safegraph-simulation

Codebase for SIGSPATIAL ARIC 2020: Foot-Traffic Informed COVID-19 Simulation and Mitigation

Installation

1. Clone the repository.

2. pip install -r requirements.txt.

3. Create a subdirectory called safegraph-data in the repository directory.

4. Download the SafeGraph Open Census Data here. Save it to safegraph-data/safegraph_open_census_data.

5. Get free access to the remaining SafeGraph data by following these steps. A non-disclosure agreement must be signed as part of the process.

6. Download the SafeGraph Weekly Patterns (v2) data. Save it to safegraph-data/safegraph_weekly_patterns_v2.

7. Download the SafeGraph Core Places data. Save it to safegraph-data/safegraph_core_places.

8. Download the SafeGraph Social Distancing Metrics data. Save it to safegraph-data/safegraph_social_distancing_metrics.

Usage

• county-parser.py is used to extract locality data. Run this at least once, and then run simulation.py. To create custom simulation configurations, place new .cfg files in config-files/. Use config-files/default-config.cfg as a template.

• simulation-naive.py is used to simulate community and household spread in a naive way by weighting POIs equally, ignoring the time of day, and using a constant dwell time. In most cases, the virus will only reach a very small number of agents because agents will not congregate at popular POIs, making this simulation version unrealistic.

• mobility-stats.py is used to evaluate mobility data assuming no virus has been introduced. It provides the total number of visitors to each POI within a specified timeframe.

• sigspatial-trials.txt, sigspatial-trial-runner.py, and any files in a folder that is titled sigspatial-trials/ were used to generate results for the conference publication. These files will likely not be applicable in other cases.

• All results will be located in results/.