Related Experiment Video
Updated: Nov 22, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling
Published on: June 23, 2022
Estimating and explaining the spread of COVID-19 at the county level in the USA
Anthony R Ives1, Claudio Bozzuto2
1Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, 53706, USA. arives@wisc.edu.
Abstract:
The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R2 = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R0 allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R0 argues for public health policies enacted at the county level for controlling COVID-19.
Related Concept Videos
Steps in Outbreak Investigation
Pie Chart
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
Statistical Methods for Analyzing Epidemiological Data
Causality in Epidemiology
Estimating Population Standard Deviation
Pareto Chart
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...

