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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.
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Summary Report/Recommendations
To begin bridging the gap in knowledge about COVID-19 risk among sexual minority adults, the Centers for Disease Control and Prevention examined disparities between sexual minority and heterosexual adults in the prevalence of underlying conditions with strong or mixed evidence of associations with severe COVID-19-related illness, by using data from the 2017–2019 Behavioral Risk Factor Surveillance System (BRFSS). Collecting data on sexual orientation in COVID-19 surveillance and other studies would improve knowledge about disparities in infection and adverse outcomes by sexual orientation, thereby informing more equitable responses to the pandemic.
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.
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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.