Examining the effect of social distancing on the compound growth rate of COVID-19 at the county level (United States) using statistical analyses and a random forest machine learning model.

ABSTRACT:

Objectives

The goal of the present work is to investigate trends among US counties and coronavirus disease 2019 (COVID-19) growth rates in relation to the existence of shelter-in-place (SIP) orders in that county.

Study design

This is a prospective cohort study.

Methods

Compound growth rates were calculated using cumulative confirmed COVID-19 cases from January 21, 2020, to March 31, 2020, in all 3139 US counties. Compound growth was chosen as it gives a single number that can be used in machine learning to represent the speed of virus spread during defined time intervals. Statistical analyses and a random forest machine learning model were used to analyze the data for differences in counties with and without SIP orders.

Results

Statistical analyses revealed th

SUBMITTER: Cobb JS 

PROVIDER: S-EPMC7186211 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature