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https://github.com/bansallab/indoor_outdoor

https://github.com/bansallab/indoor_outdoor

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  • Host: GitHub
  • Owner: bansallab
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 28.1 MB
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Created almost 5 years ago · Last pushed about 3 years ago

https://github.com/bansallab/indoor_outdoor/blob/main/ 

# Disentangling the rhythms of human activity in the built environment for airborne transmission risk
This repository provides the data and source code for the following study: Zachary Susswein, Eva Rest, Shweta Bansal. "Disentangling the rhythms of human activity in the built environment for airborne transmission risk". *Elife*, 2023. https://doi.org/10.7554/eLife.80466

## Deriving the metric
In the `deriving_indoor_activity_metric` directory, we provide the code for deriving the indoor activity metric using the Safegraph Weekly Patterns data (which are available for researchers directly from Safegraph). We also provide the file of indoor/outdoor classifications that we derived for each Safegraph POI.

## Data
Data on the indoor activity seasonality metric (\sigma) that we define in this work can be found in the `indoor_activity_data` directory. The `indoor_activity_2018_2020.csv` file contains weekly, county-level (fips) indoor activity estimates.

## Analysis
#### Time series clustering
Python code for the time series clustering in this work can be found in the `time_series_clustering` directory.

#### Sinusoidal fits
R code for the sinusoidal fits in this work can be found in the `sinusoidal_fit` directory.

Owner

  • Name: Bansal Lab
  • Login: bansallab
  • Kind: organization
  • Location: Georgetown University, Washington DC

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