; (2) review current standards for reporting, quality controls, and transparency of the data; (3) examine data gaps and barriers to timely and accurate reporting and identify ways to fill those gaps; (4) examine how systems can be accessed and used by a wide range of users, including external researchers; (5) examine how different data systems interact and how different data sources can be integrated; (6) examine nontraditional data sources or alternative data gathering methods that could be used to complement traditionally collected data; (7) identify needed improvements to the public health data systems and structure, especially with regard to the needs of Tribal systems; (8) identify core elements of a minimum data set that might be used for State population surveillance, including demographic components that are necessary to ensure health equity in public health decision making; (9) examine how surveillance systems can be explicitly designed to ensure vulnerable populations (which may include racial and ethnic minorities, immigrants, individuals in nursing homes, other institutionalized populations, and individuals experiencing homelessness) are included in reporting; (10) consider how traditional and nontraditional data might be used to promote health equity across the United States and reduce racial, Tribal, and other demographic disparities; (11) examine data gaps and barriers to collecting, analyzing, and using demographic data to characterize the COVID–19 pandemic for public health action and research to improve public health actions and identify ways to fill those gaps