Related Experiment Video
Updated: Oct 20, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
Continuous-time stochastic processes for the spread of COVID-19 disease simulated via a Monte Carlo approach and
Fabiana Calleri1, Giovanni Nastasi1, Vittorio Romano2
1Dipartimento di Matematica e Informatica, Università degli Studi di Catania, Viale Andrea Doria 6, 95125, Catania, Italy.
Abstract:
Two stochastic models are proposed to describe the evolution of the COVID-19 pandemic. In the first model the population is partitioned into four compartments: susceptible S, infected I, removed R and dead people D. In order to have a cross validation, a deterministic version of such a model is also devised which is represented by a system of ordinary differential equations with delays. In the second stochastic model two further compartments are added: the class A of asymptomatic individuals and the class L of isolated infected people. Effects such as social distancing measures are easily included and the consequences are analyzed. Numerical solutions are obtained with Monte Carlo simulations. Quantitative predictions are provided which can be useful for the evaluation of political measures, e.g. the obtained results suggest that strategies based on herd immunity are too risky. Finally, the models are calibrated on data referring to the second wave of infection in Italy.
Related Concept Videos
Steps in Outbreak Investigation
Causality in Epidemiology
Statistical Methods for Analyzing Epidemiological Data
Mechanistic Models: Compartment Models in Individual and Population Analysis
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Random Variables
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...

