-022-14472-3
pmc: PMC9673202
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2118

Informations de copyright

© 2022. The Author(s).

Références

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pubmed: 29311553
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pubmed: 22696175
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pubmed: 34986810
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pubmed: 32322102
Lancet Glob Health. 2022 Apr;10(4):e457-e458
pubmed: 35303444
J Adolesc Health. 2004 Mar;34(3):177-83
pubmed: 14967340
Epidemiology. 2018 Jan;29(1):142-150
pubmed: 28926374
J Adolesc Health. 2000 Mar;26(3):176-86
pubmed: 10706165

Auteurs

Anna Sisk (A)

Department of Mathematics, University of Tennessee, 1403 Circle Dr, 227 Ayres Hall, Knoxville, TN, 37916, USA. asisk9@vols.utk.edu.

Patricia Bamwine (P)

College of Social Work, University of Tennessee, 1618 Cumberland Ave., 401 Henson Hall, Knoxville, TN, 37996, USA.

Judy Day (J)

Applied BioMath, LLC, 561 Virginia Road, Suite 220, Concord, MA, 01742, USA.

Nina Fefferman (N)

Department of Mathematics, University of Tennessee, 1403 Circle Dr, 227 Ayres Hall, Knoxville, TN, 37916, USA.
Department of Ecology & Evolutionary Biology, University of Tennessee, 569 Dabney Hall, Knoxville, TN, 37996-1610, USA.

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