Prediction of the time evolution of the Covid-19 Pandemic in Italy by a Gauss Error Function and Monte Carlo simulations

Ignazio Ciufolini; Antonio Paolozzi

The Monte Carlo simulations [6] [7] [8] have been designed to possibly take into account the measurement error in each daily number of the cumulative positive cases of Covid-19 in Italy. This error describes the uncertainty in the process of measuring the daily number of positive cases due to some fluctuations in the measurement procedures (such as a different number of performed daily tests of one day with respect to another day); of course this error does not describe the difference between the actual total positive cases and the diagnosed ones which can be very large 5 . However, the diagnosed cases are considered to be a representative sample of the population (i.e. of the total number of positive cases, which by the way is unknown). To get an estimate of the uncertainty in each daily number, we applied the following heuristic approach. We have assumed a measurement uncertainty in the total positive cases equal to 10% of each daily number (Gaussian distributed). the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.