Estimates for the total death count of the Second World War generally range somewhere between 70 and 85 million people. The Soviet Union suffered the highest number of fatalities of any single nation, with estimates mostly falling between 22 and 27 million deaths. China then suffered the second greatest, at around 20 million, although these figures are less certain and often overlap with the Chinese Civil War. Over 80 percent of all deaths were of those from Allied countries, and the majority of these were civilians. In contrast, 15 to 20 percent were among the Axis powers, and the majority of these were military deaths, as shown in the death ratios of Germany and Japan. Civilian deaths and atrocities It is believed that 60 to 67 percent of all deaths were civilian fatalities, largely resulting from war-related famine or disease, and war crimes or atrocities. Systematic genocide, extermination campaigns, and forced labor, particularly by the Germans, Japanese, and Soviets, led to the deaths of millions. In this regard, Nazi activities alone resulted in 17 million deaths, including six million Jews in what is now known as The Holocaust. Not only was the scale of the conflict larger than any that had come before, but the nature of and reasoning behind this loss make the Second World War stand out as one of the most devastating and cruelest conflicts in history. Problems with these statistics Although the war is considered by many to be the defining event of the 20th century, exact figures for death tolls have proven impossible to determine, for a variety of reasons. Countries such as the U.S. have fairly consistent estimates due to preserved military records and comparatively few civilian casualties, although figures still vary by source. For most of Europe, records are less accurate. Border fluctuations and the upheaval of the interwar period mean that pre-war records were already poor or non-existent for many regions. The rapid and chaotic nature of the war then meant that deaths could not be accurately recorded at the time, and mass displacement or forced relocation resulted in the deaths of many civilians outside of their homeland, which makes country-specific figures more difficult to find. Early estimates of the war’s fatalities were also taken at face value and formed the basis of many historical works; these were often very inaccurate, but the validity of the source means that the figures continue to be cited today, despite contrary evidence.

In comparison to Europe, estimate ranges are often greater across Asia, where populations were larger but pre-war data was in short supply. Many of the Asian countries with high death tolls were European colonies, and the actions of authorities in the metropoles, such as the diversion of resources from Asia to Europe, led to millions of deaths through famine and disease. Additionally, over one million African soldiers were drafted into Europe’s armies during the war, yet individual statistics are unavailable for most of these colonies or successor states (notably Algeria and Libya). Thousands of Asian and African military deaths went unrecorded or are included with European or Japanese figures, and there are no reliable figures for deaths of millions from countries across North Africa or East Asia. Additionally, many concentration camp records were destroyed, and such records in Africa and Asia were even sparser than in Europe. While the Second World War is one of the most studied academic topics of the past century, it is unlikely that we will ever have a clear number for the lives lost in the conflict.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

As of 2023, the countries with the highest death rates worldwide were Monaco, Bulgaria, and Latvia. In these countries, there were ** to ** deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just *** death per 1,000 people. Leading causes of death The leading causes of death worldwide are, by far, cardiovascular diseases, accounting for ** percent of all deaths in 2021. That year, there were **** million deaths worldwide from ischaemic heart disease and **** million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2023, there were around **** million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined ** percent of all deaths in 2023. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around ****** deaths among men alone in the year 2025. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2023, the tenth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019, and it was the third leading cause of death in the U.S. during those years.

Number and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.

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.

Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implemented these case definitions. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported from state and local health departments through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration and set up alerts to monitor for discrepancies in the data.
• CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• County level data were aggregated to obtain state- and territory- specific totals.
• Counting of cases and deaths is based on date of report and not on the date of symptom onset. CDC calculates rates in these data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data are organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts are calculated as the week-to-week change in cumulative counts of cases and deaths reported (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the prior week.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues.

Description This archived public use dataset focuses on the cumulative and weekly case and death rates per 100,000 persons within various sociodemographic factors across all states and their counties. All resulting data are expressed as rates calculated as the number of cases or deaths per 100,000 persons in counties meeting various classification criteria using the US Census Bureau Population Estimates Program (2019 Vintage).

Each county within jurisdictions is classified into multiple categories for each factor. All rates in this dataset are based on classification of counties by the characteristics of their population, not individual-level factors. This applies to each of the available factors observed in this dataset. Specific factors and their corresponding categories are detailed below.

Population-level factors Each unique population factor is detailed below. Please note that the “Classification” column describes each of the 12 factors in the dataset, including a data dict

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

THIS DATASET WAS LAST UPDATED AT 2:11 PM EASTERN ON SEPT. 7

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.

The American Civil War is the conflict with the largest number of American military fatalities in history. In fact, the Civil War's death toll is comparable to all other major wars combined, the deadliest of which were the World Wars, which have a combined death toll of more than 520,000 American fatalities. The ongoing series of conflicts and interventions in the Middle East and North Africa, collectively referred to as the War on Terror in the west, has a combined death toll of more than 7,000 for the U.S. military since 2001. Other records In terms of the number of deaths per day, the American Civil War is still at the top, with an average of 425 deaths per day, while the First and Second World Wars have averages of roughly 100 and 200 fatalities per day respectively. Technically, the costliest battle in U.S. military history was the Battle of Elsenborn Ridge, which was a part of the Battle of the Bulge in the Second World War, and saw upwards of 5,000 deaths over 10 days. However, the Battle of Gettysburg had more military fatalities of American soldiers, with almost 3,200 Union deaths and over 3,900 Confederate deaths, giving a combined total of more than 7,000. The Battle of Antietam is viewed as the bloodiest day in American military history, with over 3,600 combined fatalities and almost 23,000 total casualties on September 17, 1862. Revised Civil War figures For more than a century, the total death toll of the American Civil War was generally accepted to be around 620,000, a number which was first proposed by Union historians William F. Fox and Thomas L. Livermore in 1888. This number was calculated by using enlistment figures, battle reports, and census data, however many prominent historians since then have thought the number should be higher. In 2011, historian J. David Hacker conducted further investigations and claimed that the number was closer to 750,000 (and possibly as high as 850,000). While many Civil War historians agree that this is possible, and even likely, obtaining consistently accurate figures has proven to be impossible until now; both sides were poor at keeping detailed records throughout the war, and much of the Confederacy's records were lost by the war's end. Many Confederate widows also did not register their husbands death with the authorities, as they would have then been ineligible for benefits.

This is the first attempt to record the Jewish soldiers who became casualties in the numerous Wars between the Habsburg Monarchy and Revolutionary and Napoleonic France. Jewish military service in the Austrian and Austro-Hungarian army from the mid-19th century onwards, especially during the First World War, is well known and documented. By contrast, nothing comparable has been done for the very first Jewish soldiers in modern history. The time has come to set the record straight!

The current database was compiled from the personal records of the War Archive (Kriegsarchiv) of the Austrian State Archives. At that time, the Habsburg army did not publish casualty lists other than mentioning the names of the most senior officers. To find individual Jewish soldiers who became casualties, one must identify serving Jewish soldiers in the regular musters and revision papers. Those found so far can be seen in the database Jewish Soldiers of the Habsburg Army (1788-1820), which should be used in parallel with this one. The current database offers an outtake with a separate list of Jewish soldiers who were killed, wounded, missing in action, or taken prisoner. The first version has 253 entries. These are arranged chronologically based on the date the soldier first became a casualty. The name of the battle or the action shows at the top of the table. Under each such action, up to four sub-categories are given:

1. K/KIA (Killed in Action) – Soldier killed outright in combat. Readers might be surprised how few such cases appear in the database. There are several possible reasons. Firstly, since 1781 the Habsburg manpower reports began to omit the rubric Vor Feind geblieben (left in front of the enemy) denoting soldiers killed in battle. This was part of a broader rationalisation of military records in the early days of Joseph II’s rule. Whichever was the cause of their death, all fatalities were now perceived as irrecoverable manpower wastage. Soldiers who died in service were now simply marked as gestorben. Identifying combat deaths is only possible by looking at monthly reports called Standes- und Diensttabellen. Even then, the number of combat deaths remains extraordinarily low. It appears that the Habsburg army formally recorded a soldier as ‘killed in action’ only if the body was identified. For this to happen, the army had to remain in control of the battlefield – in other words, the battle had to be won. For much of the Revolutionary and Napoleonic period, this was rarely the case on the Austrian side. It appears that most combat deaths in the period landed in the rubric as ‘missing-in-action’.

2. W/WIA (Wounded in Action) – Muster rolls did not record wounds at all. Monthly tables did so very rarely. The latter were intended primarily as financial documents to record the source of the men’s pay. When a soldier entered hospital, his pay was issued from the hospital fund whose accounts were later reimbursed by the man’s regiment. While dates of hospitalisation were meticulously recorded, the cause of hospitalisation was not mentioned. In most cases, identifying wounded soldiers can only be done indirectly. When dozens or hundreds of men from the same unit were hospitalised on the same day directly after a major battle, it can be reasonably assumed that these were combat casualties. A sure way of identifying a wounded soldier was through the medical evaluation papers (Superarbitrierungs-Liste), which were filed for men no longer fit for wartime service. These papers always mentioned combat wounds, as this was a major argument in favour of making the soldier eligible for admission into the invalids. Unfortunately, the survival rate of these documents is variable and the majority simply do not exist. This database employs two categories for wounded soldiers. When medical papers or hospitalisation date allows clear identification, a soldier is entered into the database as a certain case. When broader context allows (such as wartime service and numerous other hospitalisations from the same company on the same day, suggesting a skirmish), such men are entered as probable cases.

3. P/POW (Prisoner of War) – Unlike the previous two rubrics, the Habsburg military records usually mentioned soldiers taken prisoner (Kriegsgefangen/ In Kriegsgefangenschaft gefallen). The reason was again financial. Firstly, returning men had to be issued with backpay. Secondly, from the Third Coalition War onwards, reciprocal wartime prisoner swaps (Cartel) were discontinued, but the system remained in place to ensure that mutual settlement of accounts between two belligerent armies could happen after the war. This is not the only reason why prisoners make the largest single category in our database. For much of the Revolutionary and Napoleonic period, entire Austrian army corps were forced to surrender (for instance in Ulm in 1805). This happened so often that musters from 1806 and 1811 sometimes blankly omitted case of POWs, based on the assumption that nearly every soldier fell prisoner in the previous war. Therefore, for regiments who fought in Germany and Austerlitz in 1805, and in Bavaria and Deutsch-Wagram in 1809, one must also consult the monthly tables.

4. M/MIA (Missing in Action) – Recorded as Vor Feind vermisst or vermisst for short, this category denotes men who were missing when the battle ended. Anything could have happened to them. Some were dead (see rubric one), but others were taken prisoner, were lost, or deserted. The army recorded such missing men for the same reason as prisoners of war – to settle their backpay in future if necessary.

The total for each category of casualties is given at the bottom of the table for every war fought by the Habsburg army from 1792 to 1815. At the right hand side of the table are the grand totals for each category marked in red. At the end of every personal record are fields showing what happened to the soldier after he became a casualty. Wounded could recover or perish in hospital, while the prisoners and the missing could return. The same soldier could appear in the database more than once as he could be taken prisoner, be wounded or go missing several times. Only for those killed in action could the record be closed. For those who survived, the final fate was noted where known: discharge (including sub category), invaliding, desertion, or non-combat death. Men still in service when last mentioned in the documents are noted as ‘serves’. Whether complete or not, a detailed service record for each soldier as as I could reconstruct it from the sources is available in the database Jewish Soldiers of the Habsburg Army (1788-1820).

Norway Vital Statistics: Death per 1000 Persons data was reported at 7.750 NA in 2017. This records a decrease from the previous number of 7.810 NA for 2016. Norway Vital Statistics: Death per 1000 Persons data is updated yearly, averaging 16.970 NA from Dec 1735 (Median) to 2017, with 283 observations. The data reached an all-time high of 52.200 NA in 1742 and a record low of 7.750 NA in 2017. Norway Vital Statistics: Death per 1000 Persons data remains active status in CEIC and is reported by Statistics Norway. The data is categorized under Global Database’s Norway – Table NO.G004: Vital Statistics. Data since Jan 1760 is available in CEIC upon individual request.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

This table provides Canadians and researchers with 2020 mortality data for all-causes and selected causes of death by neighbourhood income quintile. The data are available for Canada (excluding territories) and for selected regions.

A trend of the number of deaths per accident and death rate per 100,000 people is illustrated over the last ten years, 2011–2020. Two reports of death counts during Songkran festival and New Year holiday are given by the Injury Data Collaboration Center (IDCC) and Department of Disaster Prevention and Mitigation (DDPM). (XLSX)

COVID-19 Cases information is reported through the Pennsylvania State Department’s National Electronic Disease Surveillance System (PA-NEDSS). As new cases are passed to the Allegheny County Health Department they are investigated by case investigators. During investigation some cases which are initially determined by the State to be in the Allegheny County jurisdiction may change, which can account for differences between publication of the files on the number of cases, deaths and tests. Additionally, information is not always reported to the State in a timely manner, delays can range from days to weeks, which can also account for discrepancies between previous and current files. Test and Case information will be updated daily. This resource contains individuals who received a COVID-19 test and individuals whom are probable cases. Every day, these records are overwritten with updates. Each row in the data reflects a person that is tested, not tests that are conducted. People that are tested more than once will have their testing and case data updated using the following rules:

1. Positive tests overwrite negative tests.
2. Polymerase chain reaction (PCR) tests overwrite antibody or antigen (AG) tests.
3. The first positive PCR test is never overwritten. Data collected from additional tests do not replace the first positive PCR test.

Note: On April 4th 2022 the Pennsylvania Department of Health no longer required labs to report negative AG tests. Therefore aggregated counts that included AG tests have been removed from the Municipality/Neighborhood files going forward. Versions of this data up to this cut-off have been retained as archived files.

Individual Test information is also updated daily. This resource contains the details and results of individual tests along with demographic information of the individual tested. Only PCR and AG tests are included. Every day, these records are overwritten with updates. This resource should be used to determine positivity rates.

The remaining datasets provide statistics on death demographics. Demographic, municipality and neighborhood information for deaths are reported on a weekly schedule and are not included with individual cases or tests. This has been done to protect the privacy and security of individuals and their families in accordance with the Health Insurance Portability and Accountability Act (HIPAA). Municipality or City of Pittsburgh Neighborhood is based off the geocoded home address of the individual tested.

Individuals whose home address is incomplete may not be in Allegheny County but whose temporary residency, work or other mitigating circumstance are determined to be in Allegheny County by the Pennsylvania Department of Health are counted as "Undefined".

Since the start of the pandemic, the ACHD has mapped every day’s COVID tests, cases, and deaths to their Allegheny County municipality and neighborhood. Tests were mapped to patient address, and if this was not available, to the provider location. This has recently resulted in apparent testing rates that exceeded the populations of various municipalities -- mostly those with healthcare providers. As this was brought to our attention, the health department and our data partners began researching and comparing methods to most accurately display the data. This has led us to leave those with missing home addresses off the map. Although these data will still appear in test, case and death counts, there will be over 20,000 fewer tests and almost 1000 fewer cases on the map. In addition to these map changes, we have identified specific health systems and laboratories that had data uploading errors that resulted in missing locations, and are working with them to correct these errors.

Due to minor discrepancies in the Municipal boundary and the City of Pittsburgh Neighborhood files individuals whose City Neighborhood cannot be identified are be counted as “Undefined (Pittsburgh)”.

On May 19, 2023, with the rescinding of the COVID-19 public health emergency, changes in data and reporting mechanisms prompted a change to an annual data sharing schedule for tests, cases, hospitalizations, and deaths. Dates for annual release are TBD. The weekly municipal counts and individual data produced before this changed are maintained as archive files.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

This is the number of people of all ages killed or seriously injured (KSI) in road traffic accidents, in an area, adjusted. This indicator includes only casualties who are fatally or seriously injured and these categories are defined as follows:

Fatal casualties are those who sustained injuries which caused death less than 30 days after the accident; confirmed suicides are excluded.

Seriously injured casualties are those who sustained an injury for which they are detained in hospital as an in-patient, or any of the following injuries, whether or not they are admitted to hospital: fractures, concussion, internal injuries, crushings, burns (excluding friction burns), severe cuts and lacerations, severe general shock requiring medical treatment and injuries causing death 30 or more days after the accident.

An injured casualty is recorded as seriously or slightly injured by the police on the basis of information available within a short time of the collision. This generally will not reflect the results of a medical examination, but may be influenced according to whether the casualty is hospitalised or not. Hospitalisation procedures will vary regionally.

Slight injuries are excluded from the total, such as a sprain (including neck whiplash injury), bruise or cut which are not judged to be severe, or slight shock requiring roadside attention.

Police forces use one of two systems for recording reported road traffic collisions; the CRaSH (Collision Recording and Sharing) or COPA (Case Overview Preparation Application). Estimates are calculated from figures which are as reported by police. Since 2016, changes in severity reporting systems for a large number of police forces mean that serious injury figures, and to a lesser extent slight injuries, are not comparable with earlier years. As a result, both adjusted and unadjusted killed or seriously injured statistics are available. Further information about the reporting systems can be found here.

Areas with low resident populations but have high inflows of people or traffic may have artificially high rates because the at-risk resident population is not an accurate measure of exposure to transport. This is likely to affect the results for employment centres e.g. City of London and sparsely populated rural areas which have high numbers of visitors or through traffic. Counts for Heathrow Airport are included in the London Region and England totals only.

From the publication of the 2023 statistics onwards, casualty rates shown in table RAS0403 to include rates based on motor vehicle traffic only. This is because the department does not consider pedal cycle traffic to be robust at the local authority level.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.