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Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
RELEASE DATE:
Peer Review Study
Challenges related to workforce capacity have existed throughout the COVID-19 pandemic. These shortages are especially acute and problematic for settings with high disease burdens such as nursing facilities. Strategies for expanding public health capacity within nursing homes and more broadly include increased training and retention of experienced staff.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
RELEASE DATE:
Evaluation Report, Peer Review Study
The article evaluates the connection between health care workers’ unions and Covid-19 mortality rates in nursing homes. Using regression analysis, the presence of a union were associated with lower Covid-19 mortality rates (30% lower) and infection rates (42% lower) among nursing home residents. Nursing homes with unions saw increased access to N95 respirators and eye shields as well. These results ultimately show that health care worker unionization may better ensure access to appropriate PPE and infection control policies that will protect nursing home residents.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
RELEASE DATE:
Peer Review Study
This study develops a microsimulation model of COVID-19 transmission in a homeless shelter and calibrated it to data from surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2022. The study estimates the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies. The results show that within communities with high COVID-19 community incidence are unable to prevent a large outbreak, despite extensive infection control strategies. This study suggests a need for non-congregate housing in high-risk settings, is needed to avoid outbreaks within these settings.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
RELEASE DATE:
Peer Review Study
This study looks at a COVID-19 outbreak among a multi-residential home for adults with intellectual and developmental disabilities in Arizona to determine how COVID-19 was spread. Epidemiologic and genomic evidence show that spread likely occurred from asymptomatically infected staff. This study demonstrates the need for public health measures and rapid genomic analysis to shape policies that protect these vulnerable populations.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
RELEASE DATE:
Peer Review Study
This article discusses the use of wastewater surveillance to indicate new levels of COVID-19 or other infection in congregate housing settings. The study sampled wastewater from a hospital and a wastewater treatment plant to detect levels of COVID-19 in the individuals residing in the hospital. The results were able to indicate levels of COVID-19 in the wastewater, but were unable to distinguish between new infection levels and residual viral shed from previously infected patients. This study shows the potential of wastewater management, and calls for the increased refinement of the process to more accurately monitor viral spread in vulnerable living situations.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
RELEASE DATE:
Peer Review Study
This article conducted a cross-sectional study of 351 Massachusetts cities and towns from January 1-May 6, 2020, to understand what demographic, economic, and occupational factors are affecting COVID-19 incidence rates. Results found that non-Latino Black and Latino populations are at most risk of contracting COVID-19. Addressing factors like healthcare access for foreign-born non-citizens, crowded housing, and the protection of food service workers may help mitigate spread among minority populations.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
RELEASE DATE:
Peer Review Study
The Cuyahoga County Board of Health partnered with congregate living facilities to try to prevent and mitigate Covid outbreaks. The Board partnered with community partners, facility staff, state health officials, and other health care professionals and organized structured team meetings to identify and respond to cases in congregate living facilities. This partnership worked together to plan testing, contract tracing, and isolation/quarantine protocols. The department also hired a resource manager who coordinated all response efforts. For high need congregate living facilities, the resource manager/partners assisted with PPE needs.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
RELEASE DATE:
Peer Review Study
This case study is on the effectiveness of COVID-19 vaccine distribution via mobile vans to residents/staff of 47,907 long-term care facilities (LTCFs) across the United States that relied on algorithms to optimize vaccine distribution. The authors developed a modeling framework for vaccine distribution to high-risk populations in a supply-constrained environment. The framework decomposed this challenge as two separate problems: an assignment problem, where they optimally mapped each LTCF to select CVS stores responsible for vaccines; and a scheduling problem, where they developed an algorithm to assign available resources efficiently. The learning and this framework may be of use to other organizations, including communities where mobile clinics can be established to efficiently distribute vaccines and other healthcare resources in a variety of scenarios.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
RELEASE DATE:
Peer Review Study
This article describes the approach and impact of the Stanford Flu Crew, a service learning program at Stanford University School of Medicine, where pre-clinical students provide vaccines to underserved populations in community settings. The article includes information on both program outcomes (i.e., the number of people vaccinated per year over a 4-year period) and student perceptions of learning outcomes achieved through this program.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
RELEASE DATE:
Peer Review Study
This is a retrospective cohort study that was used to inform COVID-19 infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach. The strongest predictors of COVID-19 infection were identified as the county’s infection rate and the number of separate units in the NH; other predictors included the county’s population density, historical health deficiencies, and resident density. In addition, the NH’s historical percentage of non-Hispanic white residents was identified as a protective factor. The study concluded that a machine-learning model can help quantify and predict infection risk.