COVID-19 Infection Exposure to Customers Shopping during Black Friday
Braxton Rolle, and Ravi Kiran

TL;DR
This study uses a simulated model of a Black Friday shopping event to analyze how COVID-19 spreads among customers, highlighting the impact of exposure distance and initial infective percentage on infection rates.
Contribution
It introduces a detailed simulation framework to quantify COVID-19 transmission dynamics in a large shopping environment during Black Friday.
Findings
Increasing exposure distance significantly raises infection numbers.
Higher initial infective percentage leads to a substantial increase in new infections.
Exposure distance and initial infective percentage are critical factors in infection spread.
Abstract
The outbreak of COVID-19 within the last two years has resulted in much further investigation into the safety of large events that involve a gathering of people. This study aims to investigate how COVID-19 can spread through a large crowd of people shopping in a store with no safety precautions taken. The event being investigated is Black Friday, where hundreds or thousands of customers flood stores to hopefully receive the best deals on popular items. A mock store was created, separated into several different shopping sections, and represented using a 2-D grid where each square on the grid represented a 5 feet by 5 feet area of the mock store. Customers were simulated to enter the store, shop for certain items, check out, and then leave the store. A percentage of customers were chosen to be infective when they entered the store, which means that they could spread infection quantum to…
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Taxonomy
TopicsCOVID-19 Pandemic Impacts · COVID-19 epidemiological studies · COVID-19 and Mental Health
