Bringing Micro to the Macro: How Citizen Science Data Enrich Geospatial Visualizations to Advance Health Equity.

Social and spatial contexts affect health, and understanding nuances of context is key to informing successful interventions for health equity. Layering mixed methods and mixed scale data sources to visualize patterns of health outcomes facilitates analysis of both broad trends and person-level experiences across time and space. We used micro-scale citizen scientist-collected data from four Bay Area communities along with aggregate epidemiologic and population-level data sets to illustrate barriers to, and facilitators of, physical activity in low-income aging adults. These data integrations highlight the synergistic value added by combining data sources, and what might be missed by relying on either a micro- or macro-level data source alone. Mixed methods and granularity data integration can generate a deeper understanding of environmental context, which in turn can inform more relevant and attainable community, advocacy, and policy improvements.

What is counted counts: An innovative linkage of police, hospital, and spatial data for transportation injury prevention.

INTRODUCTION: Growing research indicates transportation injury surveillance using police collision reporting alone underrepresents injury to vulnerable groups, including pedestrians, cyclists, and people of color. This reflects differing reporting patterns and non-clinicians' challenge in accurately evaluating injury severity. To our knowledge, San Francisco is the first U.S. city to link and map hospital and police injury data. Analysis of linked data injury patterns informs interventions supporting traffic fatality and injury prevention goals. METHODS: Injury and fatality records 2013-2015 were collected from San Francisco Police, Emergency Medical Services (EMS), Medical Examiner, and Zuckerberg San Francisco General Hospital (ZSFG). Probabilistic linkage was conducted using LinkSolv9.0 on match variables collision/admission time, name, birthdate, sex, travel mode, and geographic collision location. RESULTS: From 2013-2015, this study identified 17,000+ transportation-related injuries on public roadways in San Francisco. Twenty-six percent (n = 4,415) appeared in both police and ZSFG sources. Linked injury records represent 39% of police records (N = 11,403) and 43% of hospital records (N = 10,223). Among hospital records, 34% of cyclist, 38% of motor vehicle occupant, 61% of pedestrian, and 54% of motorcyclist records linked with a police record. Linkage rate varied by travel mode even after controlling for injury severity. Transportation-injured ZSFG-treated patients lacking police reports were more often cyclists, male, Hispanic or Black, and less often occupants of motor vehicles compared to those with injuries captured only in police reports. CONCLUSIONS: Incorporating hospital and EMS spatial data into injury surveillance systems historically reliant on police reports offers trifold benefits. First, linkage captures injuries absent in police data, adding data on populations empirically vulnerable to injury. Second, it improves injury severity assessment. Finally, linked data better informs and targets interventions serving injury-burdened populations and road users, advancing transportation injury prevention. PRACTICAL APPLICATIONS: Linkage closes data gaps, improving ability to quantify injury and develop evidence-based interventions for vulnerable groups.

Roadway features associated with elderly drivers in motor vehicle crashes.

BACKGROUND: As the number of older US drivers has increased over the past decades, so has the number of injuries, hospitalizations, and deaths from motor vehicle crashes (MVCs) involving elderly drivers. We seek to identify personal, environmental, and roadway features associated with increased crashes involving elderly drivers. We hypothesize that elderly drivers are more likely to be involved in MVCs at intersections with more complex signage and traffic flow. METHODS: This is a retrospective observational study using 2015 to 2019 police traffic crash reports and a Department of Public Health database of built-environment variables from a single urban center. Demographics and environmental/road features were compared for vehicle-only MVCs involving elderly (≥65 years) and younger drivers. χ2 and nonparametric tests were used to analyze 36,168 drivers involved in MVCs. RESULTS: There were 2,575 (7.1%) elderly drivers involved in MVCs during the study period. Left turns and all-way stop signs were associated with increased crash risk among elderly drivers compared with younger drivers. Elderly-involved MVCs were less likely to occur at intersections with left-turn restrictions, traffic lights, only one-way streets, and bike lanes compared with MVCs with younger drivers. Elderly drivers were more likely to be involved in MVCs on weekdays, less often intoxicated at the time of the crash, and less frequently involved in fatal MVCs compared with younger drivers. However, elderly drivers were more frequently the at-fault party, especially after the age of 75 years. CONCLUSION: Updates to roadway features have potential to decrease injury and death from MVCs involving elderly adults. Left turn restrictions or other innovative safety treatments at all-way stops or where left turns are permitted may mitigate road crashes involving older adults. Education may increase awareness of higher-risk driving tasks such as turning left, and driving alternatives including public transportation/paratransit may offer alternate means to maintain activities of daily living. LEVEL OF EVIDENCE: Prognostic/Epidemiological, level IV.