Insights on cannabis dispensaries and drug sales?

My name is Zeyad Kelani, and I am new Postdoc at UCI’s Emergency Medicine and Informatics Department. The team and I are working with mobility data and looking to define some POIs using Safegraph data. I was wondering if Safegraph data can provide insights on the following:

  1. Cannabis dispensaries or related category
  2. Drug sales/prostitution
  3. Methadone/drug abuse clinics; and
    I would really appreciate it if you have used the data for similar purpose before.

Hi @Zeyad_Kelani, SafeGraph’s data can help with some of this:

  1. I believe SafeGraph has good coverage of cannabis dispensaries. The data definitely has liquor stores as well. You should be able to filter to these locations using the corresponding NAICS codes.
  2. SafeGraph’s data might not be as useful for drug sales/prostitution. Correct me if I’m wrong, but I’m guessing that most locations for these activities are not in well-defined points of interest.
  3. I would expect drug abuse clinics to appear in the dataset. If drug abuse clinics have their own NAICS codes, then you could find them that way. Otherwise, if you have a dataset of drug abuse locations you can address match them with SafeGraph’s data (using Placekey) to get SafeGraph’s foot traffic data to those locations.
    For some related work, check out this post by @David_Bradford and this post by @Shooshan_Danagoulian_Wayne_State_University.

Hi @Ryan_Kruse_MN_State,
Many thanks for your reply. Ok, I will use the NAICS codes then to look for POIs of interest.
True, drug sales/prostitution are not labeled POIs.

@Ryan_Kruse_MN_State which dataset should I request for then from the Safegraph catalog? I am new to POIs data.

@Zeyad_Kelani No worries. I would start with Core Places to identify the POIs that you want, because Core Places comes with a NAICS codes column. Then if you want mobility patterns data too, you can download Monthly or Weekly Patterns and join with the relevant locations from Core Places on the placekey column.

Thank you so much @Ryan_Kruse_MN_State . I really appreciate it.