Overview

The Marshall Project, the nonprofit investigative newsroom dedicated to the U.S. criminal justice system, has partnered with The Associated Press to compile data on the prevalence of COVID-19 infection in prisons across the country. The Associated Press is sharing this data as the most comprehensive current national source of COVID-19 outbreaks in state and federal prisons.

Lawyers, criminal justice reform advocates and families of the incarcerated have worried about what was happening in prisons across the nation as coronavirus began to take hold in the communities outside. Data collected by The Marshall Project and AP shows that hundreds of thousands of prisoners, workers, correctional officers and staff have caught the illness as prisons became the center of some of the country’s largest outbreaks. And thousands of people — most of them incarcerated — have died.

In December, as COVID-19 cases spiked across the U.S., the news organizations also shared cumulative rates of infection among prison populations, to better gauge the total effects of the pandemic on prison populations. The analysis found that by mid-December, one in five state and federal prisoners in the United States had tested positive for the coronavirus -- a rate more than four times higher than the general population.

This data, which is updated weekly, is an effort to track how those people have been affected and where the crisis has hit the hardest.

Methodology and Caveats

The data tracks the number of COVID-19 tests administered to people incarcerated in all state and federal prisons, as well as the staff in those facilities. It is collected on a weekly basis by Marshall Project and AP reporters who contact each prison agency directly and verify published figures with officials.

Each week, the reporters ask every prison agency for the total number of coronavirus tests administered to its staff members and prisoners, the cumulative number who tested positive among staff and prisoners, and the numbers of deaths for each group.

The time series data is aggregated to the system level; there is one record for each prison agency on each date of collection. Not all departments could provide data for the exact date requested, and the data indicates the date for the figures.

To estimate the rate of infection among prisoners, we collected population data for each prison system before the pandemic, roughly in mid-March, in April, June, July, August, September and October. Beginning the week of July 28, we updated all prisoner population numbers, reflecting the number of incarcerated adults in state or federal prisons. Prior to that, population figures may have included additional populations, such as prisoners housed in other facilities, which were not captured in our COVID-19 data. In states with unified prison and jail systems, we include both detainees awaiting trial and sentenced prisoners.

To estimate the rate of infection among prison employees, we collected staffing numbers for each system. Where current data was not publicly available, we acquired other numbers through our reporting, including calling agencies or from state budget documents. In six states, we were unable to find recent staffing figures: Alaska, Hawaii, Kentucky, Maryland, Montana, Utah.

To calculate the cumulative COVID-19 impact on prisoner and prison worker populations, we aggregated prisoner and staff COVID case and death data up through Dec. 15. Because population snapshots do not account for movement in and out of prisons since March, and because many systems have significantly slowed the number of new people being sent to prison, it’s difficult to estimate the total number of people who have been held in a state system since March. To be conservative, we calculated our rates of infection using the largest prisoner population snapshots we had during this time period.

As with all COVID-19 data, our understanding of the spread and impact of the virus is limited by the availability of testing. Epidemiology and public health experts say that aside from a few states that have recently begun aggressively testing in prisons, it is likely that there are more cases of COVID-19 circulating undetected in facilities. Sixteen prison systems, including the Federal Bureau of Prisons, would not release information about how many prisoners they are testing.

Corrections departments in Indiana, Kansas, Montana, North Dakota and Wisconsin report coronavirus testing and case data for juvenile facilities; West Virginia reports figures for juvenile facilities and jails. For consistency of comparison with other state prison systems, we removed those facilities from our data that had been included prior to July 28. For these states we have also removed staff data. Similarly, Pennsylvania’s coronavirus data includes testing and cases for those who have been released on parole. We removed these tests and cases for prisoners from the data prior to July 28. The staff cases remain.

About the Data

There are four tables in this data:

• covid_prison_cases.csv contains weekly time series data on tests, infections and deaths in prisons. The first dates in the table are on March 26. Any questions that a prison agency could not or would not answer are left blank.

• prison_populations.csv contains snapshots of the population of people incarcerated in each of these prison systems for whom data on COVID testing and cases are available. This varies by state and may not always be the entire number of people incarcerated in each system. In some states, it may include other populations, such as those on parole or held in state-run jails. This data is primarily for use in calculating rates of testing and infection, and we would not recommend using these numbers to compare the change in how many people are being held in each prison system.

• staff_populations.csv contains a one-time, recent snapshot of the headcount of workers for each prison agency, collected as close to April 15 as possible.

• covid_prison_rates.csv contains the rates of cases and deaths for prisoners. There is one row for every state and federal prison system and an additional row with the National totals.

Queries

The Associated Press and The Marshall Project have created several queries to help you use this data:

Get your state's prison COVID data: Provides each week's data from just your state and calculates a cases-per-100000-prisoners rate, a deaths-per-100000-prisoners rate, a cases-per-100000-workers rate and a deaths-per-100000-workers rate here

Rank all systems' most recent data by cases per 100,000 prisoners here

Find what percentage of your state's total cases and deaths -- as reported by Johns Hopkins University -- occurred within the prison system here

Attribution

In stories, attribute this data to: “According to an analysis of state prison cases by The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system, and The Associated Press.”

Contributors

Many reporters and editors at The Marshall Project and The Associated Press contributed to this data, including: Katie Park, Tom Meagher, Weihua Li, Gabe Isman, Cary Aspinwall, Keri Blakinger, Jake Bleiberg, Andrew R. Calderón, Maurice Chammah, Andrew DeMillo, Eli Hager, Jamiles Lartey, Claudia Lauer, Nicole Lewis, Humera Lodhi, Colleen Long, Joseph Neff, Michelle Pitcher, Alysia Santo, Beth Schwartzapfel, Damini Sharma, Colleen Slevin, Christie Thompson, Abbie VanSickle, Adria Watson, Andrew Welsh-Huggins.

Questions

If you have questions about the data, please email The Marshall Project at info+covidtracker@themarshallproject.org or file a Github issue.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

This open-access geospatial dataset (downloadable in csv or shapefile format) contains a total of 11 environmental indicators calculated for 1865 U.S. prisons. This consists of all active state- and federally-operated prisons according to the Homeland Infrastructure Foundation-Level Data (HIFLD), last updated June 2022. This dataset includes both raw values and percentiles for each indicator. Percentiles denote a way to rank prisons among each other, where the number represents the percentage of prisons that are equal to or have a lower ranking than that prison. Higher percentile values indicate higher vulnerability to that specific environmental burden compared to all the other prisons. Full descriptions of how each indicator was calculated and the datasets used can be found here: https://github.com/GeospatialCentroid/NASA-prison-EJ/blob/main/doc/indicator_metadata.md.

From these raw indicator values and percentiles, we also developed three individual component scores to summarize similar indicators, and to then create a single vulnerability index (methods based on other EJ screening tools such as Colorado Enviroscreen, CalEnviroScreen and EPA’s EJ Screen). The three component scores include climate vulnerability, environmental exposures and environmental effects. Climate vulnerability factors reflect climate change risks that have been associated with health impacts and includes flood risk, wildfire risk, heat exposure and canopy cover indicators. Environmental exposures reflect variables of different types of pollution people may come into contact with (but not a real-time exposure to pollution) and includes ozone, particulate matter (PM 2.5), traffic proximity and pesticide use. Environmental effects indicators are based on the proximity of toxic chemical facilities and includes proximity to risk management plan (RMP) facilities, National Priority List (NPL)/Superfund facilities, and hazardous waste facilities. Component scores were calculated by taking the geometric mean of the indicator percentiles. Using the geometric mean was most appropriate for our dataset since many values may be related (e.g., canopy cover and temperature are known to be correlated).

To calculate a final, standardized vulnerability score to compare overall environmental burdens at prisons across the U.S., we took the average of each component score and then converted those values to a percentile rank. While this index only compares environmental burdens among prisons and is not comparable to non-prison sites/communities, it will be able to heighten awareness of prisons most vulnerable to negative environmental impacts at county, state and national scales. As an open-access dataset it also provides new opportunities for other researchers, journalists, activists, government officials and others to further analyze the data for their needs and make comparisons between prisons and other communities. This is made even easier as we produced the methodology for this project as an open-source code base so that others can apply the code to calculate individual indicators for any spatial boundaries of interest. The codebase can be found on GitHub (https://github.com/GeospatialCentroid/NASA-prison-EJ) and is also published via Zenodo (https://zenodo.org/record/8306856).

Investigator(s): Bureau of Justice Statistics The National Jail Census was conducted by the U.S. Census Bureau for the Bureau of Justice Statistics. Excluded from the census were federal- or state-administered facilities, including the combined jail-prison systems in Alaska, Connecticut, Delaware, Hawaii, Rhode Island, and Vermont. Data include jail population by reason being held, age (juvenile or adult) and sex, maximum sentence that can be served in the facility, available services, type of security available, facility capacity, age, construction and renovation of the facility, employment, and operating expenditures.Years Produced: Every 5 years

This dataset shows the number of people that are in prison by state in 2006 and 2007. These numbers are then compared to show the difference between the two years and a percentage of change is given as well. This data was brought to our attention by the Pew Charitable Trusts in their report titled, One in 100: Behind Bars in America 2008."" The main emphasis of the article emphasizes the point that in 2007 1 in every 100 Americans were in prison. To note: Many states have not completed their data verification process. Final published figures may differ slightly. The District of Columbia is not included. D.C. prisoners were transferred to federal custody in 2001

The purpose of the Survey of Jails in Indian Country is an enumeration of all known adult and juvenile facilities -- jails, confinement facilities, detention centers, and other correctional facilities operated by tribal authorities or by the Bureau of Indian Affairs (BIA)in the United States Department of the Interior. For the purpose of this collection, Indian country includes reservations, pueblos, rancherias, and other Native American and Alaska Native communities throughout the United States. The survey collects data on the number of adults and juveniles held on the last weekday in June 2009, type of offense, average daily population in June, most crowded day in June, admissions and releases in June, number of inmate deaths and suicide attempts, rated capacity, and jail staffing.

This dataset shows the total amount of State Prison Expenditures for Medical Care, Food expenses, and Utilities in the year 2001. Over a quarter of prison operating costs are for basic living expenses. Prisoner medical care, food service, utilities, and contract housing totaled $7.3 billion, or about 26% of State prison current operating expenses. Inmate medical care totaled $3.3 billion, or about 12% of operating expenditures. Supplies and services of government staff and full-time and part-time managed care and fee-for service providers averaged $2,625 per inmate, or $7.19 per day. By comparison, the average annual health care expenditure of U.S. residents, including all sources in FY 2001, was $4,370, or $11.97 per day. Factors beyond the scope of this report contributed to the variation in spending levels for prisoner medical care. Lacking economies of scale, some States had significantly higher than average medical costs for everyone, and some had higher proportions of inmates whose abuse of drugs or alcohol had led to disease. Also influencing variations in expenditures were staffing and funding of prisoner health care and distribution of specialized medical equipment for prisoner treatment. Food service in FY 2001 cost $1.2 billion, or approximately 4% of State prison operating expenditures. On average nationwide, State departments of correction spent $2.62 to feed inmates each day. Utility services for electricity, natural gas, heating oil, water, sewerage, trash removal, and telephone in State prisons totaled $996 million in FY 2001. Utilities accounted for about 3.5% of State prison operating expenditure. For more information see the url source of this dataset.

ObjectivesTo systematically review recidivism rates internationally, report whether they are comparable and, on the basis of this, develop best reporting guidelines for recidivism.MethodsWe searched MEDLINE, Google Web, and Google Scholar search engines for recidivism rates around the world, using both non-country-specific searches as well as targeted searches for the 20 countries with the largest total prison populations worldwide.ResultsWe identified recidivism data for 18 countries. Of the 20 countries with the largest prison populations, only 2 reported repeat offending rates. The most commonly reported outcome was 2-year reconviction rates in prisoners. Sample selection and definitions of recidivism varied widely, and few countries were comparable.ConclusionsRecidivism data are currently not valid for international comparisons. Justice Departments should consider using the reporting guidelines developed in this paper to report their data.

This measure reports the percentage of offenders who are currently serving terms in Iowa correctional institutions who have a high school diploma or an equivalent. It includes offenders where the highest level of education completed includes: High School Diploma, HiSET/GED or Special Education Diploma.

This dataset lists inmates incarcerated at Cockatoo Island prison in Sydney (Australia) between 1847-1869. It offers insights into how the colonial criminal justice system operated after New South Wales’ transition from a penal colony to a ‘free’ colony when transportation ceased in 1840. It is a useful tool for genealogists tracing the lives of their criminal ancestors and for historians of crime and punishment researching nineteenth-century Australia. The dataset includes prisoners' names and aliases, their ship of arrival, place of origin, details of their colonial conviction(s) (trial place, court, offence, sentence), date(s) admitted to Cockatoo Island, and when and how they were discharged from Cockatoo Island. In some cases, it also includes prisoners' place of origin, occupation, biometric information (height, eye/hair colour, complexion, scars, tattoos), 'condition upon arrival' (convict or free), and (for convicts) details of their original conviction in Britain or Ireland. As a UNESCO World Heritage 'Convict Site' Cockatoo Island is best known as a site of secondary punishment for recidivist convicts, especially those transferred from Norfolk Island. This dataset demonstrates the diversity of the prison population: including nominally free convicts (ticket-of-leave holders), migrants from Britain, China and other Australian colonies drawn in by the gold rush, exiles from Port Phillip, Aboriginal Australians convicted during frontier warfare, colonial-born white Australians (including bushrangers), and black, Indian and American sailors visiting Sydney. Significant attention has been paid to the more than 160,000 British and Irish convicts who were transported Australia as colonists between 1787 and 1868. Much less has been said about those punished within the criminal justice system that arose in the wake of New South Wales' transition from 'penal' to 'free' colony (Finnane, 1997: x-xi). Cockatoo Island prison opened in 1839, a year before convict transportation to New South Wales ceased, and was intended to punish the most recidivist and violent of the transported convicts. This archetype has prevailed in historical discourses, and they have been described as 'criminal lunatics... [and] criminals incapable of reform' (Parker, 1977: 61); 'the most desperate and abandoned characters' (O'Carrigan, 1994: 64); and people of 'doubtful character' (NSW Government Architect's Office, 2009: 29). Yet, this was far from the truth. My analysis of 1666 prisoners arriving between 1839-52 show they were overwhelming non-violent offenders, tried for minor property crimes at lower courts. They were also far more diverse population than commonly recognised, including Indigenous Australian, Chinese and black convicts alongside majority British and Irish men (Harman, 2012). This project will make publicly available extremely detailed records relating to Cockatoo Island's prisoners to show people firsthand exactly who made up the inmate population. The digital version of the original registers will include information on convicts' criminal record, but also their job, whether they were married or had children, and even what they looked like. It will also be a name-searchable database so family historians can search for their ancestors, who may have been incarcerated on the island. As it stands, they will be able find information online about ancestors who were transported as long as they remained in the 'convict system', but they may seem to disappear as soon as they are awarded their ticket-of-leave and become 'free'. However, many former convicts, and free immigrants, to New South Wales were convicted locally, and these records can give us information about their lives within the colony. The type of data included in these registers will also allow researchers to investigate questions including: (1) were convicts more likely to offend again than free immigrants? (2) Were the children of convicts more likely to offend than others? (3) Did the influx of mostly Chinese migrants during the gold rush actually lead to a crime-wave, as reported in the press? (4) Were laws introduced between 1830 and 1853, actually effective at prosecuting bushrangers (highwaymen)? (5) Was the criminal-judicial system in Australia more rehabilitative, despite developing out of a harsher convict transportation system? Alongside the dataset, the website will include 'life-biographies' of individual convicts to show you how this dataset can be used to piece together a life-story. It also to warns against understanding a real-life person only through the records of their conviction. There many of fascinating stories to tell, including those 'John Perry' ('Black Perry') the prizewinning boxer; the love story of the 'Two Fredericks'; and Tan, the Chinese gold-digger who resisted his incarceration. In addition, there will be teaching resources for secondary school children and undergraduate university students who want to engage directly with historical materials, without having to leave their classroom. Overall, this website invites anyone with an interest in the history of crime and punishment, and any visitors to the UNESCO world heritage site 'Cockatoo Island', to try searching for a name in the database or read about a featured convict's life story. It asks them, though, to think about how and why these people's lives intersected with the state, leading to their incarceration, and how history has erased much of their lives outside of it. Data collection involved photographing a Cockatoo Island’s surviving prison registers and returns kept at the State Archives of New South Wales (call numbers: 4/4540, 4/6501, 4/6509, 6571, 4/6572, 4/6573, 4/6574, 4/6575, X819). In these volumes, clerks had listed details of incoming prisoners on the dates they arrived between April 1847 and October 1869. This prison register for the period 1839-46 (call number: 2/8285) had not survived to a good enough quality for accurate transcription and was excluded from data collection. I photographed and then transcribed these records in full into a tabular form, with minor standardisation of abbreviations and irregular spellings. Where multiple records existed for one person I combined information from two separate archival records into one line of the dataset. Where I could not verify that two people with the same name were the same person, I listed them as separate entries. Barring errors in entry at the time of record creation, the studied population represents the entire population of prisoners incarcerated at Cockatoo Island between April 1847 and October 1869 when the prison closed.

The 1922 Prison System Enquiry Committee Report said that: 'In order to judge our Prison system rightly it is necessary to know what kind of people become prisoners... How many go to prison? For what length of sentence?' These questions persist, and are especially relevant for today's prison crisis. This project will assess nearly 100 years of historical data to explore, for the first time, how prison numbers were largely dictated by the repeat incarceration of recidivist's offenders with short sentences. It questions how the prison authorities attempted to manage increasing numbers of offenders by using early release schemes (licenses) in the nineteenth and twentieth centuries (licenses have only recently become available, generous access granted by The National Archives). This project will explore whether short sentences contributed to repeat offending, and whether early release schemes accelerated or inhibited recidivism. It investigates the financial costs of imprisonment to the country (and the human costs to those imprisoned) and does this over a significant period of time (allowing an examination of how repeated incarcerations affected the whole of an offender's criminal career). It concludes by asking what lessons can be learnt for today's debates about sentencing offenders and managing the prison population? Data was derived from the following sources: PCOM 3 (1853-1887, 1902-08, 1912-42) – these files contained 45,000 licenses and also the registers of license holders. They listed the prisoner’s name, sentence, where/when convicted, dates and conditions of the current license; previous convictions, age, previous occupation, when and from where the prisoner was released; and most had photographs of the prisoner. The National Archives granted us access to these records pre public release (they are now available on Find-My-Past and Ancestry). Criminal Registers 1853-1892 (contained offenders tried for indictable crimes, whether they were found guilty, details of the offence, and sentence imposed). Where possible we traced these offences in the Quarter Sessions Calendars in order to trace the antecedent criminal history. From these main sources, we were then able to trace prisoners released on license using a wide variety of other extant sources. These sources provided us with a considerable amount of additional information on offenders who were released on license: Census returns from 1841-1911 censuses (which gave details of the residence, family status, and occupation, of each person we will be searching for). Online Birth, Marriage and Death indices (which detailed if and when our offender was married, and had children; and, of course, when they died). Military records (mainly referring to World War One; these included service records - which in turn included disciplinary breaches - medal indices and pensions details. Metropolitan Police records including Habitual Criminal Registers (MEPO 6) which contain details of criminals as defined by sections 5-8 of the Prevention of Crimes Act 1871. From the sources above we constructed approximately 650 life grids. These were divided into an early (1853-55 n=62), middle (1871-73 n=201), and late (1885-1887 n=184) tranche, for 356 men and 288 women. Each life-grid charted offending/life histories for each offender. Studies funded by Leverhulme Trust (F/00130/H)) and ESRC (RES-062-23-0416) used life grids and `whole-life’ research methods and the method is now well-tested. The life-grid data was then entered into excel and SPSS in order to produce quantifiable data on - the progress of their criminal careers, their periods of incarceration, their employment careers, life events such as marriage, death of parents, and other significant life events. We had over two hundred thousand fields of data at the conclusion of our data collection/analysis. By analysing each of the life grids we were able to see the relationships and connections between life events and offending post-imprisonment (both short and long periods of custody, whilst on licence, and after license had expired.

This dataset displays the inmate populations for all the Federal Prisons throughout the United States on 7.2.08. This weekly Population Report can be found on the Bureau of Prisons website at bop.gov. These facilities are positioned by their lat/lon and this dataset is updated on a weekly basis.

The United Nations International Crime Prevention and Criminal Justice Branch began the Surveys of Crime Trends and Operations of Criminal Justice Systems (formerly known as the World Crime Surveys) in 1978. The goal of the data collection effort was to conduct a more focused inquiry into the incidence of crime worldwide. To date, there have been five quinquennial surveys, covering the years 1970-1975, 1975-1980, 1980-1986, 1986-1990, and 1990-1994, respectively. Starting with the 1980 data, the waves overlap by one year to allow for reliability and validity checks of the data. For this data collection, the original United Nations data were restructured into a standard contemporary file structure, with each file consisting of all data for one year. Naming conventions were standardized, and each country and each variable was given a unique identifying number. Crime variables include counts of recorded crime for homicide, assault, rape, robbery, theft, burglary, fraud, embezzlement, drug trafficking, drug possession, bribery, and corruption. There are also counts of suspects, persons prosecuted, persons convicted, and prison admissions by crime, gender, and adult or juvenile status. Other variables include the population of the country and largest city, budgets and salaries for police, courts, and prisons, and types of sanctions, including imprisonment, corporal punishment, deprivation of liberty, control of freedom, warning, fine, and community sentence. The countries participating in the survey and the variables available vary by year.

ObjectiveWe aimed to systematically review recidivism rates in individuals given community sentences internationally. We sought to explore sources of variation between these rates and how reporting practices may limit their comparability across jurisdictions. Finally, we aimed to adapt previously published guidelines on recidivism reporting to include community sentenced populations.MethodsWe searched MEDLINE, PsycINFO, SAGE and Google Scholar for reports and studies of recidivism rates using non-specific and targeted searches for the 20 countries with the largest prison populations worldwide. We identified 28 studies with data from 19 countries. Of the 20 countries with the largest prison populations, only 2 reported recidivism rates for individuals given community sentences.ResultsThe most commonly reported recidivism information between countries was for 2-year reconviction, which ranged widely from 14% to 43% in men, and 9% to 35% in women. Explanations for recidivism rate variations between countries include when the follow-up period started and whether technical violations were taken into account.ConclusionRecidivism rates in individuals receiving community sentences are typically lower in comparison to those reported in released prisoners, although these two populations differ in terms of their baseline characteristics. Direct comparisons of the recidivism rates in community sentenced cohorts across jurisdictions are currently not possible, but simple changes to existing reporting practices can facilitate these. We propose recommendations to improve reporting practices.

Adult correctional services, custodial and community supervision, average counts of adults in provincial and territorial programs, five years of data.

The purpose of this study was to develop and validate a reliable and accurate method for measuring the effectiveness of offender classification systems to improve the management of correctional facilities. In the early 1980s, the state of Hawaii began classifying its prisoners with a newly developed Federal Bureau of Prisons classification instrument. This study was designed to develop a method to evaluate this form. Two prediction models were used. The first, initial classification, used the sum of four variables to arrive at a security score, which was taken to be predictive of violence. The second, reclassification, used the sum of seven different variables to obtain a custody total, which was then used as a major determinant of reclassification. Two groups of inmates were used: inmates who had committed infractions and inmates with no reported infractions. Research variables include (a) initial classification: offense (severity), expected length of incarceration (sentence), type of prior commitments, and history of violence, and (b) reclassification: percentage of time served, involvement with drugs/alcohol, mental/psychological stability, most serious disciplinary report, frequency of disciplinary reports, responsibility that the inmate demonstrated, and family/community ties. In addition, the collection supplies information on race and sex of inmates, sentence limitation, history of escapes or attempts, previous infractions, entry, reclassification, and termination dates (month and year), and custody level. There are demographic variables for sex and race. The unit of observation is the inmate.

Internationally, incarcerated offenders are known to have higher rates of problem gambling with studies finding that up to one third of prisoners may be medium or high risk problem gamblers. This project will identify the nature and extent of connections between gambling and crime careers, including sources of resilience and vulnerability, in order to address and prevent further re-offending. Two wings in six prisons in England and Scotland will be screened using a questionnaire that includes the Problem Gambling Severity Index, a resilience measure and questions relating to offending and co-morbidity. The full sample of 400 women, 200 young offenders and 600 men will be tracked on the Police National Computer collecting data on offending history and re-offending over 12 months. Statistical analysis will identify crimes most frequently associated with problem gambling offenders, recidivism, resilience and co-morbidity. A longitudinal cohort of 9 problem gamblers, 9 non-problem gamblers and 9 abstainers from each prison (N=162) will be interviewed pre and post release to collect in-depth data on personal histories, crime, gambling and points of potential intervention through career narratives. Findings will be disseminated to academic, policy and practice audiences including a work shop for criminal justice and related professionals.

NATIONAL JAIL CENSUS, 1988, is the fifth in a series of data collection efforts aimed at studying the nation's locally administered jails. For purposes of this data collection, a jail was defined as a confinement facility intended for holding adults (and in some cases juveniles) pending adjudication or having sentences of a year or less. Jails were further defined as being administered and staffed by municipal or county employees. Also included in this collection were six jails privately operated under contract for local governments. Excluded from the census were federal or state-administered facilities, including the combined jail-prison systems in Alaska, Connecticut, Delaware, Hawaii, Rhode Island, and Vermont. The mailing list used for the census was derived from data gathered from the AMERICAN CORRECTIONAL ASSOCIATION DIRECTORY OF JUSTICE AGENCIES, publications such as AMERICAN JAILS, telephone calls to large metropolitan jail systems (e.g., New York City), state jail inspection bureaus, and newspaper articles. Following the initial mailout to 3,448 facilities, 44 jails were added and 176 deleted according to the criteria for inclusion, leaving a total of 3,316 facilities in 44 states. Variables include information on jail population by legal status, age and sex of prisoners, maximum sentence, admissions and releases, available services, structure and capacity, expenditure, and employment.

Abstract: Mortality in prisons, a basic indicator of the right to health for incarcerated persons, has never been studied extensively in Brazil. An assessment of all-cause and cause-specific mortality in prison inmates was conducted in 2016-2017 in the state of Rio de Janeiro, based on data from the Mortality Information System and Prison Administration. Mortality rates were compared between prison population and general population after standardization. The leading causes of death in inmates were infectious diseases (30%), cardiovascular diseases (22%), and external causes (12%). Infectious causes featured HIV/AIDS (43%) and TB (52%, considering all deaths with mention of TB). Only 0.7% of inmates who died had access to extramural health services. All-cause mortality rate was higher among prison inmates than in the state’s general population. Among inmates, mortality from infectious diseases was 5 times higher, from TB 15 times higher, and from endocrine diseases (especially diabetes) and cardiovascular diseases 1.5 and 1.3 times higher, respectively, while deaths from external causes were less frequent in prison inmates. The study revealed important potentially avoidable excess deaths in prisons, reflecting lack of care and exclusion of this population from the Brazilian Unified National Health System. This further highlights the need for a precise and sustainable real-time monitoring system for deaths, in addition to restructuring of the prison staff through implementation of the Brazilian National Policy for Comprehensive Healthcare for Persons Deprived of Freedom in the Prison System in order for inmates to fully access their constitutional right to health with the same quality and timeliness as the general population.

The Washington legislature has established a comprehensive system of corrections for convicted law violators within the state of Washington to accomplish a primary objective of ensuring public safety. The system is designed and managed to provide the maximum feasible safety for the persons and property of the general public, the staff, and the inmates (RCW 72.09.010).

Adult correctional services, custodial and community supervision, average counts of offenders in federal programs, Canada and regions, five years of data.