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Since the onset of the COVID-19 outbreak in Wuhan, China, numerous forecasting models have been proposed to project the trajectory of coronavirus infection cases. We propose a new discrete-time Markov chain transition matrix model that directly incorporates stochastic behavior and for which parameter estimation is straightforward from available data. Using such data from Chinas Hubei province (for which Wuhan is the provincial capital city), the model is shown to be flexible, robust, and accurate. As a result, it has been adopted by the first Shanghai assistance medical team in Wuhans Jinyintan Hospital, which was the first designated hospital to take COVID-19 patients in the world. The forecast has been used for preparing medical staff, intensive care unit (ICU) beds, ventilators, and other critical care medical resources and for supporting real-time medical management decisions. Empirical data from Chinas first two months (January/February) of fighting COVID-19 was collected and used to enhance the model by embedding NPI efficiency into the model. We applied the model to forecast Italy, South Korea, and Iran on March 9. Later we made forecasts for Spain, Germany, France, US on March 24. Again, the model has performed very well, proven to be flexible, robust, and accurate for most of these countries/regions outside China.
We present a simple analytical model to describe the fast increase of deaths produced by the corona virus (COVID-19) infections. The D (deaths) model comes from a simplified version of the SIR (susceptible-infected-recovered) model known as SI model.
Disease transmission is studied through disciplines like epidemiology, applied mathematics, and statistics. Mathematical simulation models for transmission have implications in solving public and personal health challenges. The SIR model uses a compa
We consider a global (location independent) model of pandemic growth which generalizes the SIR model to accommodate important features of the COVID-19 pandemic, notably the implementation of pandemic reduction measures. This SHIR model is applied to
The Covid-19 epidemic of the novel coronavirus (severe acute respiratory syndrome SARS - CoV-2) has been spreading around the world. While different containment policies using non-pharmaceutical interventions have been applied, their efficiency are n
We propose a mathematical model to analyze the time evolution of the total number of infected population with Covid-19 disease at a region in the ongoing pandemic. Using the available data of Covid-19 infected population on various countries we formu