Abstract 2160: Utilizing geospatial analytics to identify neighborhood cancer hot spots for recruitment of underserved populations in clinical prevention research

Abstract Background: The term “precision public health” has increasingly been used in literature to describe public health practices that utilize new technologies and big data to precisely target the most vulnerable populations for disease control. Following the principles of precision public health, we used geospatial technologies and population-based health data to identify the locations and socioeconomic status of neighborhoods with high cancer incidences for recruitment of participants in prevention research. Methods: Using Florida cancer registry data, geospatial hot spot analyses were carried out to identify statistically significant clusters of census tracts with high incidences of prostate, gastric, and oral cancers within the catchment area of the Sylvester Comprehensive Cancer Center in South Florida. The locations, social determinants of health (US Census’ American Community Survey), and behavioral risk factor data (CDC’s Behavioral Risk Factor Surveillance System) of these hot spots were analyzed to identify the locations of underserved communities facing high risk for these three cancers. Results: Hot spots with high incidences for each of these three cancers overlap in many neighborhoods with high proportions of Hispanic and Non-Hispanic Black populations and high levels of socioeconomic disparities, such as low income, low education level, rental housing, no vehicles, and no access to health insurance. These neighborhoods also have high rates for behavioral risk factors in smoking, lack of physical activity, obesity, and high incidence of cervical cancer (high risk areas for HPV-associated oral cancers). Mobile screening units called the Game Changer Vehicles have been deployed to the locations to recruit participants who were tested on-site for prostate specific antigen (prostate cancer), H. pylori (gastric cancer), or solCD44 (a soluble tumor marker for squamous cell carcinoma) and total protein levels in oral rinse specimens, which can distinguish individuals with molecular features at risk for oral cancers due to tobacco, alcohol use, and human HPV infection. Conclusions: Geospatial analyses of population health data can be used to produce metrics that precisely target neighborhoods with high cancer risk and health disparities to recruit research participants. The same precision approach can also be applied for cancer screening purposes, such as offering cervical self-sample and fecal blood test kits in disadvantaged communities facing heightened risk for cervical and colorectal cancers. Citation Format: Ming S. Lee, Rebecca Kaiser, Ridhi Vyas, Amando Vera, Daniela Flores Quetant, Nancy Elliott, Valerie Bethel, Amanda Rivera, Shria Kumar, Brandon Mahal, Elizabeth Franzmann, Erin Kobetz. Utilizing geospatial analytics to identify neighborhood cancer hot spots for recruitment of underserved populations in clinical prevention research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2160.