Evaluation of the number of undiagnosed infected in an outbreak using source of infection measurements

TL;DR

This paper proposes a method to estimate the number of undiagnosed infected individuals during outbreaks by analyzing the relationship between diagnosed cases and known sources of infection, providing a more accurate assessment of epidemic spread.

Contribution

It demonstrates that the fraction of diagnosed infected is approximately equal to the fraction with known sources across common epidemic models, enabling better estimation of total infections.

Findings

The diagnosed-to-total infected ratio approximates the known-source-to-diagnosed ratio.

This relationship holds across exponential and most epidemic models.

Applied to SARS-CoV-2, it estimates the true infection numbers in various countries.

Abstract

In times of outbreaks, an essential requirement for better monitoring is the evaluation of the number of undiagnosed infected individuals. An accurate estimate of this fraction is crucial for the assessment of the situation and the establishment of protective measures. In most current studies using epidemics models, the total number of infected is either approximated by the number of diagnosed individuals or is dependent on the model parameters and assumptions, which are often debated. We here study the relationship between the fraction of diagnosed infected out of all infected, and the fraction of infected with known contaminator out of all diagnosed infected. We show that those two are approximately the same in exponential models and across most models currently used in the study of epidemics, independently of the model parameters. As an application, we compute an estimate of the effective number of infected by the SARS-CoV-2 virus in various countries.