In 2023, Mississippi had the highest firearm mortality rate in the United States with 29.4 deaths per 100,000 population. Louisiana and Alabama followed with **** and **** deaths per 100,000 population, respectively. Massachusetts had the lowest firearm mortality rate at that time.

Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; other firearm-like weapons; firearm, type of firearm is unknown), Canada, 1974 to 2024.

In 2023, there were ****** fatalities caused by injuries related to firearms in the United States, a slight decrease from the previous year. In 2021, there were ****** firearm deaths, the highest number of gun deaths ever recorded in the country. However, this figure has remained relatively high over the past 25 years, with ****** firearm deaths in 1990 and a slight dip in fatalities between 1999 and 2002. Firearms in the United States The right to own firearms in the United States is enshrined in the 2nd Amendment of the U.S. Constitution, and while this right may be seen as quintessentially American, the relationship between Americans and their firearms has become fraught in the last few years. The proliferation of mass shootings in the U.S. has brought the topic of gun control into the national spotlight, with support for banning assault-style weapons a particularly divisive issue among Americans. Gun control With a little less than **** of all Americans owning at least one firearm and the highest rate of civilian gun ownership in the world, it is easy to see how the idea of gun control is a political minefield in the U.S. However, public opinion has begun to shift over the past ten years, and a majority of Americans report that laws governing the sale of firearms should be stricter than they are now.

The statistic shows the rate of firearm homicide deaths per 100,000 of population in the United States from 1990 to 2020. In 2020, about 5.9 of every 100,000 people were killed by a firearm in the United States.

Mortality rate from firearms includes homicides, suicides, accidental deaths, deaths by law enforcement, and deaths for which intent was undetermined. Mortality rate is based on the location of residence and has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify firearm deaths are W32-W34, X72-X74, X93-X95, Y22-Y24, Y35.0, and U01.4. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Violence is a public health crisis in the US, with gun violence being a major driver. In the US, the age-adjusted homicide rate from firearms is more than 20 times higher than in the European Union or in Australia. Significant disparities by age, sex, and race and ethnicity exist, with young adults (ages 15-34 years), males, and Black individuals most disproportionately impacted. Firearm-related suicides disproportionately impact older, White men. Comprehensive prevention strategies should work to address underlying physical, social, economic, and structural conditions known to increase risk.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

In 2022, ** children younger than one year died due to firearms in the United States. That year, ****** people between the ages of 25 and 34 years, and ***** people between the ages of 45 and 54 died due to firearms across the country.

The dataset is sourced and edited from
data.world

Description is given as below:

Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death with U.S. - Mexico Border Regions 1999-2019 on CDC WONDER Online Database, released in 2020. Data are from the Multiple Cause of Death Files, 1999-2019, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. U.S. - Mexico border counties has been demarcated as the 44 counties that are located within 100 kilometers (62 miles) defined under the 1983 La Paz Agreement. Accessed at http://wonder.cdc.gov/ucd-border.html on Nov 6, 2021 12:22:30 AM

Query Parameters: Title: Gun Deaths by County MCD - ICD-10 Codes: W32 (Handgun discharge); W33 (Rifle, shotgun and larger firearm discharge); W34 (Discharge from other and unspecified firearms); X72 (Intentional self-harm by handgun discharge); X73 (Intentional self-harm by rifle, shotgun and larger firearm discharge); X74 (Intentional self-harm by other and unspecified firearm discharge); X93 (Assault by handgun discharge); X94 (Assault by rifle, shotgun and larger firearm discharge); X95 (Assault by other and unspecified firearm discharge); Y22 (Handgun discharge, undetermined intent); Y23 (Rifle, shotgun and larger firearm discharge, undetermined intent); Y24 (Other and unspecified firearm discharge, undetermined intent); Y35.0 (Legal intervention involving firearm discharge)

Group By: Year; County Show Totals: True Show Zero Values: False Show Suppressed: False Standard Population: 2000 U.S. Std. Population Calculate Rates Per: 100,000 Rate Options: Default intercensal populations for years 2001-2009 (except Infant Age Groups)

picture sourced from peterplit

The dataset that I have created through web scraping using BeautifulSoup library in Python provides a comprehensive overview of the legality of firearms across various countries. It contains detailed information on the laws and regulations governing firearms possession, use, and ownership. The dataset also includes data on the number of deaths resulting from firearm incidents, including suicides, accidents, and police shootings. In addition, the dataset provides insights into the number of firearms owned by citizens, whether they are registered or unregistered. The information is compiled from reliable sources such as Wikipedia, Wisevoter, GunPolicy, and WorldPopulationReview, ensuring that the dataset is both comprehensive and accurate. This dataset is an invaluable resource for researchers, policymakers, and others who are interested in studying the prevalence and impact of firearms on society. With its comprehensive coverage of firearm laws and incidents across various countries, this dataset offers valuable insights into the complex issue of gun control and can be used to inform policy decisions aimed at reducing the negative impact of firearms on individuals and communities.

The dataset I have created can be used for various technical applications such as machine learning and data analytics. For example, researchers and developers can use this dataset to train machine learning algorithms to identify patterns and correlations between firearm laws and incidents. This can help in developing predictive models to forecast firearm-related incidents and aid in policymaking. Data analytics techniques can also be applied to the dataset to identify trends and patterns in the data, helping researchers to gain a better understanding of the complex issues surrounding firearms. Overall, the dataset I have created offers a wealth of information on firearms laws and incidents, and its potential applications extend beyond research to include policy and decision-making in various fields.

*******Links used:******* - Wikipedia - WiseVoter - GunPolicy - WorldPopulationReview

This dataset includes the number and rate of firearm-related deaths among Virginia residents by patient health district and Age over 5 combined years. Virginia Department of Health (VDH) health districts are assigned based on the residence of the patient at the time of death, not where the death occurred. Data include Virginia residents only, whether or not they died in Virginia. Data set includes deaths from 2018 through 2022.

The VDH Office of Vital Records tracks causes of death among Virginia residents using death certificates. Codes on the death certificate indicate underlying and contributing causes of death. Deaths are classified as firearm-related using the definition from the Centers for Disease Control and Prevention State Injury Indicators Report

In 2023, 13,529 recorded murders in the United States were committed by firearm. This is a decrease from the previous year, when 12,244 homicides were committed with a firearm in the country. However, figures may not accurately reflect the total number of homicides, as not all law enforcement agencies in the U.S. submitted homicide data.

Updated dataset for the "Gun Deaths in America" project https://fivethirtyeight.com/features/gun-deaths/, documenting firearm usage fatalities.

The R code for processing the raw data is taken from https://github.com/fivethirtyeight/guns-data

I will be progressively adding the years before 2006, but the data format changed several times, so it is not as fast as I would like :-/ User guide for processing: https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm

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.

BackgroundPrior research suggests that United States governmental sources documenting the number of law-enforcement-related deaths (i.e., fatalities due to injuries inflicted by law enforcement officers) undercount these incidents. The National Vital Statistics System (NVSS), administered by the federal government and based on state death certificate data, identifies such deaths by assigning them diagnostic codes corresponding to “legal intervention” in accordance with the International Classification of Diseases–10th Revision (ICD-10). Newer, nongovernmental databases track law-enforcement-related deaths by compiling news media reports and provide an opportunity to assess the magnitude and determinants of suspected NVSS underreporting. Our a priori hypotheses were that underreporting by the NVSS would exceed that by the news media sources, and that underreporting rates would be higher for decedents of color versus white, decedents in lower versus higher income counties, decedents killed by non-firearm (e.g., Taser) versus firearm mechanisms, and deaths recorded by a medical examiner versus coroner.Methods and findingsWe created a new US-wide dataset by matching cases reported in a nongovernmental, news-media-based dataset produced by the newspaper The Guardian, The Counted, to identifiable NVSS mortality records for 2015. We conducted 2 main analyses for this cross-sectional study: (1) an estimate of the total number of deaths and the proportion unreported by each source using capture–recapture analysis and (2) an assessment of correlates of underreporting of law-enforcement-related deaths (demographic characteristics of the decedent, mechanism of death, death investigator type [medical examiner versus coroner], county median income, and county urbanicity) in the NVSS using multilevel logistic regression. We estimated that the total number of law-enforcement-related deaths in 2015 was 1,166 (95% CI: 1,153, 1,184). There were 599 deaths reported in The Counted only, 36 reported in the NVSS only, 487 reported in both lists, and an estimated 44 (95% CI: 31, 62) not reported in either source. The NVSS documented 44.9% (95% CI: 44.2%, 45.4%) of the total number of deaths, and The Counted documented 93.1% (95% CI: 91.7%, 94.2%). In a multivariable mixed-effects logistic model that controlled for all individual- and county-level covariates, decedents injured by non-firearm mechanisms had higher odds of underreporting in the NVSS than those injured by firearms (odds ratio [OR]: 68.2; 95% CI: 15.7, 297.5; p < 0.01), and underreporting was also more likely outside of the highest-income-quintile counties (OR for the lowest versus highest income quintile: 10.1; 95% CI: 2.4, 42.8; p < 0.01). There was no statistically significant difference in the odds of underreporting in the NVSS for deaths certified by coroners compared to medical examiners, and the odds of underreporting did not vary by race/ethnicity. One limitation of our analyses is that we were unable to examine the characteristics of cases that were unreported in The Counted.ConclusionsThe media-based source, The Counted, reported a considerably higher proportion of law-enforcement-related deaths than the NVSS, which failed to report a majority of these incidents. For the NVSS, rates of underreporting were higher in lower income counties and for decedents killed by non-firearm mechanisms. There was no evidence suggesting that underreporting varied by death investigator type (medical examiner versus coroner) or race/ethnicity.

This dataset includes the number and rate of firearm-related deaths among Virginia residents by patient health district and Sex over 5 combined years. Virginia Department of Health (VDH) health districts are assigned based on the residence of the patient at the time of death, not where the death occurred. Data include Virginia residents only, whether or not they died in Virginia. Data set includes deaths from 2018 through 2022.

The VDH Office of Vital Records tracks causes of death among Virginia residents using death certificates. Codes on the death certificate indicate underlying and contributing causes of death. Deaths are classified as firearm-related using the definition from the Centers for Disease Control and Prevention State Injury Indicators Report

1) Data Introduction • The Gun Violence Dataset in US is a tabularized data set for gun violence analysis that includes the date, location, victim and suspect information, and geographic coordinates of major 2024 shootings across the U.S.

2) Data Utilization (1) Gun Violence Dataset in US has characteristics that: • Each row contains key information about the shooting, including incident-specific ID, date of occurrence, state and city/county, number of deaths and injuries, suspects (death, injury, arrest), latitude, and longitude. • Data is designed to analyze the distribution of gun incidents and the extent of damage by month and region, and spatial analysis through geographic coordinates is also possible. (2) Gun Violence Dataset in US can be used to: • Analysis of shooting trends by region: Use data by location, magnitude of damage, and time to visualize and analyze the regional and temporal distribution and risk areas of gun violence. • Establishing public safety policies and prevention strategies: Based on victim and suspect information and incident characteristics, it can be used to establish effective gun control, prevention policies, resource allocation strategies, and more.

In recent years there has been an increase in the rate of firearm-related deaths in the United States. In 2021, there were **** such deaths per 100,000 population. This is the highest rate seen since the early *****. Firearm deaths Firearm-related deaths are much more common among males than females, with almost ****** firearm deaths among males in the United States in 2021, compared to just ****** among females. Those aged 25 to 34 years are the age group with the highest number of deaths from firearms, followed by those aged 15 to 24. The states with the highest mortality rates from firearms are Mississippi, Louisiana, and Wyoming. Firearm suicides The use of firearms is one of the most common methods for suicide in the United States. Around ** percent of male suicides and ** percent of female suicides are conducted by firearms. In 2020, there were a total of ****** suicide deaths from firearms. Suicide is currently the **** leading cause of death in the United States.

Trend of firearm mortality after legislation.

Number of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2024.

BackgroundGun violence has shortened the average life expectancy of Americans, and better knowledge about the root causes of gun violence is crucial to its prevention. While some empirical evidence exists regarding the impacts of social and economic factors on violence and firearm homicide rates, to the author’s knowledge, there has yet to be a comprehensive and comparative lagged, multilevel investigation of major social determinants of health in relation to firearm homicides and mass shootings.Methods and findingsThis study used negative binomial regression models and geolocated gun homicide incident data from January 1, 2015, to December 31, 2015, to explore and compare the independent associations of key state-, county-, and neighborhood-level social determinants of health—social mobility, social capital, income inequality, racial and economic segregation, and social spending—with neighborhood firearm-related homicides and mass shootings in the United States, accounting for relevant state firearm laws and a variety of state, county, and neighborhood (census tract [CT]) characteristics. Latitude and longitude coordinates on firearm-related deaths were previously collected by the Gun Violence Archive, and then linked by the British newspaper The Guardian to CTs according to 2010 Census geographies. The study population consisted of all 74,134 CTs as defined for the 2010 Census in the 48 states of the contiguous US. The final sample spanned 70,579 CTs, containing an estimated 314,247,908 individuals, or 98% of the total US population in 2015. The analyses were based on 13,060 firearm-related deaths in 2015, with 11,244 non-mass shootings taking place in 8,673 CTs and 141 mass shootings occurring in 138 CTs. For area-level social determinants, lag periods of 3 to 17 years were examined based on existing theory, empirical evidence, and data availability. County-level institutional social capital (levels of trust in institutions), social mobility, income inequality, and public welfare spending exhibited robust relationships with CT-level gun homicide rates and the total numbers of combined non-mass and mass shooting homicide incidents and non-mass shooting homicide incidents alone. A 1–standard deviation (SD) increase in institutional social capital was linked to a 19% reduction in the homicide rate (incidence rate ratio [IRR] = 0.81, 95% CI 0.73–0.91, p < 0.001) and a 17% decrease in the number of firearm homicide incidents (IRR = 0.83, 95% CI 0.73–0.95, p = 0.01). Upward social mobility was related to a 25% reduction in the gun homicide rate (IRR = 0.75, 95% CI 0.66–0.86, p < 0.001) and a 24% decrease in the number of homicide incidents (IRR = 0.76, 95% CI 0.67–0.87, p < 0.001). Meanwhile, 1-SD increases in the neighborhood percentages of residents in poverty and males living alone were associated with 26%–27% and 12% higher homicide rates, respectively. Study limitations include possible residual confounding by factors at the individual/household level, and lack of disaggregation of gun homicide data by gender and race/ethnicity.ConclusionsThis study finds that the rich–poor gap, level of citizens’ trust in institutions, economic opportunity, and public welfare spending are all related to firearm homicide rates in the US. Further establishing the causal nature of these associations and modifying these social determinants may help to address the growing gun violence epidemic and reverse recent life expectancy declines among Americans.

BackgroundFirearm-related death rates and years of potential life lost (YPLL) vary widely between population subgroups and states. However, changes or inflections in temporal trends within subgroups and states are not fully documented. We assessed temporal patterns and inflections in the rates of firearm deaths and %YPLL due to firearms for overall and by sex, age, race/ethnicity, intent, and states in the United States between 1999 and 2016.MethodsWe extracted age-adjusted firearm mortality and YPLL rates per 100,000, and %YPLL from 1999 to 2016 by using the WONDER (Wide-ranging Online Data for Epidemiologic Research) database. We used Joinpoint Regression to assess temporal trends, the inflection points, and annual percentage change (APC) from 1999 to 2016.ResultsNational firearm mortality rates were 10.3 and 11.8 per 100,000 in 1999 and 2016, with two distinct segments; a plateau until 2014 followed by an increase of APC = 7.2% (95% CI 3.1, 11.4). YPLL rates were from 304.7 and 338.2 in 1999 and 2016 with a steady APC increase in %YPLL of 0.65% (95% CI 0.43, 0.87) from 1999 to an inflection point in 2014, followed by a larger APC in %YPLL of 5.1% (95% CI 0.1, 10.4). The upward trend in firearm mortality and YPLL rates starting in 2014 was observed in subgroups of male, non-Hispanic blacks, Hispanic whites and for firearm assaults. The inflection points for firearm mortality and YPLL rates also varied across states.ConclusionsWithin the United States, firearm mortality rates and YPLL remained constant between 1999 and 2014 and has been increasing subsequently. There was, however, an increase in firearm mortality rates in several subgroups and individual states earlier than 2014.