Twitter-based population mobility and COVID-19 forecasting in South Carolina R-script and data

Published: 8 March 2021| Version 1 | DOI: 10.17632/68chgz6chh.1
Chengbo Zeng,


The data and R script are provided to allow for reproducibility of results for all of the information provided within the article ("Spatial-temporal relationship between population #mobility and COVID-19 outbreaks in South Carolina: A time series forecasting analysis").


Steps to reproduce

Instruction for accessing these data and script: Access, download, and extract the data resource and script from the URL. Using RStudio to open the R script "Mobility and COVID-19 in SC ". Change the path manually and import the datasets. The script included data management and analysis. No additional changes are needed. Run the script based on the instruction. In terms of the forecasting for specific county, users need to change the name of county manually.


University of South Carolina Arnold School of Public Health, University of South Carolina School of Medicine, University of South Carolina College of Arts and Sciences


Infectious Disease, Population, Movement, Twitter