Abstract
Introduction Urgent action is required to combat sexually transmitted diseases (STDs), such as syphilis. This study aimed to examine whether the combination of hierarchical hexagonal grids (H3) (Uber Technologies, Inc., San Francisco, CA, USA) and Quantum Geographic Information System (QGIS) (OSGeo, Grut, Switzerland) can capture localized clustering and short-term fluctuations of estimated STD-related risk behaviors with high spatial resolution while preserving anonymity, and to evaluate its potential utility as a public infectious disease surveillance method. Methods A field survey was conducted in District A, an urban area in Japan (80 m × 60 m), between July 16 and 27, 2024, from 6:30 to 8:00 p.m. Estimated female commercial sex workers (CSWs) and involved males were recorded using a GPS application, collecting only date, time, latitude-longitude, and gender. The data were processed in QGIS and aggregated at H3 resolutions 13 (43.9 m²) and 14 (6.3 m²). We also assessed fluctuations in the data during an incidental police intervention that occurred during the observation period. Maps displayed anonymized building footprints, and no contact with individuals or collection of personal information occurred. Results At H3 resolution 14, clusters of up to four observations were detected in cells near the central intersection, while resolution 13 allowed recognition of broader spatial patterns. Over the 10-day observation period, a total of 96 observations were recorded. Spatial clustering varied by time period and gender. An external factor (police intervention) resulted in a temporary reduction of approximately 70% in observations, followed by a rapid recovery, which was visualized on the grid. Conclusions High-resolution hexagonal grid analysis using H3 and QGIS provides a practical method to monitor the spatial dynamics of STD-related risk behaviors without handling personal information. Its independence from administrative boundaries enhances generalizability, enabling flexible application in response to infection trends and supporting evidence-based public health nursing activities in infectious disease surveillance.