Abstract
At the end of 2019, coronavirus disease (COVID-19) broke out in Wuhan, Hubei. With the spring festival travel rush, the epidemic spread rapidly to other provinces and even overseas. In the view of this epidemic, in this paper, we improved the classic SEIR model, introducing a new parameter, average delay time, to describe the incubation period and time for nucleic acid detection. Based on the data published by the National Health Commission of China, parameters of the model were estimated first. Then the model was used to simulate the development of COVID-19. The number of new confirmed cases and remaining confirmed cases of each day are predicted. Finally, the results show that the model is well fit for the actual data. By now, this epidemic has been basically under control, and under the current medical level and control measurements, it is hoped to announce the end of COVID-19 in China before May.
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References
Kai-Yuan, C., Lei, C.: Analyzing software science data with partial repeatability. J. Syst. Softw. 63(3), 173–186 (2002)
Lin, Z.: Fitness of the generalized growth to the 2019 novel coronavirus data, Journal of University of Electronic Science and Technology of China. https://doi.org/10.12178/1001-0548.2020037
Ru-Guo, F., Yi-Bo, W., Ming, L., Ying-Qing, Z., Chao-Ping, Z.: SEIR-based novel pneumonia transmission model and inflection point prediction analysis. J. Univ. Electron. Sci. Technol. China. https://doi.org/10.12178/1001-0548.2020029
Ying, L., Gayle Albert, A.: Wilder-Smith Annelies, The reproductive number of COVID-19 is higher compared to SARS coronavirus. J. Travel Med. https://doi.org/10.1093/jtm/taaa021
Tao, Z., Quan-Hui, L., Zi-Mo, Y., Jing-Yi, L., Ke-Xin, Y., Bai Wei, Lu., Xin, Z.W.: Preliminary prediction of the basic reproduction number of the Wuhan novel coronavirus 2019-nCoV. Chin. J. Evidence-Based Med. 20(3), 359–364 (2020)
Yan, Y., Chen, Yu., Ke-Ji, L., Luo Xin-Yue, Xu., Bo-Xi, J.Y., Jin, C.: Modeling and prediction for the trend of outbreak of NCP based on a time-delay dynamic system. SCIENTIA SINICA Math. 50(8), 1–8 (2020)
Tian-Mu, C., Jia, R., Qiu-Peng, W.: A mathematical model for simulating the phase-based transmissibility of a novel coronavirus. Infect. Dis. Poverty 9(1), 24 (2020)
Zhi-Xin, W., Zhi, L., Zhao-Jun, L.: 2019-nCoV analysis and forecast based on machine learning. Journal of Biomedical Engineering Research 39(01), 1–5 (2020)
Zi-Feng, Y., Zhi-Qi, Z., Ke, W.: Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J. Thoracic Dis. 12(3), 165–174 (2002)
Gong-Xian, X., En-Min, F., Zong-Tao, W., Xin-Xin, T., Zhi-Long, X.: SEIR dynamic model of SARS epidemic and its parameter identification. J. Natural Sci. Heilongjiang Univ. 22(4), 459–462,467 (2005)
Chao, W., Yang Xu-Ying, Xu., Ke, M.-F.: SEIR-Based model for the information spreading over SNS. Acta Electronica Sinica 42(11), 2325–2330 (2014)
Chen Bo, Yu., Ling, L.-T., Weimin, C.: Dissemination and control model of internet public opinion in the ubiquitous media environments. Syst. Eng. Theory Pract. 31(11), 2140–2150 (2011)
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This work is supported by the Aviation Power Fund (6141B09050377).
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Cui, G., Quan, Q. (2022). Modeling and Prediction of COVID-19 with Long Incubation Period Under High-Intensity Control in China. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_323
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DOI: https://doi.org/10.1007/978-981-15-8155-7_323
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