THIS DATASET WAS LAST UPDATED AT 8:10 PM EASTERN ON MARCH 24

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.

To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs. This translates into the following equation: Where i represents census tracts, () is the metropolitan/micropolitan (CBSA) mean tract poverty rate, is the ith tract poverty rate, () is the non-Hispanic white population in tract i, and Pop is the population in tract i.While this definition of R/ECAP works well for tracts in CBSAs, place outside of these geographies are unlikely to have racial or ethnic concentrations as high as 50 percent. In these areas, the racial/ethnic concentration threshold is set at 20 percent.

Data Source: American Community Survey (ACS), 2009-2013; Decennial Census (2010); Brown Longitudinal Tract Database (LTDB) based on decennial census data, 1990, 2000 & 2010.

Related AFFH-T Local Government, PHA Tables/Maps: Table 4, 7; Maps 1-17. Related AFFH-T State Tables/Maps: Table 4, 7; Maps 1-15, 18.

References:Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.

To learn more about R/ECAPs visit:https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 11/2017

Equity Atlas Data Description

Geographies Background:

Census Tract populations range from 1,200 to 8,000, have an average population of 4,000, and are intended to be relatively homogeneous units with respect to the resident population’s characteristics, economic status, and housing conditions. There are 375 Census Tracts completely within Bexar County. Census Tracts do not follow the CoSA boundary. Both Decennial Census and ACS Tract level data are available for Bexar County.

Blocks are the smallest subdivisions of Tracts. They are typically bounded by visible features like roads and boundaries like city limits. They can have populations that vary from zero to several hundred, such as when an apartment complex occupies the entire area. Blocks are the smallest geographic unit used by the Census Bureau for tabulation of 100-percent data (Data collected from all houses such as in the Decennial Census). There are 23,698 Blocks in Bexar County, 18,629 of which had a population of at least one and as much as 5,052 in the 2020 Decennial Census.

Demographic Data Background:

The U.S. Census Bureau’s Decennial Census is conducted once every ten years. During the Decennial Census, the Census Bureau strives to count every single person and every single residence using what was, prior to 2010, known as the “Short Form.” Decennial Census data are released down to the Census Block level. The data provided in the Decennial Census is much more accurate than the data available from the American Community Survey (ACS), which replaces what was known as the Decennial Census “Long Form.” However, since the Decennial Census is only conducted once every 10-years, the data are not as up to date as that provided by the ACS (Except for the year of Decennial Census data release).

The U.S. Census Bureau’s ACS sends out approximately 3.5-million surveys to nationwide households annually, approximately 135 households per Tract, nationwide, over a 5-year period. The ACS has a final approximate response rate of 67%, or 2.3-million surveys. This means that approximately 13,300 or 1.85% of 717,124 Total Households (Per 2021 ACS 5-Year estimates) in Bexar County respond to an ACS survey in a single year.

ACS 5-year estimates include survey results from 5-years, such as from 2017 to 2021 for the 2021 ACS 5-year estimates. The approximate 66,502 or 9.27% of Total Households within Bexar County responding to the ACS survey over a 5-years period, are the basis for numbers released that represent all households in the county. While the ACS data are more up-to date then Decennial Census data, they are less accurate due to the small sample size and Margin of Error.

Several 2021 ACS 5-Year Estimates tables were used to create the EquityScore GIS data layer attribute table, and the Equity Atlas companion data tables, EquityScoreAdditionalVariables and EquityScoreSpecialVariables. Those ACS tables are:

1. DP02 SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES

2. DP04 SELECTED HOUSING CHARACTERISTICS

3. DP05 ACS DEMOGRAPHIC AND HOUSING ESTIMATES

4. S1701 POVERTY STATUS IN THE PAST 12 MONTHS

5. S1903 MEDIAN INCOME IN THE PAST 12 MONTHS (IN 2017 INFLATION-ADJUSTED DOLLARS)

Split Tracts and Data Allocation:

A couple of issue arise with using the more up to data annually released ACS Census Tract estimates. These issues involve splitting Tracts and allocating demographic values between the split portions of Tracts.

First, Census Tract boundaries do not align with the CoSA boundary, and some Tracts are thus split by the CoSA boundary. To address this, when the portion of a Tract intersecting the CoSA was reduced to a very small area (e.g., Less than 10 Acres) or the intersecting portion is very long and exceedingly narrow sliver, those areas were merged with adjacent Tracts within the CoSA to avoid map clutter. The demographic data of the merged small area/sliver (Typically small counts, if any) do not convey to the Tract with which it was merged since it is important that the demographic values allocated to the portions of split Tracts add up to the original Tract’s values for quality assurance procedures. Instead, that value was added to the majority area portion of the original Tract that is outside the CoSA.

Second, the count values (e.g., Total Population, Race/Ethnicity, High School Education…) of a split by the CoSA boundary Tract need to be divided between the sub-portions of the Tract in a way that acknowledges the fact that population is often not evenly distributed within Tract areas. To address this, two allocation methods were used. The Dasymetric Allocation method divided the 2021 ACS 5-year Tract estimates values within its source Track, based on the 2020 Decennial Census total population values of sub-Tracts area Blocks. For instance, if Tract 1 had 10% of its 2020 Decennial Census Total Population within its Block A, then Block A would be assigned 10% of that Tract’s 2021 ACS Total Population. This methodology approximates population densities within a Tract. For variables with averages rather than counts (e.g., Median Household Incomes), portions of split Tracts retain the original values.

Blocks can also be split by the CoSA boundary. To address this, the Areal Allocation method divided split sub-Tract Block areas based on the percentage of the total area within or without the CoSA boundary. For instance, if a Block had a Dasymetric Allocation assigned Total Population value of 200, and that Block was split so that 75% of its area was in the CoSA, then that portion of the Block intersecting the CoSA was assigned a Total Population value of 150.

Equity Score Assignment:

Following the Split Tract Data Allocation, the CoSA Total Population was calculated as being 1,440,704. This value must be used rather than the Census Bureau’s ACS 5-Year estimate Total Population for the CoSA, 1,434,540, since the allocated values for all the Tracts must add up to the Total Population value. Discrepancies between the allocated from Tracts with the CoSA Boundary value and the Census Bureau CoSA value are minor (+6,164) and at least partly attributable to CoSA boundary changes in recent years (Census Bureau does not update their boundaries as frequently). For the People of Color, Median Household Income, Education and Language Equity Scores, the goal is to have approximately 20-percent of the Tract allocated CoSA Total Population, 288,141, in each of the 5 Equity scores (1-5) for a particular variable.

People of Color Score:

Since Hispanics (An ethnicity) are usually treated as a race, it is important to note that the Hispanic or Latino by Race table is used. This table includes a Hispanic and Latino value, as well as Not Hispanic and Latino race values (e.g., Not Hispanic or Latino White, Black or African American, Asian…). The use of this table, rather than the Hispanic and Latino value and the regular Race table, is necessary in order to sum the Race/Ethnicity populations and come up with the correct Total Population value.

The values for the People of Color variable are the sum of all Race/Ethnicity categories, except for the White Alone, Not Hispanic or Latino variable. The Percent People of Color (People of Color / Total Population) variable is symbolized in five classes with each class representing as near as possible, 20% of the above referenced total population. This was accomplished by sorting the Percent People of Color values from high to low and then, starting from the top, selecting records until the target summed Total Population, 288,141, was as close as possible for those selected records. Scores of five were given to the highest values of Percent People of Color. Scores decreased, in turn, to one for the lowest values of Percent People of Color.

Income Score:

The Median Household Income variable was sorted from low to high. Then, starting from the top, records were selected until the target summed Total Population, 288,141, was as close as possible for those selected records. Scores of five were given to the lowest values of Median Household Income. Scores decreased, in turn, to one for the highest values of Median Household Income.

Overall Score:

The Overall Equity score was calculated by adding the People of Color and Median Household Income scores. This results in nine Overall Equity scores (2-10).

Education Score:

The Percent Less than High School Graduate or Equivalent (Less than High School Graduate or Equivalent / Educational Attainment Age 25-Years and Up Total Population) variable values were sorted from high to low. Then, starting from the top, records were selected until the target summed Total Population, 288,141, was as close as possible for those selected records. Scores of five were given to the highest values of Percent Less than High School Graduate or Equivalent. Scores decreased, in turn, to one for the lowest values of Percent Less than High School Graduate or Equivalent.

Language Score:

The Percent Speaks English Less than "Very Well” (Speaks English Less than "Very Well" / Language Spoken at Home Age 5-years and Up Total Population) variable values were sorted from high to low. Then, starting from the top, records were selected until the target summed Total Population, 288,141, was as close as possible for those selected records. Scores of five were given to the highest values of Percent Speaks English Less than "Very Well." Scores decreased, in turn, to one for the lowest values of Percent Speaks English Less than "Very Well."

Data Used in Equity Score Determination:

The EquityScore GIS data layer attribute table only contains the actual Equity Scores or Ranks. The variables used to determine those scores (TOTAL_POP, PCT_PEOPLE_OF_COLOR, MED_HSHLD_INCOME_TOTAL_HSHLDS, PCT_EDU_LESS_THAN_HS_GRAD, and PCT_SPEAK_NOT_ENGLISH) are in the EquityScoreAdditionalVariables companion table. That companion table can be joined to the

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.