Geolocated Twitter social media data to describe the geographic spread of SARS-CoV-2

J Travel Med. 2020 Aug 20;27(5):taaa120. doi: 10.1093/jtm/taaa120.

Abstract

Openly available, geotagged Twitter data from 2013 to 2015 was used to estimate the 2019–2020 human mobility patterns in and outside of China to predict the spatiotemporal spread of severe acute respiratory syndrome coronavirus 2. Countries with the highest number of visiting Twitter users outside of China were the USA, Japan, UK, Germany and Turkey. A high correlation was observed when comparing country-level Twitter user visits and reported cases.

Keywords: COVID-19; SARS-CoV2; Twitter; epidemiology; geospatial; mobility; pandemic.

MeSH terms

  • Betacoronavirus
  • COVID-19
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / transmission*
  • Global Health
  • Humans
  • Pandemics
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / transmission*
  • SARS-CoV-2
  • Social Media / statistics & numerical data*
  • Spatio-Temporal Analysis