Dataset Information

Lessons Learned from COVID-19 Response in Correctional and Detention Facilities.

ABSTRACT: The COVID-19 pandemic disproportionately affected persons held in and working in correctional and detention facilities, causing facilities' traditional priorities to shift when healthcare and public health needs temporarily drove many aspects of operations. During July-August 2022, we interviewed members of health departments and criminal justice organizations to document lessons learned from the COVID-19 response in correctional settings. Participants valued enhanced partnerships, flexibility, and innovation, as well as real-time data and corrections-specific public health guidance. Challenges included cross-sector collaborations, population density, scarcity of equipment and supplies, and mental health. Most participants reported improved relationships between criminal justice and public health organizations during the pandemic. Lessons from COVID-19 can be applied to everyday public health preparedness and emergency response in correctional facilities by ensuring representation of correctional health in public health strategy and practice and providing timely, data-driven, and partner-informed guidance tailored to correctional environments when public health needs arise.

SUBMITTER: Waddell C

PROVIDER: S-EPMC10986833 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Lessons Learned from COVID-19 Response in Correctional and Detention Facilities.

Waddell Caroline C Meehan Ashley A Schoonveld Megan M Kaplan Zoe Z Bien Michael M Bailey Claire C Mosites Emily E Hagan Liesl M LM

Emerging infectious diseases 20240401 13

The COVID-19 pandemic disproportionately affected persons held in and working in correctional and detention facilities, causing facilities' traditional priorities to shift when healthcare and public health needs temporarily drove many aspects of operations. During July-August 2022, we interviewed members of health departments and criminal justice organizations to document lessons learned from the COVID-19 response in correctional settings. Participants valued enhanced partnerships, flexibility, ...[more]

PMID: 38561631

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Project description:Introduction. The risk of infectious disease transmission, including COVID-19, is disproportionately high in correctional facilities due to close living conditions, relatively low levels of vaccination, and reduced access to testing and treatment. While much progress has been made on describing and mitigating COVID-19 and other infectious disease risk in jails and prisons, there are open questions about which data can best predict future outbreaks. Methods. We used facility data and demographic and health data collected from 24 prison facilities in the Pennsylvania Department of Corrections from March 2020 to May 2021 to determine which sources of data best predict a coming COVID-19 outbreak in a prison facility. We used machine learning methods to cluster the prisons into groups based on similar facility-level characteristics, including size, rurality, and demographics of incarcerated people. We developed logistic regression classification models to predict for each cluster, before and after vaccine availability, whether there would be no cases, an outbreak defined as 2 or more cases, or a large outbreak, defined as 10 or more cases in the next 1, 2, and 3 d. We compared these predictions to data on outbreaks that occurred. Results. Facilities were divided into 8 clusters of sizes varying from 1 to 7 facilities per cluster. We trained 60 logistic regressions; 20 had test sets with between 35% and 65% of days with outbreaks detected. Of these, 8 logistic regressions correctly predicted the occurrence of an outbreak more than 55% of the time. The most common predictive feature was incident cases among the incarcerated population from 2 to 32 d prior. Other predictive features included the number of tests administered from 1 to 33 d prior, total population, test positivity rate, and county deaths, hospitalizations, and incident cases. Cumulative cases, vaccination rates, and race, ethnicity, or age statistics for incarcerated populations were generally not predictive. Conclusions. County-level measures of COVID-19, facility population, and test positivity rate appear as potential promising predictors of COVID-19 outbreaks in correctional facilities, suggesting that correctional facilities should monitor community transmission in addition to facility transmission to inform future outbreak response decisions. These efforts should not be limited to COVID-19 but should include any large-scale infectious disease outbreak that may involve institution-community transmission.HighlightsThe risk of infectious disease transmission, including COVID-19, is disproportionately high in correctional facilities.We used machine learning methods with data collected from 24 prison facilities in the Pennsylvania Department of Corrections to determine which sources of data best predict a coming COVID-19 outbreak in a prison facility.Key predictors included county-level measures of COVID-19, facility population, and the test positivity rate in a facility.Fortifying correctional facilities with the ability to monitor local community rates of infection (e.g., though improved interagency collaboration and data sharing) along with continued testing of incarcerated people and staff can help correctional facilities better predict-and respond to-future infectious disease outbreaks.

Project description:Vulnerable communities are susceptible to and disproportionately affected by the impacts of the COVID-19 pandemic. Understanding the challenges faced, perceptions, lessons learned, and recommendations of the organizations that provide services in response to COVID-19 to vulnerable communities is critical to improving emergency response and preparedness in these communities. This study employed GIS mapping to identify the needs and assets that exist in communities in Baltimore City, where vulnerabilities related to social determinants of health and the burden of the COVID-19 pandemic were greatest. We also conducted an online survey between September 1, 2021, and May 30, 2022, to assess the COVID-19-related services provided by local organizations, challenges faced, perceptions, lessons learned, and recommendations to inform policies, programs, and funding related to improving the COVID-19 response in underserved communities. The survey was disseminated through the online Kobo Toolbox platform to leaders and representatives of organizations in Baltimore City. Based on GIS mapping analysis, we identified three communities as the most vulnerable and 522 organizations involved in the COVID-19 response across Baltimore City. 247 surveys were disseminated, and 50 survey responses were received (20.24% response rate). Out of these organizations, nearly 80% provided services in response to COVID-19 to the identified vulnerable communities. Challenges experienced ranged from funding (29%), and outreach/recruitment (26%), to not having access to updated and accurate information from local officials (32%). This research highlights critical insights gained related to the experiences of vulnerable populations and suggests ways forward to address challenges faced during the emergency response by providing recommendations for policy and program changes. Furthermore, the findings will help better prepare vulnerable communities for public health emergencies and build more community resilience.

Dataset Information

Lessons Learned from COVID-19 Response in Correctional and Detention Facilities.

Publications

Lessons Learned from COVID-19 Response in Correctional and Detention Facilities.

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