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Editorial
. 2020 Jul;21(5):665-668.
doi: 10.1007/s10198-020-01202-y.

Modelling Covid-19 under uncertainty: what can we expect?

Meimei Wang  1 , Steffen Flessa  2
Affiliations
Editorial

Modelling Covid-19 under uncertainty: what can we expect?

Meimei Wang et al. Eur J Health Econ. 2020 Jul.
No abstract available

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Figures

Fig. 1
Fig. 1
Covid-19 model structure
Fig. 2
Fig. 2
Covid-19 model SIR-results (own)
Fig. 3
Fig. 3
Sick patients and infection rate (results from own simulations)
See this image and copyright information in PMC

References

    1. Heymann DL, Shindo N. COVID-19: what is next for public health? Lancet. 2020;395(10224):542–545. doi: 10.1016/S0140-6736(20)30374-3. - DOI - PMC - PubMed
    1. Hopkins, J: Corona Resource Center. https://coronavirus.jhu.edu/ (2020). Accessed 4 May 2020
    1. Tan-Torres ET, World Health Organization . Making choices in health: WHO guide to cost-effectiveness analysis. Geneva: World Health Organization; 2003.
    1. Vivanco-Lira, A.: Predicting COVID-19 distribution in Mexico through a discrete and time-dependent Markov chain and an SIR-like model. arXiv preprint arXiv:2003.06758 (2020)
    1. Song PX, et al. An epidemiological forecast model and software assessing interventions on COVID-19 epidemic in China. medRxiv. 2020 doi: 10.1101/2020.02.29.20029421. - DOI

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