Questioning the use of global estimates of reproduction numbers, with implications for policy

TL;DR

This paper critiques the common practice of using a single global estimate of the basic reproduction number ($R_0$) for infectious diseases, highlighting its limitations and implications for policy decisions.

Contribution

It challenges the validity of averaging $R_0$ estimates across populations and discusses practical issues with theoretically grounded methods like the next generation matrix.

Findings

Averaging $R_0$ estimates can be misleading.

Single $R_0$ values do not capture population heterogeneity.

Practical impediments exist in applying complex $R_0$ estimation methods.

Abstract

The basic reproduction number, $R_0$ is an important and widely used concept in the study of infectious diseases. We briefly review the recent trend of calculating the average of various $R_0$ estimates in systematic reviews aimed at estimating the basic reproduction number of SARS-CoV-2, and discuss the drawbacks and implications of using such averaging methods. Additionally, we argue that even a theoretically grounded approach such as next generation matrix could have practical impediments in its use. More generally, the practice of associating an infectious disease with a single value of $R_0$ is problematic, when the disease can, in fact have different reproduction numbers in various populations.