A. SUMMARY This data was created by the San Francisco Department of Public Health (SFDPH) to update the 2017 Vision Zero High Injury Network dataset. It identifies street segments in San Francisco that have a high number of fatalities and severe injuries. This dataset is a simplified representation of the network and only indicates which streets qualified; it does not contain any additional information, including prioritization by mode or a breakdown of count reported/unreported severe/fatal injuries by corridorized segment. SFDPH shares this network with CCSF agencies to help inform where interventions could save lives and reduce injury severity.

B. HOW THE DATASET IS CREATED The 2022 Vision Zero High Injury Network is derived from 2017-2022 severe and fatal injury data from Zuckerberg San Francisco General (ZSFG), San Francisco Police Department (SFPD), the Office of the Medical Examiner (OME), and Emergency Medical Services agencies. ZSFG patient records and SFPD victim records were probabilistically linked through the Transportation Injury Surveillance System (TISS) using LinkSolv Software. Injury severity for linked SFPD/ZSFG records was reclassified based on injury outcome as determined by ZSFG medical personnel (net 1732 police reported severe injuries) consistent with the Vision Zero Severe Injury Protocol (2017) while unlinked SFPD victim records were not changed (178 police reported severe injuries). Severe injuries captured by ZSFG but not reported to SFPD were also included in this analysis (650 unreported/unlinked geocodable severe injury patient records). Fatality data came from OME records that meet San Francisco’s Vision Zero Fatality Protocol (129 fatalities). Only transportation-related injuries resulting in a severe injury or fatality were used in this analysis. Each street centerline segment block was converted into ~0.25 mile overlapping corridorized sections using ArcPy. These sections were intersected with the severe/fatal injury data. Only severe/fatal injuries with the same primary street as the corridorized section were counted for that section. The count of severe/fatal injuries was then normalized by the sections mileage to derive the number of severe/fatal injuries per mile. A threshold of ≥10 severe/fatal injuries per mile was used as the threshold to determine if a corridorized segment qualified for inclusion into the network. A full methodology of the 2022 update to the Vision Zero High Injury Network can be found here: https://www.visionzerosf.org/wp-content/uploads/2023/03/2022_Vision_Zero_Network_Update_Methodology.pdf

C. UPDATE PROCESS This dataset will be updated on an as needed basis.

D. HOW TO USE THIS DATASET The 2022 Vision Zero Network represents a snapshot in time (2017-2021) where severe and fatal injuries are most concentrated. It may not reflect current conditions or changes to the City’s transportation system. Although prior incidents can be indicative of future incidents, the 2022 Vision Zero High Injury Network is not a prediction (probability) of future risk. The High Injury Network approach is in contrast to risk-based analysis, which focuses on locations determined to be more dangerous with increased risk or danger often calculated by dividing the number of injuries or collisions by vehicle volumes to estimate risk of injury per vehicle. The High Injury Network provides information regarding the streets where injuries, particularly severe and fatal, are concentrated in San Francisco based on injury counts; it is not an assessment of whether a street or particular ___location is dangerous. The 2022 Vision Zero Network is derived from the more severe injury outcomes (count of severe/fatal injuries) and may not cover locations with high numbers of less severe injury collisions. Hospital and emergency medical service records from which SFPD-unreported injury and reclassified injury collisions are derived are pro