Forecasting COVID-19 pandemic
Researchers from the Faculty of Maritime Studies and Transport of the University of Ljubljana, are involved in researching the influence of Corona on transportation. An economic driven approach led to mathematical modelling of the future course of the virus epidemic. We developed two models, logisic and calssical SIR model, from back in February, relied almost exclusively on data from China, and it turned out that the forecast for the course of infections almost precisely matched the outcome predicted. From that point, the models have been applied to other countries and regions around the globe, forecasting the final epidemic numbers for: Argentina, Austria, Belgium, Brazil, China, Croatia, Denmark, France, Hungary, Germany, India, Indonesia, Iran, Italy, Lombardia, NY State, Netherlands, Norway, Poland, Portugal, Serbia, Slovenia, South Korea, Spain, Switzerland, UK, USA and parts of the USA such as New York state, and the total for countries outside of China. The Matlab program developed have being called the fitVirus and fitVirusCOVID19 program.
It is assumed that the model is a reasonable description of the one-stage epidemic. In particular, the model assumes a constant population, uniform mixing of the people, equally likelihood of recovery among those infected. The model is data-driven, so its forecast is only as good as the data are. The forecasting changes with new or changed data. Data used are from worldometers and Wikipedia.
DISCLAIMER: Software and data is for education and not for medical or commercial purposes. The model may fail in some situations. In particular, the model may be inadequate, the model may fail in the initial phase and when there are additional epidemic stages or outbreaks (not described by the SIR model). Use it at your own discretion.