A workable strategy for COVID-19 testing: stratified periodic testing rather than universal random testing

Abstract

This paper argues for the regular testing of people in groups that are more likely to be exposed to SARS-CoV-2, to reduce the spread of COVID-19 and resume economic activity. We call this ‘stratified periodic testing’. It is ‘stratified’ as it is based on at-risk groups, and ‘periodic’ as everyone in the group is tested at regular intervals. We argue that this is a better use of scarce testing resources than ‘universal random testing’, as has been recently discussed globally. We find that, under reasonable assumptions and allowing for false negative results 30 per cent of the time, 17 per cent of a subgroup would need to be tested each day to lower the effective reproduction number R from 2.5 to 0.75, under stratified periodic testing. Using the same assumptions the universal random testing rate would need to be 27 per cent (as opposed to 7 per cent as argued by Romer (2020b)). We obtain this rate of testing using a corrected method for calculating the impact of an infectious person on others, and allowing for asymptomatic cases. We also find that the effect of one day’s delay between testing positive and self-isolating is similar to having a test that is 30 per cent less accurate.

The challenges of containing SARS-CoV-2 via test-trace-and-isolate

“…In contrast, unspecific symptom sets will require a high number of tests, especially in seasons where other respiratory conditions are prominent (currently, the fraction of SARS-CoV-2 cases among all influenza-like cases is less than 4% 44 ). Random testing on a population level has the lowest positive rate in the regime of low prevalence that we focus on 41 , 45 , but could be used in a targeted manner, e.g., screening of healthcare workers, highly vulnerable populations 10 , 46 or those living in the vicinity of localized outbreaks. We conclude that contact-tracing-based testing and highly specific symptoms-based testing should receive the highest priority, with the remaining test capacity used on less specific symptoms-based testing and random screening in particular settings.…”

Assessing population-sampling strategies for reducing the COVID-19 incidence

“…In [ 4 ], the authors claim that sampling strategies must be focused on target groups to increase the effectiveness of the sampling policies; these may be an age group [ 14 , 36 ] or a high-risk group such as those of people in nursing homes, where both residents and staff are in close contact [ 8 , 12 ]. According to our experiments, these policies may contribute to reducing the incidence within certain collectives, but to reduce the overall incidence it is necessary to continue testing the population from other collectives.…”

Effectiveness of Testing and Contact-Tracing to Counter COVID-19 Pandemic: Designed Experiments of Agent-Based Simulation

“…It is argued that contact tracing and the delay between symptom onset and case isolation are critical factors to reduce the spread of disease [ 11 , 12 ]. Studies in [ 13 ] show the effectiveness of stratified testing where people in groups that are more likely to be exposed to the virus get tested regularly. One distinct approach about contact tracing is proposed in [ 14 ], where bidirectional contact tracing is proposed.…”