Use of Twitter social media activity as a proxy for human mobility to predict the spatiotemporal spread of 2019 novel coronavirus at global level
Bisanzio, D., Kraemer, M. U. G., Bogoch, I. I., Brewer, T., Brownstein, J. S., & Reithinger, R. (2020). Use of Twitter social media activity as a proxy for human mobility to predict the spatiotemporal spread of 2019 novel coronavirus at global level. RTI International.
Importance: In December 2019 pneumonia cases of unknown etiological origin were reported in Wuhan, China. By January 30 2020, more than 8,235 confirmed cases of 2019 novel coronvirus (2019-nCoV) had been reported, including 170 deaths, with cases reported in Wuhan and other provinces in China, as well as in in 18 international locations outside of mainland China.
Objective: To predict the spatiotemporal spread of 2019-nCoV at global level.
Design: Human mobility patterns were estimated by using openly available geolocated Twitter social media data posted from November 1, 2013, to February 28, 2014, and from November 1, 2014, to February 28, 2015. Case data were used to investigate the correlation among cases reported during the current 2019-nCoV outbreak, locations visited by a study cohort of Twitter users, and airports with scheduled flights from Wuhan in China. Infectious disease vulnerability index (IDVI) data were obtained to identify the capacity of countries receiving travellers from Wuhan to respond to infectious disease threats.
Participants: Publicly available 2019-nCoV case data reported since December 2019.
Main Outcome(s) and Measure(s): Human mobility patterns as per Twitter users who had (1) tweeted at least twice on consecutive days from Wuhan between November 1, 2013, and January 28, 2014, and November 1, 2014, and January 28, 2015; and (2) left Wuhan following their second tweet during the time period under investigation.
Results: Our study cohort comprised 161 users posting more than two tweets within two consecutive days from Wuhan during the study period. Of these users, 133 (82.6%) posted tweets from 157 Chinese cities (1,344 tweets) during the 30 days after leaving Wuhan following their second tweet, with a median of 2 (IQR= 1–3) locations visited and a mean distance of 601 km (IQR= 295.2–834.7 km) traveled. Of our user cohort, 60 (37.2%) traveled abroad to 119 locations in 28 countries. Of the 82 2019-nCoV cases reported outside China as of January 30, 2020, 54 cases had known geolocation coordinates and 74.1% (40 cases) were reported less than 15 km (median = 7.4 km, IQR= 2.9–285.5 km) from a location visited by at least one of our study cohort’s users. Countries visited by the cohort’s users and which have cases reported by January 30, 2020, had a median IDVI equal to 0.74.
Conclusions and Relevance: Based on our analyses, we anticipate cases to be reported soon in the United Kingdom, Saudi Arabia and Indonesia, all countries to which more than one user from our study cohort travelled within 30 days after having tweeted a second time from Wuhan during our study period; additionally, countries with a moderate to low IDVI (i.e. ≤0.7) such as Barbados, Indonesia, Pakistan, and Turkey should be on high alert and develop 2019-nCOV response plans as soon as permitting.