Modelling COVID-19

Nature Reviews Physics - Tập 2 Số 6 - Trang 279-281
Alessandro Vespignani1, Huaiyu Tian2, Christopher Dye3, James O. Lloyd‐Smith4, Rosalind M. Eggo5, Munik Shrestha1, Samuel V. Scarpino1, Bernardo Gutiérrez3, Moritz U. G. Kraemer3, Joseph T. Wu6, Kathy Leung6, GM Leung6
1Network Science Institute, Northeastern University, Boston, MA, USA
2State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
3Department of Zoology, University of Oxford, Oxford, UK
4Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
5Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
6WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

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Tài liệu tham khảo

Tian, H. et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science https://doi.org/10.1126/science.abb6105 (2020).

Lloyd-Smith, J. O., Schreiber, S. J., Kopp, P. E. & Getz, W. M. Superspreading and the effect of individual variation on disease emergence. Nature 438, 355–359 (2005).

Kucharski, A. J. & Althaus, C. L. The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmission. Eurosurveillance 20, 14–18 (2015).

Hellewell, J. et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob. Health 8, e488–e496 (2020).

Kraemer, M. U. G. et al. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 21, eabb4218 (2020).

Xu, B. & Kraemer, M. U. G. Open access epidemiological data from the COVID-19. Lancet Infect. Dis. 3099, 30119 (2020).

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Nature Reviews Physics

Tập 2 Số 6

279-281

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