Issue |
Math. Model. Nat. Phenom.
Volume 15, 2020
Coronavirus: Scientific insights and societal aspects
|
|
---|---|---|
Article Number | 74 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/mmnp/2020050 | |
Published online | 10 December 2020 |
- Epidemiology Working Group for NCIP Epidemic Response, The epidemiological characteristics of an outbreakof 2019 novel coronavirus diseases (COVID-19) in China. Chin. J. Epidemiol. 41 (2020) 145–151. [Google Scholar]
- H. Haario, M. Laine, A. Mira and E. Saksman, DRAM: efficient adaptive MCMC. Stat. Comput. 16 (2006) 339–354. [Google Scholar]
- R. Li, S. Pei, B. Chen, Y. Song, T. Zhang, W. Yang and J. Shaman, Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2). Science 368 (2020) 489–493. [Google Scholar]
- Q. Lin, S. Zhao, D. Gao, Y. Lou, S. Yang, S.S. Musa et al., A conceptual model for the coronavirusdisease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action. Int. J. Infect. Dis. 93 (2020) 211–216. [CrossRef] [PubMed] [Google Scholar]
- M. Lipsitch, Transmission dynamics and control of severe acute respiratory syndrome. Science 300 (2003) 1966–1970. [Google Scholar]
- Y. Liu, A.A. Gayle, A. Wilder-Smith and J. Rocklöv, The reproductive number of COVID-19 is higher compared to SARS coronavirus. J. Travel Med. 27 (2020). [Google Scholar]
- K. Mizumoto, K. Kagaya, A. Zarebski and G. Chowell, Estimating the asymptomatic proportion of coronavirusdisease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance 25 (2020) 2000180. [CrossRef] [Google Scholar]
- K. Prem, Y. Liu, T.W. Russell, A.J. Kucharski, R.M. Eggo, N. Davies et al., The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health 5 (2020) E261–E270. [CrossRef] [PubMed] [Google Scholar]
- B. Tang, N.L. Bragazzi, Q. Li, S. Tang, Y. Xiao and J. Wu, An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov). Infect. Dis. Modell. 5 (2020) 248–255. [CrossRef] [Google Scholar]
- B. Tang, X. Wang, Q. Li, N.L. Bragazzi, S. Tang, Y. Xiao and J. Wu, Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions. J. Clin. Med. 9 (2020) 462. [Google Scholar]
- P. van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180 (2002) 29–48. [Google Scholar]
- P.G. Walker, C. Whittaker, O. Watson, M. Baguelin, K.E.C. Ainslie, S. Bhatia et al., Report 12: The global impact of COVID-19 and strategies for mitigation and suppression. Technical report, Imperial College London (2020). https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gidafellowships/Imperial-College-COVID19-Global-Impact-26-03-2020v2.pdf. [Google Scholar]
- K. Wan, J. Chen, C. Lu, L. Dong, Z. Wu and L. Zhang, When will the battle against novel coronavirus end in Wuhan: A SEIR modeling analysis. J. Glob. Health 10 (2020) 011002. [CrossRef] [PubMed] [Google Scholar]
- Y. Wei, Z. Lu, Z. Du, Z. Zhang, Y. Zhao, S. Shen et al., Fitting and forecasting the trend of COVID-19 by seir (+ caq) dynamic model. Chin. J. Epidemiol. 41 (2020) 470–475. [Google Scholar]
- J.T. Wu, K. Leung and G.M. Leung, Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet 395 (2020) 689–697. [CrossRef] [PubMed] [Google Scholar]
- S. Zhao, Q. Lin, J. Ran, S.S. Musa, G. Yang, W. Wang et al., Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China,from 2019 to 2020: A data-driven analysis in the early phase of the outbreak. Int. J. Infect. Dis. 92 (2020) 214–217. [CrossRef] [PubMed] [Google Scholar]
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