Identifying predictors for counties that have exceptionally low STI case rates in the US (2019): a positive deviant...

The US is experiencing an unprecedented sexually transmitted infections (STIs) epidemic. Although recent provisional data show some stabilization or minor declines in case rates for chlamydia, gonorrhea and syphilis, overall rates remain significantly higher than a decade ago. Local health departments (LHDs) play a crucial role in preventing and treating STIs, but some LHDs are demonstrably more effective than others. This study utilized a positive deviance (PD) approach to identify and analyze US counties with unexpectedly low STI rates.

We used a cross-sectional study design, analyzing data from 981 counties across the US, using a two-step approach: (1) multivariate linear regression to identify PD counties, and (2) multivariate logistic regression to examine predictors of PD status.

We identified 187 (19.06%) high-performing counties, considering internal and external factors, and investigated predictors that affect the identification of these high-performing counties. These counties were more likely to have the smallest population category (<25,000), which had 6.47 times odds of being identified as PD counties compared with counties of ≥1 million, counties with high social vulnerability in specific subcategories (racial and ethnic subgroup, housing, and transportation), and counties with LHDs that provided STI-related treatment services directly and through community partnerships.

Our findings demonstrate the potential of using a PD approach for identifying and learning from high-performing LHDs. The identification of high-performing counties provides a foundation for future research to explore the nuanced interventions contributing to their success, ultimately informing targeted public health strategies and resource allocation.