Utilizing geospatial analytics of cancer catchment area data for targeted recruitment of underserved populations for cancer prevention research: a precision public health application

Background: This paper introduces an innovative application of precision public health by the Sylvester Comprehensive Cancer Center (SCCC), utilizing catchment area data and geospatial analytics to identify cancer hot spots with underserved populations to recruit participants into research projects on prostate cancer, H. pylori infection, and oral cancers via community outreach and engagement.Methods: Using data from SCAN360 (i.e. a web-based data repository operated by SCCC), we carried out geospatial hot spot analyses to identify statistically significant clusters of census tracts with high incidences of prostate, gastric cancer associated with H. pylori infection, and oral cancer. The hot spots were overlaid on census tracts categorized with Social Determinants of Health (SDOH) to identify recruitment targets.Results: Hot spots for prostate and gastric cancers generally overlap and cluster in communities of significant SDOH disparities and behavioral risk prevalence, especially for gastric cancer. Hot spot clusters of prostate and gastric cancer also overlap in the persistent poverty area in the catchment area.Conclusions: Geospatial analytics of catchment area 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.

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Publication Details

Journal
Preventive Oncology & Epidemiology
Published
2024-12-06
DOI
https://doi.org/10.1080/28322134.2024.2406807
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
0.00
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article

Utilizing geospatial analytics of cancer catchment area data for targeted recruitment of underserved populations for cancer prevention research: a precision public health application

Lauren Nahodyl, Armando Vera, Amanda Rivera, Elizabeth Franzmann et al.
Preventive Oncology & Epidemiology
Data-Driven Disease Surveillance
article

Utilizing geospatial analytics of cancer catchment area data for targeted recruitment of underserved populations for cancer prevention research: a precision public health application

Lauren Nahodyl, Armando Vera, Amanda Rivera, Elizabeth Franzmann, Till Krenz, Shria Kumar, Nancy S. Elliott, Ming S. Lee, Erin N. Kobetz, Valerie D. Bethel, Daniela Flores Quetant, Brandon A. Mahal
article en

Abstract

Background: This paper introduces an innovative application of precision public health by the Sylvester Comprehensive Cancer Center (SCCC), utilizing catchment area data and geospatial analytics to identify cancer hot spots with underserved populations to recruit participants into research projects on prostate cancer, H. pylori infection, and oral cancers via community outreach and engagement.Methods: Using data from SCAN360 (i.e. a web-based data repository operated by SCCC), we carried out geospatial hot spot analyses to identify statistically significant clusters of census tracts with high incidences of prostate, gastric cancer associated with H. pylori infection, and oral cancer. The hot spots were overlaid on census tracts categorized with Social Determinants of Health (SDOH) to identify recruitment targets.Results: Hot spots for prostate and gastric cancers generally overlap and cluster in communities of significant SDOH disparities and behavioral risk prevalence, especially for gastric cancer. Hot spot clusters of prostate and gastric cancer also overlap in the persistent poverty area in the catchment area.Conclusions: Geospatial analytics of catchment area 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.

Preventive Oncology & EpidemiologyVol. 3(1)
University of Miami (US), Sylvester Comprehensive Cancer Center (US)
Openalex Percentile: Top 67%
Data-Driven Disease Surveillance
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