The Black Death was the largest and deadliest pandemic of Yersinia pestis recorded in human history, and likely the most infamous individual pandemic ever documented. The plague originated in the Eurasian Steppes, before moving with Mongol hordes to the Black Sea, where it was then brought by Italian merchants to the Mediterranean. From here, the Black Death then spread to almost all corners of Europe, the Middle East, and North Africa. While it was never endemic to these regions, it was constantly re-introduced via trade routes from Asia (such as the Silk Road), and plague was present in Western Europe until the seventeenth century, and the other regions until the nineteenth century. Impact on Europe In Europe, the major port cities and metropolitan areas were hit the hardest. The plague spread through south-western Europe, following the arrival of Italian galleys in Sicily, Genoa, Venice, and Marseilles, at the beginning of 1347. It is claimed that Venice, Florence, and Siena lost up to two thirds of their total population during epidemic's peak, while London, which was hit in 1348, is said to have lost at least half of its population. The plague then made its way around the west of Europe, and arrived in Germany and Scandinavia in 1348, before travelling along the Baltic coast to Russia by 1351 (although data relating to the death tolls east of Germany is scarce). Some areas of Europe remained untouched by the plague for decades; for example, plague did not arrive in Iceland until 1402, however it swept across the island with devastating effect, causing the population to drop from 120,000 to 40,000 within two years. Reliability While the Black Death affected three continents, there is little recorded evidence of its impact outside of Southern or Western Europe. In Europe, however, many sources conflict and contrast with one another, often giving death tolls exceeding the estimated population at the time (such as London, where the death toll is said to be three times larger than the total population). Therefore, the precise death tolls remain uncertain, and any figures given should be treated tentatively.

A Comprehensive History of Major Disease Outbreaks

Tracing the Past to Prevent the Future

About this dataset

This dataset provides a comprehensive record of major disease outbreaks throughout history. It includes information on the disease, the death toll, the date and location of the outbreak, and the global and regional population lost.

Disease outbreaks are a major public health issue that can have devastating consequences. This dataset can help us better understand how these diseases spread and how to prevent them in the future. By studying this data, we can learn from past mistakes and take steps to avoid repeating them

How to use the dataset

This dataset provides a comprehensive record of major disease outbreaks throughout history. It includes information on the disease, the death toll, the date and location of the outbreak, and the global and regional population lost.

To use this dataset, simply download it as a CSV file and import it into your favourite data analysis software. From there, you can begin to explore the data and understand more about how these diseases have affected people throughout history

Research Ideas

• This dataset can be used to study the history of major disease outbreaks and the effects they have had on global and regional populations.

• This dataset can be used to predict future disease outbreaks by identifying patterns and trends in past outbreaks.

• This dataset can be used to develop better strategies for responding to and preventing future disease outbreaks

Acknowledgements

The dataset was compiled by the Centers for Disease Control and Prevention (CDC)

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: df_16.csv

File: df_26.csv

File: df_20.csv

File: df_18.csv

File: df_25.csv

File: df_11.csv | Column name | Description | |:------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------| | vteNatural disasters – list by death toll | This column lists natural disasters by death toll. (Categorical) | | vteNatural disasters – list by death toll.1 | This column lists natural disasters by death toll and provides additional information on the disaster. (Categorical) |

File: df_1.csv | Column name | Description | |:-----------------------------|:----------------------------------------------------------------------------------| | Rank | The rank of the disease outbreak. (Numeric) | | Disease | The name of the disease. (String) | | Death toll | The number of deaths caused by the disease outbreak. (Numeric) | | Global population lost | The percentage of the global population lost to the disease outbreak. (Numeric) | | Regional population lost | The percentage of the regional population lost to the disease outbreak. (Numeric) | | Date | The date of the disease outbreak. (Date) | | Location | The location of the disease outbreak. (String) |

File: df_4.csv

File: df_21.csv

File: df_17.csv

File: df_24.csv

File: df_9.csv

File: df_13.csv

File: df_14.csv

File: df_22.csv

File: df_15.csv

File: df_10.csv

File: df_3.csv

File: df_19.csv

File: df_2.csv | Column name | Description | |:--------------------------|:--------------------------------------------------------------------| | Date | The date of the disease outbreak. (Date) | | Location | The location of the disease outbreak. (String) | | Disease | The name of the disease. (String) | | Event | A description of the disease outbreak. (String) ...

Although the Black Death peaked in Europe between 1348 and 1351, plague was almost always present in Britain for the next four centuries. In most years, plague was a dormant threat that affected very few people, and diseases such as smallpox and influenza were much more widespread; however, bubonic plague was prone to outbreaks that could decimate populations in a few short years. In London, plague outbreaks occurred every few decades, usually with death tolls in the tens of thousands. The duration and severity of these epidemics varied, sometimes having high death tolls but subsiding quickly, while others had relatively lower death tolls but could last for a number of years. As London's population and density also grew drastically during this period, plague affected the city differently in the sixteenth and seventeenth centuries. Great Plague of London The final major plague epidemic observed in Britain took place in 1665 and 1666. It became known as the "Great Plague" as it was the last of its kind in Britain, and its death toll eclipsed all other epidemics in the preceding century (although it was much smaller than that of the Black Death). The plague lasted for eighteen months, and had a reported death toll of more than 70,000 in this time; although modern historians estimate that the actual death toll exceeded 100,000. At its peak in September 1665, it is reported that there were more than 7,000 deaths per week, although this may have also been much higher due to the limited records kept at the time. Another reason for the lack of accurate records relating to this epidemic is because of the Great Fire of London in 1666. The fire started on September 02. 1666, and destroyed almost all of the city within the walls, leaving thousands homeless. Historians continue to debate the fire's significance, some citing that it destroyed the unsanitary dwellings where infected rats lived and drove them from the city, while others claim that the timings were purely coincidental and that the epidemic had already begun to subside in February.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

The Black Death was a pandemic that spread through Africa, Asia, and Europe. It was caused by a zoonotic disease known as the bubonic plague. This disease is transmitted by the bacterium Yersinia pestis. In England, the Black Death was an unprecedented catastrophic event dated between the years AD 1348-1350. There are multiple debates in relation to the exact mortality of the plague. However, it was estimated to have been between 30% and 60% of the population. Although traditionally it was considered that the plague had started a period of crisis, further studies indicate that the outbreak was part of a longer period of hardship that started in the 12th century. More recent studies have tackled analysing the period leading to the Black Death. However, these studies have focused exclusively on individuals living in London.This investigation aimed to evaluate childhood health in the period leading to the Black Death and its possible influence on the outbreak within and outside London to assess whether population human health was failing before the pandemic. The study sample comprised primary and secondary data from individuals from five sites outside of London (n=1341) and five sites from the London region (n=724).Individuals were examined for multiple indicators of physiological stress (cribra orbitalia, DEH), dietary indicators (vitamin C and D deficiency, folic acid), infections related to immunosuppression (tuberculosis), and estimates of disrupted growth and development (puberty stage estimation, VNC dimensions, and long bone osteometrics).Results showed evidence of stress during the late pre-Black Death period. However, when compared to the early pre- and post-Black Death periods, few statistically significant differences were found. The London region showed a significant decline in health during the Black Death period which represented not only the catastrophic outbreak but also a decline in health in the period immediately before the pandemic. This decline was followed by an improvement in health, especially for men, which reflected an increase in access to resources and higher wages after the plague. Changes in the health of females were less clear. Comparisons between regions showed different patterns, especially between males and females.These differences show the variability existing in the extra-London region concerning how the plague developed and affected rural populations. This study highlights the importance of studying health status not only after but also before a pandemic, as well as analysing regions outside London to create a more comprehensive image of health in medieval England.

BackgroundPlague is a zoonotic disease that, despite affecting humans for more than 5000 years, has historically been the subject of limited drug development activity. Drugs that are currently recommended in treatment guidelines have been approved based on animal studies alone–no pivotal clinical trials in humans have yet been completed. As a result of the sparse clinical research attention received, there are a number of methodological challenges that need to be addressed in order to facilitate the collection of clinical trial data that can meaningfully inform clinicians and policy-makers. One such challenge is the identification of clinically-relevant endpoints, which are informed by understanding the clinical characterisation of the disease–how it presents and evolves over time, and important patient outcomes, and how these can be modified by treatment.Methodology/Principal findingsThis systematic review aims to summarise the clinical profile of 1343 patients with bubonic plague described in 87 publications, identified by searching bibliographic databases for studies that meet pre-defined eligibility criteria. The majority of studies were individual case reports. A diverse group of signs and symptoms were reported at baseline and post-baseline timepoints–the most common of which was presence of a bubo, for which limited descriptive and longitudinal information was available. Death occurred in 15% of patients; although this varied from an average 10% in high-income countries to an average 17% in low- and middle-income countries. The median time to death was 1 day, ranging from 0 to 16 days.Conclusions/SignificanceThis systematic review elucidates the restrictions that limited disease characterisation places on clinical trials for infectious diseases such as plague, which not only impacts the definition of trial endpoints but has the knock-on effect of challenging the interpretation of a trial’s results. For this reason and despite interventional trials for plague having taken place, questions around optimal treatment for plague persist.

The median age at death is calculated for each municipality in Allegheny County. Data is based on the decedent's residence at the time of death, not the location where the death occurred. Median age by municipality is based on “official” death records that have been released by the Pennsylvania Department of Health. Data is broken out by race (white/black), and also includes a count of deaths for City of Pittsburgh neighborhoods and Allegheny County Municipalities.

THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

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 is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. Infant Mortality is defined as the number of deaths in infants under one year of age per 1,000 live births. Infant mortality is often used as an indicator to measure the health and well-being of a community, because factors affecting the health of entire populations can also impact the mortality rate of infants. Although California’s infant mortality rate is better than the national average, there are significant disparities, with African American babies dying at more than twice the rate of other groups. Data are from the Birth Cohort Files. The infant mortality indicator computed from the birth cohort file comprises birth certificate information on all births that occur in a calendar year (denominator) plus death certificate information linked to the birth certificate for those infants who were born in that year but subsequently died within 12 months of birth (numerator). Studies of infant mortality that are based on information from death certificates alone have been found to underestimate infant death rates for infants of all race/ethnic groups and especially for certain race/ethnic groups, due to problems such as confusion about event registration requirements, incomplete data, and transfers of newborns from one facility to another for medical care. Note there is a separate data table "Infant Mortality by Race/Ethnicity" which is based on death records only, which is more timely but less accurate than the Birth Cohort File. Single year shown to provide state-level data and county totals for the most recent year. Numerator: Infants deaths (under age 1 year). Denominator: Live births occurring to California state residents. Multiple years aggregated to allow for stratification at the county level. For this indicator, race/ethnicity is based on the birth certificate information, which records the race/ethnicity of the mother. The mother can “decline to state”; this is considered to be a valid response. These responses are not displayed on the indicator visualization.

Pestis secunda (1356–1366 CE) is the first of a series of plague outbreaks in Europe that followed the Black Death (1346–1353 CE). Collectively this period is called the Second Pandemic. From a genomic perspective, the majority of post-Black Death strains of Yersinia pestis thus far identified in Europe display diversity accumulated over a period of centuries that form a terminal sub-branch of the Y. pestis phylogeny. It has been debated if these strains arose from local evolution of Y. pestis or if the disease was repeatedly reintroduced from an external source. Plague lineages descended from the pestis secunda, however, are thought to have persisted in non-human reservoirs outside Europe, where they eventually gave rise to the Third Pandemic (19th and 20th centuries). Resolution of competing hypotheses on the origins of the many post-Black Death outbreaks has been hindered in part by the low representation of Y. pestis genomes in archaeological specimens, especially for the pestis secunda. Here we report on five individuals from Germany that were infected with lineages of plague associated with the pestis secunda. For the two genomes of high coverage, one groups within the known diversity of genotypes associated with the pestis secunda, while the second carries an ancestral genotype that places it earlier. Through consideration of historical sources that explore first documentation of the pandemic in today’s Central Germany, we argue that these data provide robust evidence to support a post-Black Death evolution of the pathogen within Europe rather than a re-introduction from outside. Additionally, we demonstrate retrievability of Y. pestis DNA in post-cranial remains and highlight the importance of hypothesis-free pathogen screening approaches in evaluations of archaeological samples.

Note: Note: Starting October 10th, 2025 this dataset is deprecated and is no longer being updated. As of April 27, 2023 updates changed from daily to weekly.

Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by race and ethnicity: African American; White; Hispanic; Asian; Other; Unknown.

Description The MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by categories of race and ethnicity. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution data layer.

Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

The successful reconstruction of an ancient bacterial genome from archaeological material presents an important methodological advancement for infectious disease research. The reliability of evolutionary histories inferred by the incorporation of ancient data, however, are highly contingent upon the level of genetic diversity represented in modern genomic sequences that are publicly accessible, and the paucity of available complete genomes restricts the level of phylogenetic resolution that can be obtained. Here we add to our original analysis of the Yersinia pestis strain implicated in the Black Death by consolidating our dataset for 18 modern genomes with single nucleotide polymorphism (SNP) data for an additional 289 strains at over 600 positions. The inclusion of this additional data reveals a cluster of Y. pestis strains that diverge at a time significantly in advance of the Black Death, with divergence dates roughly coincident with the Plague of Justinian (6th to 8th century AD). In addition, the analysis reveals further clues regarding potential radiation events that occurred immediately preceding the Black Death, and the legacy it may have left in modern Y. pestis populations. This work reiterates the need for more publicly available complete genomes, both modern and ancient, to achieve an accurate understanding of the history of this bacterium.

Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

BackgroundAccording to one USA Renal Data System report, 57% of end-stage renal disease (ESRD) cases are attributed to hypertensive and diabetic nephropathy. Yet, trends in hypertension related ESRD mortality rates in adults ≥ 35 years of age have not been studied.ObjectivesThe aim of this retrospective study was to analyze the different trends hypertension related ESRD death rates among adults in the United States.MethodsDeath records from the CDC (Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research) database were analyzed from 1999 to 2020 for hypertension related ESRD mortality in adults ≥ 35 years of age. Age-Adjusted mortality rates (AAMRs) per 100,000 persons and annual percent change (APC) were calculated and stratified by year, sex, race/ethnicity, place of death, and geographic location.ResultsHypertension-related ESRD caused a total of 721,511 deaths among adults (aged ≥ 35 years) between 1999 and 2020. The overall AAMR for hypertension related ESRD deaths in adults was 9.70 in 1999 and increased all the way up to 43.7 in 2020 (APC: 9.02; 95% CI: 8.19-11.04). Men had consistently higher AAMRs than woman during the analyzed years from 1999 (AAMR men: 10.8 vs women: 9) to 2020 (AAMR men: 52.2 vs women: 37.2). Overall AAMRs were highest in Non-Hispanic (NH) Black or African American patients (45.7), followed by NH American Indian or Alaska Natives (24.7), Hispanic or Latinos (23.4), NH Asian or Pacific Islanders (19.3), and NH White patients (15.4). Region-wise analysis also showed significant variations in AAMRs (overall AAMR: West 21.2; South: 21; Midwest: 18.3; Northeast: 14.2). Metropolitan areas had slightly higher AAMRs (19.1) than nonmetropolitan areas (19). States with AAMRs in 90th percentile: District of Columbia, Oklahoma, Mississippi, Tennessee, Texas, and South Carolina, had roughly double rates compared to states in 10th percentile.ConclusionsOverall hypertension related ESRD AAMRs among adults were seen to increase in almost all stratified data. The groups associated with the highest death rates were NH Black or African Americans, men, and populations in the West and metropolitan areas of the United States. Strategies and policies targeting these at-risk groups are required to control the rising hypertension related ESRD mortality.

This dataset documents rates and trends in heart disease and stroke mortality. Specifically, this report presents county (or county equivalent) estimates of heart disease and stroke death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (women, men). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

Coroner’s Inquisitions are investigations into the deaths of individuals who died by a sudden, violent, unnatural, or suspicious manner, or who died without medical attendance. The coroner would summon a jury of twelve white men, usually prominent citizens of that locality, to assist him in determining cause of death. The jury viewed the body of the deceased and heard the testimony of witnesses which did include both white and Black perspectives. This witness testimony was recorded and after seeing and hearing the evidence, a white jury delivered in writing to the coroner their conclusion concerning cause of death referred to as the inquisition. These causes of death would be determined by a white perspective and Black individuals were only consulted; they were never in a position to make decisions. If a criminal act was determined to be the cause of death, the coroner delivered the guilty person to the sheriff and the inquests would be used as evidence in the criminal trial. In this case, coroner’s inquisitions were filed with the trial papers. See Commonwealth Causes for more. If there was not a trial, coroner’s inquisitions were filed separately and will likely appear in this collection as a stand alone set of documents.

Documents commonly found in coroner’s inquisitions include the inquisition, depositions, and summons. Information found in the inquisition include the name of the coroner, the names of the jurors, the name and age of the deceased if known, gender and race of the deceased, and when, how, and by what means the deceased came to his or her death. If the coroner knew the deceased person to be Black or multiracial, the inquest should identify the person as enslaved; a “free Negro”; a “person of color”; or a “mulatto.” If the coroner knew the deceased person to be enslaved, the inquest should include their name, their enslaver and the enslaver’s residence. Information found in the depositions include the name of the deponent and his or her account of the circumstances that led to the death of the deceased. Unlike many other legal proceedings in antebellum Virginia, enslaved people were permitted to provide depositions for coroners’ inquisitions.

This data is subset focusing on records where African Americans were named either as the deceased or persons of interest involved in the inquest and is a by-product of indexing done for the Virginia Untold: African American Narrative digital collection.

Some data in this collection is drawn directly from the original historical records (see column descriptions) and may contain terminology which is now deemed offensive.

Do pandemics have lasting consequences for political behavior? The authors address this question by examining the consequences of the deadliest pandemic of the last millennium: the Black Death (1347–1351). They claim that pandemics can influence politics in the long run if the loss of life is high enough to increase the price of labor relative to other factors of production. When this occurs, labor-repressive regimes like serfdom become untenable, which ultimately leads to the development of proto-democratic institutions and associated political cultures that shape modalities of political engagement for generations. The authors test their theory by tracing the consequences of the Black Death in German-speaking Central Europe. They find that areas hit hardest by that pandemic were more likely to adopt inclusive political institutions and equitable land ownership patterns, to exhibit electoral behavior indicating independence from landed elite influence during the transition to mass politics, and to have significantly lower vote shares for Hitler’s National Socialist Party in the Weimar Republic’s fateful 1930 and July 1932 elections.

Absolute changes in life expectancy at age 20 among people in prisons, by race & sex across periods, 2000–2014.

Mortality rates (per 10,000 prisoners) and the relative percentage change in prisoner mortality for forty-four states reporting to the NCRP, 2000–2014.

BackgroundThe COVID-19 pandemic has significantly impacted global health, with diverse factors influencing the risk of death among reported cases. This study mainly analyzes the main characteristics that have contributed to the increase or decrease in the risk of death among Severe Acute Respiratory Syndrome (SARS) cases classified as COVID-19 reported in southeast Brazil from 2020 to 2023.MethodsThis cohort study utilized COVID-19 notification data from the Sistema de Vigilância Epidemiológica (SIVEP) information system in the southeast region of Brazil from 2020 to 2023. Data included demographics, comorbidities, vaccination status, residence area, and survival outcomes. Classical Cox, Cox mixed effects, Prentice, Williams & Peterson (PWP), and PWP fragility models were used to assess the risk of dying over time.ResultsAcross 987,534 cases, 956,961 hospitalizations, and 330,343 deaths were recorded over the period. Mortality peaked in 2021. The elderly, males, black individuals, lower-educated, and urban residents faced elevated risks. Vaccination reduced death risk by around 20% and 13% in 2021 and 2022, respectively. Hospitalized individuals had lower death risks, while comorbidities increased risks by 20–26%.ConclusionThe study identified demographic and comorbidity factors influencing COVID-19 mortality. Rio de Janeiro exhibited the highest risk, while São Paulo had the lowest. Vaccination significantly reduces death risk. Findings contribute to understanding regional mortality variations and guide public health policies, emphasizing the importance of targeted interventions for vulnerable groups.