26
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The effect of human mobility and control measures on the COVID-19 epidemic in China

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.

          Related collections

          Most cited references 19

          • Record: found
          • Abstract: found
          • Article: not found

          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

               Qun Li,  Xuhua Guan,  Peng Wu (2020)
              Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
                Bookmark

                Author and article information

                Journal
                Science
                Science
                SCIENCE
                Science (New York, N.y.)
                American Association for the Advancement of Science
                0036-8075
                1095-9203
                25 March 2020
                Affiliations
                [1 ]Department of Zoology, University of Oxford, Oxford, UK,
                [2 ]Harvard Medical School, Harvard University, Boston, MA, USA.
                [3 ]Boston Children’s Hospital, Boston, MA, USA.
                [4 ]Network Science Institute, Northeastern University, Boston, MA, USA.
                [5 ]School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador.
                [6 ]Mathematical Sciences, University of Southampton, Southampton, UK.
                [7 ]Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA.
                [8 ]Harvard T.H. Chan School of Public Health, Boston, MA, USA.
                [9 ]Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
                [10 ]Sorbonne Universite, Paris, France.
                [11 ]ISI Foundation, Turin, Italy.
                [12 ]State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
                [13 ]Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK.
                Author notes
                [†]

                Members of the Open COVID-19 Data Working Group are listed in the supplementary materials.

                Article
                abb4218
                10.1126/science.abb4218
                7146642
                32213647
                Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                Funding
                Funded by: doi http://dx.doi.org/10.13039/501100004211, Oxford Martin School, University of Oxford;
                Categories
                Research Article
                Research Articles
                R-Articles
                Ecology
                Epidemiology
                Coronavirus

                Uncategorized

                Comments

                Comment on this article