Super-Spreader Businesses and Risk of COVID-19 Transmission

Track D, Team 6:

Participants:

Ashley O’Donoghue, PhD
Tenzin Dechen, MPH
Whitney Pavlova
Dr GARBA Moussa
Manvi Madan, MS
Michael Boals, MS

Mentors:

Frank DeFalco
Aalok Thakkar

Research Question

Are counties with a higher concentration of super-spreader businesses associated with increased risk of COVID-19 transmission?

Aim 1: Classify businesses into super-spreaders and not super-spreaders based on frequency and duration of visits pre-pandemic.

Aim 2: Identify association between counties with higher super-spreaders and COVID-19 cases.

Datasets

• John Hopkins University Dataset for COVID 19 - (For Confirmed cases and Deaths)
• SafeGraph - (To get Foot Traffic in businesses across industries)
• NAICS - (to map business codes to businesses and industries)

Methodology

• Aim 1: Classify businesses into super-spreaders and not super-spreaders based on frequency and duration of visits pre-pandemic.

• Aim 2: Identify association between counties with higher density of super-spreaders and COVID-19 cases.

  Negative Binomial Regression

Presentation link

• TrackD_Team006_Final

Prerequisites for technical implementation

• Python 3
• BigQuery
• Stata 14
• Tableau