Commenced in January 2007
Paper Count: 31108
The Origin, Diffusion and a Comparison of Ordinary Differential Equations Numerical Solutions Used by SIR Model in Order to Predict SARS-CoV-2 in Nordic Countries
Abstract:SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 87
 Bank, R. E., Coughran, W. M., Fichtner, W., Grosse, E. H., Rose, D. J., & Smith, R. K. Transient simulation of silicon devices and circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems; 1985. 4(4), 436–451.
 Boujakjian, H. Modeling the spread of Ebola with SEIR and optimal control. SIAM Undergraduate Research Online; 2016. 9, 299–310.
 Chen, Y., Cheng, J., Jiang, Y., & Liu, K. A time delay dynamical model for outbreak of 2019-nCoV and the parameter identification. Journal of Inverse and Ill-posed Problems; 2020. 28(2), 243–250.
 Cristianini, N., & Hahn, M. W. Introduction to computational genomics: a case studies approach. Cambridge University Press; 2006.
 Dormand, J. R., & Prince, P. J. A family of embedded Runge-Kutta formulae. Journal of computational and applied mathematics; 1980. 6(1), 19–26.
 Hosea, M. E., & Shampine, L. F. Analysis and implementation of TR-BDF2. Applied Numerical Mathematics; 1996. 20(1-2), 21–37.
 Guo, Z., Xiao, D., Li, D., Wang, X., Wang, Y., Yan, T., & Wang, Z. Predicting and evaluating the epidemic trend of ebola virus disease in the 2014-2015 outbreak and the effects of intervention measures. PloS one; 2016. 11(4).
 Kermack, W. O., & McKendrick, A. G. A contribution to the mathematical theory of epidemics.Proceedings of the royal society of london. Series A, Containing papers of a mathematical and physical character; 1927. 115(772), 700–721.
 Lai, D. Monitoring the SARS epidemic in China: a time series analysis.Journal of Data Science; 2005. 3(3), 279-293.
 Lipsitch, M., Cohen, T., Cooper, B., Robins, J. M., Ma, S., James, L., ... & Fisman, D. Transmission dynamics and control of severe acute respiratory syndrome. Science; 2003. 300(5627), 1966–1970.
 Loper, M. L. (Ed.). Modeling and simulation in the systems engineering life cycle: core concepts and accompanying lectures. Springer; 2015.
 Pandey, G., Chaudhary, P., Gupta, R., & Pal, S. SEIR and Regression Model based COVID-19 outbreak predictions in India. arXiv preprint arXiv:2004.00958; 2020.
 Poon, L. L. M., Chu, D. K. W., Chan, K. H., Wong, O. K., Ellis, T. M., Leung, Y. H. C., & Guan, Y. Identification of a novel coronavirus in bats. Journal of virology; 2005. 79(4), 2001–2009.
 Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. Numerical recipes 3rd edition: The art of scientific computing. Cambridge university press; 2007.
 Rachah, A., & Torres, D. F. Predicting and controlling the Ebola infection. Mathematical Methods in the Applied Sciences; 2017. 40(17), 6155–6164.
 Read, J. M., Bridgen, J. R., Cummings, D. A., Ho, A., & Jewell, C. P. Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions. MedRxiv; 2020.
 Shampine, L. F. Computer solution of ordinary differential equations: The Initial Value Problem. W.H. Freeman, San Francisco; 1975.
 Shampine, L. F., & Reichelt, M. W. The matlab ode suite. SIAM journal on scientific computing; 1997. 18(1), 1–22.
 Shampine, L. F., Reichelt, M. W., & Kierzenka, J. A. Solving index-1 DAEs in MATLAB and Simulink. SIAM review; 1999. 41(3), 538–552.
 Tang, Z., Li, X., & Li, H. Prediction of New Coronavirus Infection Based on a Modified SEIR Model. medRxiv; 2020.
 https://www.ncbi.nlm.nih.gov/nuccore?LinkName=genome_nuccore_ samespecies&from_uid=86693
 https://www.who.int/emergencies/diseases/ novel-coronavirus-2019/situation-reports/?gclid= EAIaIQobChMIptrK657D6QIVxeAYCh2I6g4YEAAYASACEgIHlv_ D BwE