Predicting US Covid-19 Infection Rate using Time-delay Recurrence Simulation
Keywords:
US Covid-19, Simulations, Prediction, Growth Rates, Recurrence ModelAbstract
A recursion model is developed to describe the growth of Covid-19 cases in the USA. An essential requirement of any model is confidence in its predictive capability. Published growth rates for Covid-19 in the USA are shown to correlate well with recursive time-delay simulations. Data for six months after March 2020 is compared to predictions from known logistic equations and modified time-delay relations. Simple logistic equations do not show a correlated trajectory with case numbers, whereas a time-delay recurrence equation can be calibrated to follow actual data. Modelling predicts over 10 million infections by January 2021. Growth curves projected to mid-2022 are examined and discussed. Infection totals in the USA is predicted to approach 35 million cases by the end of 2021 without human control.
References
P.F. Verhulst, “Recherches mathématiques sur la loi d`accroissement de la population,” Nouv. mém. de l`Academie Royale des Sci. et Belles-Lettres de Bruxelles, Vol.18, pp.1-41, 1845.
Shuichi Kinoshita, "Introduction to Nonequilibrium Phenomena, Pattern Formations and Oscillatory Phenomena, Lotka-Volterra Model," Elsevier Science Direct, pp. 1-59, 2013.
F.J. Richards, "A Flexible Growth Function for Empirical Use," Journal of Experimental Botany, Vol.10, No.2, pp.290-310, 1959.
Ke Wu, Didier Darcet, Qian Wang, Didier Sornette, "Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world," medRxiv, Mar-16, 2020. doi.org/10.1101/2020.03.11.20034363
Santhosh Samuel Mathews, “Modelling and Analysis of Covid-19 Spread among People in a Queue,” International Journal of Scientific Research in Biological Sciences, Vol. 7, Issue.3, pp.25-33, 2020.
Robert M. May, "Chaos and the Dynamics of Biological Populations," Proc. of the Royal Society of London, Dynamical Chaos, Chapter 4, pp. 27-44, 1987.
M.Y. Dawed, P.R. Koya, A.T. Goshu,, "Mathematical Modelling of Population Growth: The Case of Logistic and Von Bertalanffy Models," Open Journal of Modelling and Simulation, Vol.2, No.4, 2014.
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