dc.creator | Hu, Bisong | |
dc.creator | Qiu, Jingyu | |
dc.creator | Chen, Haiying | |
dc.creator | Tao, Vincent | |
dc.creator | Wang, Jinfeng | |
dc.creator | Lin, Hui | |
dc.date.accessioned | 2020-07-17T17:33:19Z | |
dc.date.accessioned | 2022-09-23T18:15:35Z | |
dc.date.available | 2020-07-17T17:33:19Z | |
dc.date.available | 2022-09-23T18:15:35Z | |
dc.date.created | 2020-07-17T17:33:19Z | |
dc.identifier | 1201-9712 | |
dc.identifier | https://doi.org/10.1016/j.ijid.2020.05.048 | |
dc.identifier | http://hdl.handle.net/20.500.12010/10769 | |
dc.identifier | https://doi.org/10.1016/j.ijid.2020.05.048 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3498072 | |
dc.description.abstract | Objectives: The outbreak of atypical pneumonia caused by the novel coronavirus (COVID-19) has currently
become a global concern. The generations of the epidemic spread are not well known, yet these are
critical parameters to facilitate an understanding of the epidemic. A seafood wholesale market and
Wuhan city, China, were recognized as the primary and secondary epidemic sources. Human movements
nationwide from the two epidemic sources revealed the characteristics of the first-generation and
second-generation spreads of the COVID-19 epidemic, as well as the potential third-generation spread.
Methods: We used spatiotemporal data of COVID-19 cases in mainland China and two categories of
location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to
calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics.
Results: Two categories of device trajectories had generally significant correlations and determinant
powers of the epidemic spread. Bothr and q statistics decreased with distance from the epidemic sources
and their associations changed with time. At the beginning of the epidemic, the mixed first-generation
and second-generation spreads appeared in most cities with confirmed cases. They strongly interacted to
enhance the epidemic in Hubei province and the trend was also significant in the provinces adjacent to
Hubei. The third-generation spread started in Wuhan from January 17–20, 2020, and in Hubei from
January 23–24. No obvious third-generation spread was detected outside Hubei.
Conclusions: The findings provide important foundations to quantify the effect of human movement on
epidemic spread and inform ongoing control strategies. The spatiotemporal association between the
epidemic spread and human movements from the primary and secondary epidemic sources indicates a
transfer from second to third generations of the infection. Urgent control measures include preventing
the potential third-generation spread in mainland China, eliminating it in Hubei, and reducing the
interaction influence of first-generation and second-generation spreads | |
dc.publisher | Science Direct | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.source | reponame:Expeditio Repositorio Institucional UJTL | |
dc.source | instname:Universidad de Bogotá Jorge Tadeo Lozano | |
dc.subject | COVID-19 | |
dc.subject | Generations | |
dc.subject | Mobile device data | |
dc.subject | Statistic | |
dc.subject | Q statistic | |
dc.subject | Mainland China | |
dc.title | First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: an early exploratory study incorporating location-based service data of mobile devices | |