Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model.

Keisuke Ejima,Takaji Wakita,Yasuhisa Fujita,Shoya Iwanami,Kwang Su Kim,Roger S Zoh,Taiga Miyazaki,Kazuyuki Aihara,Shingo Iwami,Ming Li

doi:10.1098/rsif.2020.0947

Abstract

Viral tests including polymerase chain reaction (PCR) tests are recommended to diagnose COVID-19 infection during the acute phase of infection. A test should have high sensitivity; however, the sensitivity of the PCR test is highly influenced by viral load, which changes over time. Because it is difficult to collect data before the onset of symptoms, the current literature on the sensitivity of the PCR test before symptom onset is limited. In this study, we used a viral dynamics model to track the probability of failing to detect a case of PCR testing over time, including the presymptomatic period. The model was parametrized by using longitudinal viral load data collected from 30 hospitalized patients. The probability of failing to detect a case decreased toward symptom onset, and the lowest probability was observed 2 days after symptom onset and increased afterwards. The probability on the day of symptom onset was 1.0% (95% CI: 0.5 to 1.9) and that 2 days before symptom onset was 60.2% (95% CI: 57.1 to 63.2). Our study suggests that the diagnosis of COVID-19 by PCR testing should be done carefully, especially when the test is performed before or way after symptom onset. Further study is needed of patient groups with potentially different viral dynamics, such as asymptomatic cases.

Highlights

In persons with signs or symptoms consistent with COVID-19, or with a high likelihood of exposure, viral testing combined with other tests (e.g. X-ray) is recommended for the diagnosis of acute infection [1]
polymerase chain reaction (PCR) tests for SARS-CoV-2 vary according to the sampling process used, the specimen type, the collection kit, and different target and detection limits [6,7,8]
Using the parametrized viral dynamics model, we computed the viral-load distribution over time with days since symptom onset as the time scale

Summary

Introduction

In persons with signs or symptoms consistent with COVID-19, or with a high likelihood of exposure (e.g. history of close contact with a confirmed case, travel history to an epicentre), viral testing combined with other tests (e.g. X-ray) is recommended for the diagnosis of acute infection [1]. Viral tests (such as the polymerase chain reaction (PCR) test) look for the presence of SARS-CoV-2, the causative virus of COVID-19. PCR tests for SARS-CoV-2 vary according to the sampling process used (i.e. sampled by patients or by healthcare workers [3]), the specimen type (upper and lower respiratory tract, saliva, blood, stool [4,5]), the collection kit, and different target and detection limits [6,7,8]. Test results can differ among runs, laboratories and PCR assays. It is still under debate which specimen type is best. Saliva samples can be self-collected, which will mitigate the risk of infection of healthcare workers and which is helpful for mass screening [9,10,11,12]. The viral load in nasal samples collected by patients was reported to be not as high as that in nasopharyngeal swabs collected by health practitioners, which yields lower sensitivity of nasal samples collected by patients [3]

Methods

Results

Conclusion