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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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White Paper/Brief
This article details the adaptation of the 2020 Community Health Survey by the New York City Department of Health and Mental Hygiene in order to capture the impact of COVID-19 on physical health, mental health, and social determinants of health. It explains how the survey questions were adapted, how collection of survey data was adapted, and how a serosurvey was implemented. Two new polls were added, Healthy NYC and 7 Health Opinion Poll, to learn about COVID-19 related opinions, attitudes, and knowledge.
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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White Paper/Brief
This paper serves as a foundational look into how structural racism and social determinants of health impact communities of color — particularly Black and Latino communities — in Massachusetts. This document uses local Massachusetts and national data sources to examine multiple factors for health inequities among racial minorities within the state. The primer covers demographic profiles, social drivers of health, access to coverage and care, service utilization, health outcomes, and the disparate impact of COVID-19 with infographics across multiple areas of health.
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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Systematic Review/Meta-Analysis
This article explores how health data technology tools such as Artificial Intelligence (AI) and Machine Learning (ML) tools can be implemented and adapted to assist in better responses and outcomes to the COVID-19 pandemic, as well as future epidemics. This literature review focuses on peer-reviewed articles concerning four themes: COVID-19 and the need for AI; utility of AI in COVID-19 screening, contract tracing, and diagnosis; use of AI in COVID-19 patient monitoring and drug development; AI beyond COVID-19 and opportunities for Low-Middle Income Communities (LMIC). This review contains examples of ways healthcare systems have implemented AI and ML to predict and treat outcomes of COVID-19, as well as potential capacities for AI.