Quality-Quantity Trade-offs in Tests for Management of COVID-19-like Epidemics

TL;DR

This paper analyzes the trade-offs between test accuracy, cost, and delay in managing COVID-19-like epidemics, proposing optimal testing strategies combined with lockdowns to minimize peak infections and quarantine days.

Contribution

It introduces a framework for optimizing test strategies considering cost, delay, and epidemic dynamics on social networks, incorporating partial and complete lockdown effects.

Findings

Optimal test combinations reduce peak infections.

Rapid, cheaper tests enable broader testing coverage.

Lockdowns enhance epidemic control when combined with testing strategies.

Abstract

There are multiple testing methods to ascertain an infection in an individual and they vary in their performances, cost and delay. Unfortunately, better performing tests are sometimes costlier and time consuming and can only be done for a small fraction of the population. On the other hand, greater number of individuals can be tested using a cheaper, rapid test, but may only provide less reliable results. In this work, we studied the interplay between cost and delay of the tests as well the additional advantages offered by partial and complete lockdowns. To understand the influence of different test strategies, we implemented them on realistic random social networks with a COVID-19-like epidemic in progression. Specifically, we compared the performance of two tests mimicking the characteristics of popular tests implemented for COVID-19 detection. We present procedures and intuitive understanding to ascertain the optimum combination of the tests to minimize the peak infection as well as total quarantine days when the number of tests is constrained by a fixed total budget.