Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Oct:139:110090.
doi: 10.1016/j.chaos.2020.110090. Epub 2020 Jul 4.

The susceptible-unidentified infected-confirmed (SUC) epidemic model for estimating unidentified infected population for COVID-19

Affiliations

The susceptible-unidentified infected-confirmed (SUC) epidemic model for estimating unidentified infected population for COVID-19

Chaeyoung Lee et al. Chaos Solitons Fractals. 2020 Oct.

Abstract

In this article, we propose the Susceptible-Unidentified infected-Confirmed (SUC) epidemic model for estimating the unidentified infected population for coronavirus disease 2019 (COVID-19) in China. The unidentified infected population means the infected but not identified people. They are not yet hospitalized and still can spread the disease to the susceptible. To estimate the unidentified infected population, we find the optimal model parameters which best fit the confirmed case data in the least-squares sense. Here, we use the time series data of the confirmed cases in China reported by World Health Organization. In addition, we perform the practical identifiability analysis of the proposed model using the Monte Carlo simulation. The proposed model is simple but potentially useful in estimating the unidentified infected population to monitor the effectiveness of interventions and to prepare the quantity of protective masks or COVID-19 diagnostic kit to supply, hospital beds, medical staffs, and so on. Therefore, to control the spread of the infectious disease, it is essential to estimate the number of the unidentified infected population. The proposed SUC model can be used as a basic building block mathematical equation for estimating unidentified infected population.

Keywords: COVID-19; Epidemic model; Least-squares fitting.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Epidemic curve of COVID-19 confirmed cases from 21 January to 24 February 2020.
Fig. 2
Fig. 2
Flow chart of the SUC model: S is susceptible, U is infected but not confirmed (i.e., unidentified infected), and C is confirmed or removed. Here, the removed indicates the recovered or dead cases.
Fig. 3
Fig. 3
Computational results: (a), (b), and (c) are results with N=109,108,107and p=22; (d), (e), and (f) are results with N=109,108,107and p=14; (g), (h), and (i) are results with N=109,108,107and p=7.
Fig. 4
Fig. 4
(a), (b), and (c) are results with p=8and N=109,108,and 107, respectively, from 17 February 2020.

References

    1. Zhao S., Musa S.S., Lin Q., Ran J., Yang G., Wang W., et al. Estimating the unreported number of novel coronavirus (2019-nCoV) cases in China in the first half of january 2020: a data-driven modelling analysis of the early outbreak. J Clin Med. 2020;9(2):388. - PMC - PubMed
    1. Novel Coronavirus (2019-nCoV) situation reports. Available online: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situatio....
    1. Anzai A., Kobayashi T., Linton N.M., Kinoshita R., Hayashi K., Suzuki A., et al. Assessing the impact of reduced travel on exportation dynamics of novel coronavirus infection (COVID-19) J Clin Med. 2020;9(2):601. - PMC - PubMed
    1. Roosa K., Lee Y., Luo R., Kirpich A., Rothenberg R., Hyman J.M., et al. Short-term forecasts of the COVID-19 epidemic in Guangdong and Zhejiang, China: February 13–23, 2020. J Clin Med. 2020;9(2):596. - PMC - PubMed
    1. Backer J.A., Klinkenberg D., Wallinga J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020. Eurosurveillance. 2020;25(5):2000062. - PMC - PubMed

LinkOut - more resources