Supplementary Data for "Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results from a Community-Partnered Low-cost Sensor Deployment"

These are the underlying data sets needed to build the kriging maps and calculate dissemination block cumulative hazard indices described in the paper. There are three data sets: <strong>"Sampling location names and coordinates.csv"</strong>: locations and IDs of the low-cost sensors and the regulatory monitoring stations used in this work.<strong> [NOTE: </strong>latitudes and longitudes for the sensor deployments have been intentionally rounded to protect the location of volunteer sensor hosts.] <strong>"Dissemination Block Populations.csv"</strong>: These are the relevant dissemination blocks in the study domain and their associated populations. This information was originally extracted from: https://censusmapper.ca/#13/49.2430/-123.1252 <strong>"Daily average concentrations by site and pollutant.csv"</strong>: This contains the PM2.5, NO2 and O3 daily averages for the entire study period across all low-cost sensor sites and regulatory monitoring stations. Refer to "Sampling location names and coordinates.csv" to parse the labels in this data set. There is also a sample code in Python to construct the kriging maps provided in 2 formats. <strong>[NOTE: </strong>we have intentionally excluded uploading the exact data sets imported by this code; our original data contains exact locations of sensor host volunteers and thus cannot be shared.] <strong>"Jain et al - GeoHealth - Kriging Script.ipynb"</strong>: A Jupyter notebook script to import the data, build kriging maps, calculate CHIs, and export the data. <strong>" Jain et al - GeoHealth - Kriging Script.pdf"</strong>: A PDF export of the Jupyter notebook so that you can read the Python scripts even if you are not a Jupyter notebooks user.