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COVID-19 mortality and health care demand. Preprint, Imperial College COVID-19
Response Team
14. Liu Y, Gayle AA, Wilder-Smith A, Rocklöv J (2020) The reproductive number of
COVID-19 is higher compared to SARS coronavirus. J Travel Medicine, 27(2), taaa021,
https://doi.org/10.1093/jtm/taaa021
15. Li Y, Liang M, Yin X et al (2020) COVID-19 epidemic outside China: 34 founders and
exponential growth. [Preprint.] medRxiv. https://doi.org/10.1101/2020.03.01.20029819
16. Kucharski AJ et al (2020) Early dynamics of transmission and control of COVID-19: a
mathematical modelling study. Lancet Infect Dis. https://doi.org/10.1016/S1473-3099(20)
30144-4
17. Batista M (2020) Estimation of the final size of the COVID-19 epidemic. [Preprint.]
medRxiv. https://doi.org/10.1101/2020.02.16.20023606
18. Hong HG, Li Y (2020) Estimation of time-varying reproduction numbers underlying
epidemiological processes: a new statistical tool for the COVID-19 pandemic. PLoS ONE
15(7):e0236464. https://doi.org/10.1371/journal.pone.0236464
19. Dehning J et al (2020) Inferring COVID-19 spreading rates and potential change points for
case number forecasts. Preprint, ArXiv:2004.01105
20. Chen Y, Cheng J, Jiang Y, Liu K (2020) A time delay dynamical model for outbreak of
2019-nCoV and the parameter identification. ArXiv:2002.00418
21. Peng L, Yang W, Zhang D, Zhuge C, Hong L (2020) Epidemic analysis of COVID-19 in
China by dynamical modeling. ArXiv:2002.06563
22. Chang SL, Harding N, Zachreson C, Cliff OM, Prokopenko M (2020) Modelling
transmission and control of the COVID-19 pandemic in Australia. ArXiv:2003.10218
23. Pellis L, Scarabel F, Stage HB, Overton CE, Chappell LH, Lythgoe KA et al (2020)
Challenges in control of Covid-19: short doubling time and long delay to effect of
interventions. ArXiv:2004.00117
24. Zhou T, Liu Q, Yang Z, Liao J, Yang K, Bai W et al (2020) Preliminary prediction of the
basic reproduction number of the Wuhan novel coronavirus 2019-nCoV. J Evid-Based
Med. https://doi.org/10.1111/jebm.12376PMID:3204881523
25. Maier BF, Brockmann D (2020) Effective containment explains sub-exponential growth in
confirmed cases of recent COVID-19 out break in mainland China. ArXiv:2002.07572
26. Song PX, Wang L, Zhou Y, He J, Zhu B, Wang F et al (2020) An epidemiological forecast
model and software assessing interventions on COVID-19 epidemic in China. MedRxiv
27. Chinazzi M, Davis JT, Ajelli M, Gioannini C, Litvinova M, Merler S et al (2020) The effect
of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.
Science 368(6489):395–400. https://doi.org/10.1126/science.aba9757 PMID:32144116
28. Zhang Y, Jiang B, Yuan J, Tao Y (2020) The impact of social distancing and epicenter
lockdown on the COVID-19 epidemic in mainland China: a data-driven SEIQR model
study. MedRxiv
29. Benlagha N (2020) Modeling the declared new cases of COVID-19 trend using advanced
statistical approaches. [Preprint.] ResearchGate. March 2020. https://doi.org/10.6084/m9.
figshare.12052638
30. Udomsamuthirun P et al (2020) The reproductive index from SEIR model of Covid-19
epidemic in Asean. [Preprint.] MEDRXIV. https://doi.org/10.1101/2020.04.24.20078287
31. Pereira IG et al (2020) Forecasting Covid-19 dynamics in Brazil: a data driven approach.
Int J Environ Res Public Health 17(14):5115. https://doi.org/10.3390/ijerph17145115
32. Linka K, Peirlinck M, Kuhl E (2020) The reproduction number of COVID-19 and its
correlation with public health interventions. [Preprint.] MEDRXIV. https://doi.org/10.1101/
2020.05.01.20088047
33. Draper NR, Smith H (1998) Applied regression analysis (3rd edn) John Wiley
34. https://onlinepubs.trb.org/onlinepubs/nchrp/cd-22/manual/v2appendixc.pdf
166
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