With the aim of analyzing and predicting the dynamics of COVID-19, especially the occupation of ICU beds in different epidemic waves, the study led by Professor Henrique Paiva, in partnership with the Federal University of São Paulo (UNIFESP) and published in the journal Mathematical Modelling of Natural Phenomena, proposed a phenomenological model using data from five Italian regions.
The aim was to support decision-making by health authorities and hospital administrators, enabling more efficient management of resources and containment measures.
The results were highly effective: the model fitted the historical data very well, with an average relative RMSE of 0.51% for the fit and 0.93% for the forecasts. This accuracy was essential for anticipating the demand for beds and helping to reduce mortality rates.
In addition to the COVID-19 pandemic, the study highlights that the model can be adapted to other regions and diseases, due to its low cost and optimization efficiency.
It is a valuable tool for the planning and allocation of medical resources in future epidemics, strengthening the response capacity in emergency situations.Access the full article here.
