Background: With data modernization, Local health departments (LHD) require data at the “speed of need” for stakeholders to target, evaluate and adjust interventions. The Health Atlases aggregate disparate data and provide LHDs tools to analyze and visualize data for faster response.

Objectives: We demonstrate how a public-private partnership between LHD, academia and a technology firm democratized the dissemination, analysis and visualization of hyperlocal data to drive community engagement and rapid policy change.

Methods: Much publicly available geospatial data is only provided for one geographic layer (e.g. ZIP code). Our process uses a weighted-average approach to faithfully convert data at one geographic layer to another, allowing seamless data exploration and comparison between small and large geographies. We aggregate data from the layer with smaller geographies, overlaid by population or land overlap with the other layer, and weighted by both that overlap and the population distribution within the two layers. Furthermore, the Health Atlas algorithms calculate appropriate margin-of-error statistics from the originals, with an additional buffer to account for the uncertainty introduced by this algorithm. Data is then presented to users in a variety of customized places such as hospital service areas and geopolitical districts.

Results: Numerous use cases have emerged including, vaccine outreach strategies, program evaluation, curriculum design and community action toward health equity. The timeliness of data updates has increased 103% since 2021 and usage grew by 228% between 2021 and 2022.

Conclusion: Partnerships between government, academia and technology can create efficient solutions to increase data access and literacy.

Background: Since the onset of the COVID-19 pandemic, multiple public health interventions have been implemented to respond to the rapidly evolving disease and community needs. Hyperlocal data have played an important role in targeting interventions to improve the COVID-19 vaccine update and racial health equity.

Objectives: We demonstrate several ways that the Chicago and Cook County Health Atlases were utilized to inform policy initiatives and monitor differential levels of COVID-19 vaccine uptake in different Chicago communities.

Methods: We examined the COVID-19 vaccine uptake rates between January and December of 2021 and created the COVID-19 vaccine outreach timeline from interviews with the Chicago Department of Public Health (CDPH) and community-based organizations (CBOs). We then compared the outreach efforts with the vaccine uptake data. We established the overall timeline for the official city’s outreach programs. We then asked CBO leaders to describe community experiences with the official city outreach programs.

Results: Various outreach initiatives were implemented to increase vaccine uptake. CDPH had a separate data ambassador program to support CBO leaders to maximize local data for planning and evaluation. By the end of 2021, the uptake rate reached 61%. We saw a substantial increase in vaccination rates across the south and west sides of the city. The Hispanic and white disparity in vaccination was virtually eliminated, however black and white disparity while reduced remained.

Conclusion: Hyperlocal data-informed the city’s COVID-19 vaccine outreach efforts. The data ambassador program to engage community partnership continues to contribute to building community.

Background: With a population of approximately 2.5 million across 120 municipalities, Suburban Cook County (SCC) presents a challenge in addressing and reducing the prevalence and incidence of chronic disease. Innovative approaches are necessary due to the diverse demographic and jurisdictional divide within SCC. The Cook County Health Atlas and the Change Institute seek to advance health equity by addressing disparities in SCC communities that are disproportionately impacted by chronic disease, as well as monitoring disease status and the social determinants of health.

Methods: Epidemiologic methods were used to identify the most common chronic diseases that are disproportionately affecting minority and low-income communities across SCC. Public Health data was gathered, cleaned, coded, analyzed, and transformed into counts and rates. A dissemination plan was developed to support data accessibility, community engagement, and public health best practices.

Results: The Cook County Health Atlas was leveraged to disseminate data related to the Chronic Disease. A customized page for each measure was created on the Atlas that featured health indicators and a summary of disease by cancer, diabetes, heart disease, and stroke. Data briefs provide trend data, demographic stratifications for SCC, and summaries of the local burden.

Conclusions: The Change Institute Chronic Disease measures support the monitoring of disease trends and evaluation of implemented programs. It allows public health agencies to communicate the data through a health equity lens. The SCC atlas serves as a platform for addressing chronic disease disparities in SCC and may serve as a model for other diverse jurisdictions facing similar challenges.