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Activity Number: 90 - Novel Statistical Methods for COVID Pandemic and Other Current Health Policy Issues
Type: Contributed
Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
Sponsor: WNAR
Abstract #319106
Title: The Impact of Lockdown Timing on COVID-19 Transmission across US Counties
Author(s): Xiaolin Huang* and Xiaojian Shao and Xing Li and Yushan Hu and Don D. Sin and Xuekui Zhang
Companies: University of Victoria and National Research Council Canada and University of Saskatchewan and University of Victoria and St Paul’s Hospital and University of British Columbia and University of Victoria
Keywords: COVID-19; Functional Principal Component Analysis; Elastic Net; lockdown

Many countries have implemented lockdowns to reduce COVID-19 transmission. However, there is no consensus on the optimal timing of these lockdowns. Here we evaluated the relationship between timing of lockdowns, along with other risk factors, and the growth trajectories of COVID-19 across 3,112 counties in the US. We applied a Functional Principal Component Analysis to generate FPC scores, which were used as a surrogate variable to describe the trajectory of daily cumulative case counts for each county. We used machine learning methods to identify risk factors including the timing of lockdown that significantly influenced the FPC scores. Adjusted for the other factors, the impact of lockdown timing on the total daily case count of a county became significant beginning approximately 7 days prior to that county reporting at least 5 cumulative cases of COVID-19. Delays in lockdown implementation after this date led to a rapid acceleration of COVID-19 spread in the county over the first ~50 days from the date with at least 5 cumulative cases, and higher case counts across the entirety of the follow-up period.

Authors who are presenting talks have a * after their name.

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