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Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury

BACKGROUND: Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the...

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Autores principales: Keyes, Katherine M., Hamilton, Ava, Tracy, Melissa, Kagawa, Rose M. C., Pear, Veronica A., Fink, David, Branas, Charles C., Cerdá, Magdalena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162316/
https://www.ncbi.nlm.nih.gov/pubmed/35653403
http://dx.doi.org/10.1371/journal.pone.0269372
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author Keyes, Katherine M.
Hamilton, Ava
Tracy, Melissa
Kagawa, Rose M. C.
Pear, Veronica A.
Fink, David
Branas, Charles C.
Cerdá, Magdalena
author_facet Keyes, Katherine M.
Hamilton, Ava
Tracy, Melissa
Kagawa, Rose M. C.
Pear, Veronica A.
Fink, David
Branas, Charles C.
Cerdá, Magdalena
author_sort Keyes, Katherine M.
collection PubMed
description BACKGROUND: Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC). METHODS: We simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity. RESULTS: In this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43–6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified “high-risk” groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results. CONCLUSION: A key takeaway of our study is that adopting high-risk versus population-based approaches should not be an “either-or” question. When individual risk is variable and diffuse in the population, “high-risk approaches” to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues.
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spelling pubmed-91623162022-06-03 Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury Keyes, Katherine M. Hamilton, Ava Tracy, Melissa Kagawa, Rose M. C. Pear, Veronica A. Fink, David Branas, Charles C. Cerdá, Magdalena PLoS One Research Article BACKGROUND: Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC). METHODS: We simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity. RESULTS: In this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43–6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified “high-risk” groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results. CONCLUSION: A key takeaway of our study is that adopting high-risk versus population-based approaches should not be an “either-or” question. When individual risk is variable and diffuse in the population, “high-risk approaches” to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues. Public Library of Science 2022-06-02 /pmc/articles/PMC9162316/ /pubmed/35653403 http://dx.doi.org/10.1371/journal.pone.0269372 Text en © 2022 Keyes et al 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 author and source are credited.
spellingShingle Research Article
Keyes, Katherine M.
Hamilton, Ava
Tracy, Melissa
Kagawa, Rose M. C.
Pear, Veronica A.
Fink, David
Branas, Charles C.
Cerdá, Magdalena
Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title_full Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title_fullStr Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title_full_unstemmed Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title_short Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury
title_sort simulating the bounds of plausibility: estimating the impact of high-risk versus population-based approaches to prevent firearm injury
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162316/
https://www.ncbi.nlm.nih.gov/pubmed/35653403
http://dx.doi.org/10.1371/journal.pone.0269372
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