In the United States, Black people have higher rates of gun homicide than White people across all age groups. As of 2022, gun homicide rates were highest among Black people aged between 15 and 24 years, at ***** gun homicides per 100,000 of the population. In comparison, there were only **** gun homicides per 100,000 of the White population within this age range. However, the risk for gun homicide was greatest among all adolescents and adults between the ages of 15 to 44 in that year. The impact of guns on young Americans In the last few years, firearms have become the leading cause of death for American children and teenagers aged one to 19 years old, accounting for more deaths than car crashes and diseases. School shootings also remain on the rise recently, with the U.S. recording ** times as many school shootings than other high-income nations from 2009 to 2018. Black students in particular experience a disproportionately high number of school shootings relative to their population, and K-12 teachers at schools made up mostly of students of color are more likely to report feeling afraid that they or their students would be a victim of attack or harm. The right to bear arms Despite increasingly high rates of gun-related violence, gun ownership remains a significant part of American culture, largely due to the fact that the right to bear arms is written into the U.S. Constitution. Although firearms are the most common murder weapon used in the U.S., accounting for approximately ****** homicides in 2022, almost **** of American households have at least one firearm in their possession. Consequently, it is evident that firearms remain easily accessible nationwide, even though gun laws may vary from state to state. However, the topic of gun control still causes political controversy, as the majority of Republicans agree that it is more important to protect the right of Americans to own guns, while Democrats are more inclined to believe that it is more important to limit gun ownership.

This statistic shows the number of gun deaths in the United States annually as an average from the years 2012 to 2014, by race per 100,000 population. On average, there were 20 deaths per 100,000 people annually among to the black population of the United States. The corresponding rate among the white population was nearly half at 11.2 gun deaths per 100,000 people annually.

As of 2021, Black men had the highest firearm homicide rate in the United States, with ***** homicides by firearm per 100,000 of the population. In comparison, Black women had a firearm homicide rate of **** per 100,000 of the population. In that year, the risk of gun homicide was lowest among Asian people across all genders.

In 2023, ****** white people in the United States died due to injuries caused by firearms. A further ****** Black people died due to injuries caused by firearms across the country in that year.

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.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

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.

This dataset includes the number and rate of firearm-related deaths among Virginia residents by patient health district and race/ethnicity 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.

Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.

Age-adjusted rate of deaths from firearms by sex, race/ethnicity, age; trends if available. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sourcesYear (String): Year of data; presented as single year or pooled years (2012-2016)Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: <18, 18 to 44, 45 to 64, 65+; United States and Healthy People 2020 targetRate per 100,000 people (Numeric): Rate of deaths from firearms. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

THIS DATASET WAS LAST UPDATED AT 2:11 PM EASTERN ON SEPT. 3

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

This indicator is based on location of residence. Mortality rate has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify homicides are X85-Y09, Y87.1, and U01-U02. 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. Almost three quarters of homicides involve firearms. 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. Comprehensive prevention strategies should work to address the 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.

This statistic shows the number of gun deaths in the United States annually as an average from the years 2012 to 2014, by race. On average, there were ****** white victims of gun deaths compared to ***** black victims.

The Mortality Detail File: External Cause Extract is a special subset of data prepared from the MORTALITY DETAIL FILES, 1968-1991 (ICPSR 7632). Due to changes in Cause of Death definitions incorporated in the INTERNATIONAL CLASSIFICATION OF DISEASES, NINTH REVISION (ICD-9), the 1968-1978 data files differ slightly from the 1979-1980 data files. The 1968-1978 data reflect cause of death codes of the INTERNATIONAL CLASSIFICATION OF DISEASES ADAPTED FOR USE IN THE UNITED STATES, EIGHTH REVISION (ICDA-8). The period immediately following (1979-80) utilizes ICD-9 cause of death codes. In addition to the differences in the Cause of Death codes and recodes, the 1979-1980 data include three variables not available in the 1968-1978 datasets. These are: mortality by marital status, state or country of birth, and place of death and status of decedent when death occurred in a hospital or medical center. With these exceptions, the data are similar in structure and content to the 1968-1978 data and provide detailed personal and geographic information such as month and day of death, decedent's race and gender, age of deceased at time of death, place of decedent's residence (specific to the city level), place of death (specific to the county level), and whether an autopsy was performed. The 1979-1980 files also contain new variables pertinent to criminal justice research: handgun versus other gun accidents, handgun versus other firearm suicides, handgun versus other firearm homicides, and drug poison versus other poison homicides.

In 2019, *** people of Asian or Pacific Islander origin died by suicide using a firearm in the United States. In that same year, ****** White people died by suicide involving a firearm in the United States.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 44 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

There was a large spike in gun purchases and gun violence during the first year of the COVID-19 pandemic in the United States. We used an online U.S. national survey (N = 1036) to examine the characteristics of people who purchased a gun between March 2020 and October 2021 (n = 103) and compared them to non-gun owners (n = 763) and people who own a gun but did not purchase a gun during the COVID-19 pandemic (n = 170). Compared to non-gun owners, pandemic gun buyers were younger and more likely to be male, White race, and to affiliate with the Republican party. Compared to non-gun owners and pre-pandemic gun owners, pandemic gun buyers exhibited extreme elevations on a constellation of political (QAnon beliefs, pro-gun attitudes, Christian Nationalism, approval of former President Donald Trump, anti-vax beliefs, COVID-19 skepticism; mean Cohen’s d = 1.15), behavioral (intimate partner violence, antisocial behavior; mean d = 1.38), mental health (suicidality, depression, anxiety, substance use; mean d = 1.21), and personality (desire for power, belief in a dangerous world, low agreeableness, low conscientiousness; mean d = 0.95) characteristics. In contrast, pre-pandemic gun owners only endorsed more pro-gun attitudes (d = 0.67), lower approval of President Joe Biden (d = -0.41) and were more likely to be male and affiliate with the Republican party relative to non-gun owners. Pandemic gun buyers represent an extreme group in terms of political and psychological characteristics including several risk-factors for violence and self-harm.

In 2023, the FBI reported that there were 9,284 Black murder victims in the United States and 7,289 white murder victims. In comparison, there were 554 murder victims of unknown race and 586 victims of another race. Victims of inequality? In recent years, the role of racial inequality in violent crimes such as robberies, assaults, and homicides has gained public attention. In particular, the issue of police brutality has led to increasing attention following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Studies show that the rate of fatal police shootings for Black Americans was more than double the rate reported of other races. Crime reporting National crime data in the United States is based off the Federal Bureau of Investigation’s new crime reporting system, which requires law enforcement agencies to self-report their data in detail. Due to the recent implementation of this system, less crime data has been reported, with some states such as Delaware and Pennsylvania declining to report any data to the FBI at all in the last few years, suggesting that the Bureau's data may not fully reflect accurate information on crime in the United States.

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 project investigated the experiences of New York City youth ages 16-24 who were at high risk for gun violence (e.g., carried a gun, been shot or shot at). Youth participants were recruited from three neighborhoods with historically high rates of gun violence when compared to the city as a whole--Brownsville (Brooklyn), Morrisania (Bronx), and East Harlem (Manhattan). This study explores the complex confluence of individual, situational, and environmental factors that influence youth gun acquisition and use. This study is part of a broader effort to build an evidence-based foundation for individual and community interventions, and policies that will more effectively support these young people and prevent youth gun violence. Through interviews with 330 youth, this study seeks to answer these questions: What are the reasons young people carry guns? How do young people talk about having and using guns? What are young people's social networks like, and what roles do guns play in thesenetworks? Interviews covered the following topics: neighborhood perceptions; perceptions of and experiences with the police, gangs, guns, and violence; substance use; criminal history; and demographics: race, gender, age, legal status, relationship status, living situation, _location, number of children, drug use, and education.