The Predictive Power of R0 in an Epidemic Probabilistic System

TL;DR

This paper investigates the limitations of the basic reproductive number R0 as a predictor for epidemic spread in finite, heterogeneous populations, highlighting its reduced predictive power compared to classical models.

Contribution

It generalizes the concept of R0 to finite, heterogeneous populations and analyzes its predictive limitations near epidemic thresholds.

Findings

Uncertainty in R0 remains large near the epidemic threshold.

Predictive power of R0 is significantly reduced in finite systems.

Classical R0 formulations do not fully capture epidemic dynamics in complex populations.

Abstract

An important issue in theoretical epidemiology is the epidemic threshold phenomenon, which specify the conditions for an epidemic to grow or die out. In standard (mean-field-like) compartmental models the concept of the basic reproductive number, R0, has been systematically employed as a predictor for epidemic spread and as an analytical tool to study the threshold conditions. Despite the importance of this quantity, there are no general formulation of R0 when one considers the spread of a disease in a generic finite population, involving, for instance, arbitrary topology of inter-individual interactions and heterogeneous mixing of susceptible and immune individuals. The goal of this work is to study this concept in a generalized stochastic system described in terms of global and local variables. In particular, the dependence of R0 on the space of parameters that define the model is investigated; it is found that near of the ``classical'' epidemic threshold transition the uncertainty about the strength of the epidemic process still is significantly large. The forecasting attributes of R0 for a discrete finite system is discussed and generalized; in particular, it is shown that, for a discrete finite system, the pretentious predictive power of R0 is significantly reduced.