On Key Epidemiological Metrics during Infectious Disease Outbreaks

TL;DR

This paper reviews key epidemiological metrics during infectious disease outbreaks, focusing on time-varying epidemic models and their implications for understanding and predicting disease dynamics.

Contribution

It introduces a time-varying SIR-like model to derive and analyze epidemic metrics, enhancing understanding of outbreak dynamics under changing conditions.

Findings

Derived closed-form equations for key metrics like reproduction ratio and doubling time.

Analyzed differences between time-varying and time-invariant epidemic models.

Explored predictive capabilities of the model under various scenarios.

Abstract

In this work, we review the figures used to characterize an epidemic outbreak most. Particular attention is drawn to epidemic spreading at time-varying transition rates. A time-varying SIR-like model is used to describe the epidemic dynamics, from which closed equations relating parameters and key quantities like reproduction ratio and doubling time are derived. The definition and computation of these metrics are revisited in the context of the general solution to the time-varying model dynamics, focusing on the similarities and differences with the time-invariant case. Further, the prediction of these metrics, that is of the disease evolution, as response to different scenarios is also investigated.