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This review of state data collection and reporting practices during the COVID-19 pandemic found inconsistencies and gaps in data collected by race and ethnicity. Improved standardization across the U.S.–which may come in the form of a federally-operated centralized database–would address some of the concerns in data representation of all Americans.

This study assesses the usefulness in death data from a medical examiner’s office in strategic planning during a pandemic. There was found to be a statistically significant correlation between daily reported death numbers from a medical examiner’s office and hospital admissions. As such, death data from a medical examiner’s office can be assumed to be a reliable source and used when developing strategic plans.

This study analyzes different epidemic models of COVID-19. It demonstrates the variability of models’ ability to predict COVID-19 transmission and outbreak. It advises public health practitioners to exercise caution when formulating public health strategies based on the prediction results of mathematical models due to this variability.

The Johns Hopkins University COVID-19 dashboard, which was launched one day after the first confirmed US COVID-19 case, provides an accessible means of viewing COVID-19 cases, deaths, recoveries, and vaccination rates globally. This report covers the data collection process and challenges faced while doing so, especially those related to pulling data from various sources. It offers ways for public health agencies to adapt their approaches for reporting data.

This analysis identifies risk factors and socio-economic impacts of long COVID with a public health lens. It notes that more analysis is needed, but encourages the impacts of long COVID to be seen within a larger social, and not just medical, context. Workplace and family structure implications are substantial. Long COVID should be tracked as distinct condition using person-centered research techniques that include traditionally underrepresented populations such as children.

This article discusses the development of the Visible app, which uses wearables or smart watches to help measure and manage long COVID. Visible helps to manage long COVID and other chronic fatigue diseases with a heartrate-monitored guidance strategy that emphasizes pacing as long COVID patients return to physical activity.

This study compares data from the NYC coronavirus data repository with 2018 American Community Survey 5-year census estimates to examine the distribution of testing sites across New York City by race in May 2020. During this time, the results found that testing sites for primarily Black and Latinx communities increased, but primarily White areas still had the highest number of testing sites. The study team created ZIP-code level maps showing testing site distribution using ArcGIS as a part of this study.

This article conducts a retrospective case-control study of electronic health records of individuals who were diagnosed with COVID-19 and have a recent diagnosis of substance use disorder (SUD). The results show that those diagnosed with SUD, particularly African Americans and those with opioid use disorder (OUD), are more likely to contract COVID-19, as well as suffer worsening outcomes such as hospitalization and mortality due to COVID-19. This article shows that an increase in SUD screening could be a factor in mitigating the spread of COVID-19 in this community.

This study focuses on the health inequalities experienced by older adults during the COVID-19 pandemic. The study identifies six types of inequality amplifiers experienced by this population: 1) expansion of riskscape, 2) reduction of social ties, 3) uncertainty of future, 4) losing trust in institutions, 5) coping with new knowledge, and 6) straining on public spending.

This article seeks to assess COVID-19 case and mortality rates in non-Hispanic American Indian and Alaska Natives (AI/AN) through an analysis of laboratory-reported COVID-19 data from January 22-July 3, 2020, for 23 U.S. states. The results show that AI/AN individuals are 3.5 times more likely to contract COVID-19 than White individuals, and more accurate race/ethnicity data must be reported by all states to more accurately represent this population.