# Risk identification strategies for health pandemics and epidemics on college campuses: A comprehensive analysis of heat maps and behavioral observations

## TL;DR

This paper explores how combining heat maps from surveys with direct observation can identify risky mask-wearing behaviors on college campuses during health crises.

## Contribution

The study introduces a novel method combining survey-based heat maps and direct observation to pinpoint high-risk areas for pandemic behaviors on campuses.

## Key findings

- Mask-wearing was less likely in group settings compared to when individuals were alone.
- Survey heat maps accurately identified locations with high and low mask-wearing behaviors, confirmed by direct observation.
- Combining heat maps and direct observation provides actionable insights for pandemic risk management on campuses.

## Abstract

The purpose of the current studies was to use direct observation and surveys to assess behavioral risk on a college campus during the COVID-19 pandemic.

Study 1 used direct observation to monitor safe and at-risk mask-wearing behavior across multiple campus locations and whether mask-wearing differed when individuals were alone or in groups. Study 2 surveyed college students through a click-based campus map survey to identify high- and low-mask-wearing locations on campus and create data heat maps indicating at-risk behaviors. Direct observation analyses were then used to verify the identified locations.

Study 1 revealed that mask-wearing was likely during a mask-wearing policy implemented across the college campus. However, mask-wearing was less likely when people were in groups than alone. Study 2 showed that survey responses and the heat map analysis identified spatially distinct locations of perceived high and low mask-wearing. These data were validated through direct observation, verifying high and low mask-wearing at the identified locations.

Survey heat maps paired with direct observation can help identify specific locations where safe and at-risk behaviors are most likely to occur. By identifying special patterns of risk, this comprehensive approach offers actionable information to guide interventions, policy enforcement, and resource allocation during health epidemics.