Transmission Dynamics Model of Coronavirus COVID-19 for the Outbreak in Most Affected Countries of the World.
DOI:
https://doi.org/10.9781/ijimai.2020.04.001Keywords:
Sensitivity, Coronavirus COVID-19, Basic Reproductive NumberAbstract
The wide spread of coronavirus (COVID-19) has threatened millions of lives and damaged the economy worldwide. Due to the severity and damage caused by the disease, it is very important to fore-tell the epidemic lifetime in order to take timely actions. Unfortunately, the lack of accurate information and unavailability of large amount of data at this stage make the task more difficult. In this paper, we used the available data from the mostly affected countries by COVID-19, (China, Iran, South Korea and Italy) and fit this with the SEIR type model in order to estimate the basic reproduction number R_0. We also discussed the development trend of the disease. Our model is quite accurate in predicting the current pattern of the infected population. We also performed sensitivity analysis on all the parameters used that are affecting the value of R0.
Downloads
References
[1] Data source John Hopkins University. https://systems.jhu.edu/research/public-health/ncov/.
[2] Matteo Chinazzi et al: The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. March 2020. Science, DOI: 10.1126/science.aba9757.
[3] Jonathan M Read, Jessica RE Bridgen, Derek AT Cummings, Antonia Ho, Chris P Jewell: Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions. January 2020 medRxiv preprint. doi: https://doi.org/10.1101/2020.01.23.20018549.
[4] Simon James Fong, Gloria Li, Nilanjan Dey, Rubén González Crespo and Enrique Herrera-Viedma: Finding an Accurate Early Forecasting Model from Small Dataset: A Case of 2019-nCoV Novel Coronavirus Outbreak: March 2020. International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 6, No 1. DOI:10.9781/ijimai.2020.02.002.
[5] Chen Y, Cheng J, Jiang Y, Liu K.: A Time Delay Dynamical Model for Outbreak of 2019-nCoV and the Parameter Identification. Preprint 2020; arXiv:2002.00418.
[6] Liang Y, Xu D et al.: A Simple Prediction Model for the Development Trend of 2019-nCoV Epidemics Based on Medical Observations. Preprint 2020; arXiv:2002.00426.
[7] Zhou T, Liu Q, Yang Z, et al. Preliminary prediction of the basic reproduction number of the Wuhan novel coronavirus 2019-nCoV. Preprint 2020; arXiv:2001.10530.
[8] WHO 2019-nCoV situation reports. https://www.who.int.
[9] Igor Nesteruk: Statistics-Based Predictions of Coronavirus Epidemic Spreading in Mainland China. February 2020, Innov Biosyst Bioeng, vol. 4, no. 1, 13–18 DOI: 10.20535/ibb.2020.4.1.195074.
[10] Ye Liang, Dan Xu, Shang Fu, Kewa Gao, Jingjing Huan, Linyong Xu, Jia-da Li: A Simple Prediction Model for the Development Trend of 2019-nCov Epidemics Based on Medical Observations. February, 2020 Quantitative Biology, Populations and Evolution: arXiv:2002.00426v1 [q-bio.PE]
[11] Zhou, P., Yang, X., Wang, X. et al.: A pneumonia outbreak associated with a new coronavirus of probable bat origin. February 2020, Nature, https://doi.org/10.1038/s41586-020-2012-7.
[12] P. van den Driessche, and J. Watmough, Reproduction Numbers and SubThreshold Endemic Equilibria for Compartmental Models of Disease Transmission. 2002, Mathematical Biosciences, Vol. 180, pp. 29{48}.
[13] Stephen A. Lauer et al.: The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. MARCH 10, 2020. Annals of Internal Medicine, DOI: 10.7326/M20-0504
[14] M. A. Sanchez, and S. M. Blower, Uncertainty and Sensitivity Analysis of the Basic Reproductive Rate. 1997, American Journal of Epidemiology, Vol. 145, pp. 1127-1137.
[15] A. Cintron-Arias, C. Castillo-Chavez, L. M. A. Bettencourt, A. L. Lloyd, and H. T. Banks, The Estimation of the Effecctive Reproductive Number from Disease Outbreak Data. 2009, Mathematical Biosciences and Engineering, Vol. 6, pp. 261-282.
Downloads
Published
-
Abstract299
-
PDF84






