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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 is a qualitative study that looked at 25 women who were recently released from jail to ascertain reasons behind vaccine hesitancy and COVID-19 mitigation strategies for this sub-population. Results show that most participants had a great deal of vaccination mistrust and low health literacy rates, despite the fact that most of the participants were more susceptible to contracting COVID-19. The article discusses the importance of interventions to target these populations.
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.
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 examines the impact that COVID-19 has on incarcerated populations by analyzing systematic data on testing, test positivity, cases, and case fatality. Using data from the COVID Prison Project, the study presents data from 53 prison systems and compares these data with each state’s general population. Many states were not reporting full information on COVID-19 testing with some also not reporting on case fatality. Among those reporting data, there was wide variation between testing, test positivity, and case rates within prison systems and as compared to the general population. However, when more tests were deployed, more cases were identified, with the majority of state prisons having higher case rates than their general population.
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.