To visualize entities that could potentially address the unmet needs of at-risk and disadvantaged community members, a series of activities and exercises geared to participants with little programming or GIS experience were developed using geographic and population information. The learning activities and exercises progress from navigating an existing map to creating a map and uploading to harnessing freely available resources like US Census Bureau data to produce visualizations that link geographic and demographic information. Participants will apply these tools and resources to a specific public health question in a specific region and produce a data-driven report on the answers.By the end of this lesson, students will have combined geographic and demographic data related to public health resources. By processing and uploading data to the map, you have created a custom display where geographic information can be related to other data elements (e.g., population, etc.). This basic workflow is analogous to that used by GIS professionals using sophisticated tools. However, in this activity, we were able to approximate this capability using freely available and relatively user-friendly resources.

Public health concerns are often multi-faceted, complex problems. Any exploratory analysis conducted to support public health concerns should be scalable to this multi-attribute nature. This activity pairs with a chapter focused on spatial clustering techniques for multivariate analysis, which can reveal the locations with unusually high or low occurrences of multiple diseases. We will use obesity and insufficient sleep, which often occur together, as conditions to analyze considering their serious impacts on public health. Once contributing factors are determined, policymakers can be informed so that they can begin to address the negative impacts.In the activity, students will use SaTScan to find spatiotemporal hotspots and coldspots in obesity and insufficient sleep data representing American children. After a brief Q&A session, students will follow the walkthrough to complete the spatial clustering with SaTScan (Version 9.4). (SaTScan is a free software designed to detect clusters of spatial, temporal, or spatiotemporal data using scan statistics. This allows for complex relationships within the data to be revealed and explored. You can download SaTScan at https://www.satscan.org/.) The lecture can be closed with a discussion session where students will evaluate the statistically significant hotspots where they are found.LEARNING OUTCOMESBy the end of this lesson, students will be able to• analyze multivariate spatiotemporal data on obesity and insufficient sleep among children by using SaTScan;• interpret and evaluate hotspots and coldspots regions; and• create spatial cluster maps by handling spatial data files.This activity is part of Spatial Literacy in Public Health: Faculty-Librarian Teaching Collaborations (ACRL, 2024).

The lesson covers using PolicyMap and Social Explorer to visualize socioeconomic variables. These two mapping tools let learners view geographic distribution of variables (back ideas with data) and begin their exploration of spatial literacy. In addition, the visualizations can lead learners to question assumptions and examine the impact of social determinants of health among other issues. The lesson walks learners through using these tools to examine issues and combine a narrative and visualizations to write a policy report.