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Dependence of the Firearm-Related Homicide Rate on Gun Availability: A Mathematical Analysis

Overview of attention for article published in PLOS ONE, July 2013
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Title
Dependence of the Firearm-Related Homicide Rate on Gun Availability: A Mathematical Analysis
Published in
PLOS ONE, July 2013
DOI 10.1371/journal.pone.0071606
Pubmed ID
Authors

Dominik Wodarz, Natalia L. Komarova

Abstract

In the USA, the relationship between the legal availability of guns and the firearm-related homicide rate has been debated. It has been argued that unrestricted gun availability promotes the occurrence of firearm-induced homicides. It has also been pointed out that gun possession can protect potential victims when attacked. This paper provides a first mathematical analysis of this tradeoff, with the goal to steer the debate towards arguing about assumptions, statistics, and scientific methods. The model is based on a set of clearly defined assumptions, which are supported by available statistical data, and is formulated axiomatically such that results do not depend on arbitrary mathematical expressions. According to this framework, two alternative scenarios can minimize the gun-related homicide rate: a ban of private firearms possession, or a policy allowing the general population to carry guns. Importantly, the model identifies the crucial parameters that determine which policy minimizes the death rate, and thus serves as a guide for the design of future epidemiological studies. The parameters that need to be measured include the fraction of offenders that illegally possess a gun, the degree of protection provided by gun ownership, and the fraction of the population who take up their right to own a gun and carry it when attacked. Limited data available in the literature were used to demonstrate how the model can be parameterized, and this preliminary analysis suggests that a ban of private firearm possession, or possibly a partial reduction in gun availability, might lower the rate of firearm-induced homicides. This, however, should not be seen as a policy recommendation, due to the limited data available to inform and parameterize the model. However, the model clearly defines what needs to be measured, and provides a basis for a scientific discussion about assumptions and data.

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Geographical breakdown

Country Count As %
United States 4 7%
Unknown 53 93%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 21%
Student > Master 11 19%
Researcher 7 12%
Student > Ph. D. Student 5 9%
Other 4 7%
Other 11 19%
Unknown 7 12%
Readers by discipline Count As %
Social Sciences 8 14%
Medicine and Dentistry 8 14%
Agricultural and Biological Sciences 7 12%
Psychology 5 9%
Nursing and Health Professions 3 5%
Other 17 30%
Unknown 9 16%