Presentations

Abstract

Introduction: Individuals experiencing housing instability are a population with inherently transient needs and resources and are particularly vulnerable to climate events such as extreme temperatures and precipitation. Prior studies have examined the relationship between weather and clinic attendance, but few focus specifically on the housing insecure. This study evaluated the effect of weather events on attendance to a once-weekly, student-run, walk-in free clinic in the urban population of Norfolk, Virginia.

Methods: Clinic attendance and weather data were retrospectively reviewed for clinic dates in 2021-2022. Descriptive statistics and ANOVA were performed using SAS v9.4 to analyze attendance against temperature and precipitation, as well as monthly and seasonal trends.

Results: In this 2 year period there were a total of 101 clinic dates and 775 patient visits. The warmer months of August and September were found to have statistically significantly higher attendance rates when compared to June (p<0.05), February (p<0.05), and March (p<0.05). There was also a positive correlation between clinic attendance and the average temperature on the day before, night before, and day of clinic (r=0.2, p<0.05). No significant differences were found when comparing all four seasons, though significant differences were seen when comparing Summer and Spring attendance (mean difference=2.93, p=0.032). No significant findings were found when examining the effect of precipitation on the day before, night before, or the day of clinics.

Conclusion: Although limited by small clinic size and a relatively short period of analysis, this data helps us understand which climate factors most significantly impact individuals experiencing housing insecurity, which then allows us to allocate clinic resources more appropriately and address these climate barriers in the future.