2024 High Injury Network
<strong>A. SUMMARY</strong> This dataset includes street segments that were identified to be on the 2024 High Injury Network (HIN). The HIN shows the street corridors that had the highest concentration of severe and fatal injuries in the years 2020 to 2024. Using the High Injury Network, San Francisco is better able to prioritize city resources to implement engineering, education, and enforcement activities that serve to make the streets safer. <strong>B. HOW THE DATASET IS CREATED</strong> This dataset is sourced from traffic crash data from the San Francisco Police Department, hospital data from Zuckerberg San Francisco General Hospital (ZSFG), and ambulance operator data from American Medical Response (AMR) and the San Francisco Fire Department Emergency Medical Services (EMS). These data are linked using a non-probabilistic deterministic method to match records between these three data sources. Once they are matched, any details about the crash circumstances are defaulted to come from the San Francisco Police Department (SFPD), and the final injury severity determination is sourced from ZSFG Hospital. The dataset also includes un-matched SFPD severe and fatal crash victims that had associated geolocations, as well as un-linked ZSFG Hospital data from the Trauma Registry that had linked geolocation data from the ambulance operators’ pick- up locations. San Francisco’s street centerline data layer is corridorized into segments that are at least 0.25 miles long along segments that share the same street name. Then, the point data of Killed or Severely Injured (KSI) is plotted onto the map and a KSI per mile per corridor is calculated based on a count of points that geographically intersect a given corridor. The base map for the HIN is created by filtering corridors based on minimum length. Any corridor that is less than 0.25 miles in total length is excluded from eligibility onto the network. Then, corridors are selected based on a minimum cutpoint of “gre
<strong>A. SUMMARY</strong> This dataset includes street segments that were identified to be on the 2024 High Injury Network (HIN). The HIN shows the street corridors that had the highest concentration of severe and fatal injuries in the years 2020 to 2024. Using the High Injury Network, San Francisco is better able to prioritize city resources to implement engineering, education, and enforcement activities that serve to make the streets safer. <strong>B. HOW THE DATASET IS CREATED</strong> This dataset is sourced from traffic crash data from the San Francisco Police Department, hospital data from Zuckerberg San Francisco General Hospital (ZSFG), and ambulance operator data from American Medical Response (AMR) and the San Francisco Fire Department Emergency Medical Services (EMS). These data are linked using a non-probabilistic deterministic method to match records between these three data sources. Once they are matched, any details about the crash circumstances are defaulted to come from the San Francisco Police Department (SFPD), and the final injury severity determination is sourced from ZSFG Hospital. The dataset also includes un-matched SFPD severe and fatal crash victims that had associated geolocations, as well as un-linked ZSFG Hospital data from the Trauma Registry that had linked geolocation data from the ambulance operators’ pick- up locations. San Francisco’s street centerline data layer is corridorized into segments that are at least 0.25 miles long along segments that share the same street name. Then, the point data of Killed or Severely Injured (KSI) is plotted onto the map and a KSI per mile per corridor is calculated based on a count of points that geographically intersect a given corridor. The base map for the HIN is created by filtering corridors based on minimum length. Any corridor that is less than 0.25 miles in total length is excluded from eligibility onto the network. Then, corridors are selected based on a minimum cutpoint of “gre