Research Programme Team

Forecasting COVID-19 pandemic

Daily reports for all countries in PDF are available here. There is also the latest daily updated dataset.

 

Researchers of the Faculty of Maritime Studies and Transport of the University of Ljubljana are involved in researching the influence of the coronavirus pandemic on transport. An economic driven approach resulted in mathematical modelling of the future course of the virus epidemic. We developed two models, a logistic and a classical SIR model. Starting in February 2020, we relied almost exclusively on data from China. It was found that the forecast for the course of infections almost precisely matched the outcome predicted. From that point, the two 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, and the total for countries outside China. The Matlab program has been called the fitVirus and fitVirusCOVID19 program.

It is assumed that the model provides a reasonable description of the one-stage epidemic. In particular, the model assumes a constant population, uniform mixing of the people, and equal likelihood of recovery among those infected. The model is data-driven, so its forecast is only as good as the input data. The forecast changes with new or changed data. The input data are extracted from Worldometer and Wikipedia.

The model is available at the following link.
Logistic model description. SIR model description.

 

DISCLAIMER: Software and data may be used for educational purposes 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). Users are advised to use these data at their own discretion.