The Coronavirus Calendar (CoronaCal): a Simplified SARS-CoV-2 Test System for Sampling and Retrospective Analysis

BackgroundThe testing of saliva samples for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA has become a useful and common method to diagnose coronavirus disease 2019 (Covid-19). However, there are limited examples of serial testing with correlated clinical metadata, especially in the outpatient setting. MethodWe developed a method to collect serial saliva samples on ordinary white printer paper, which can be subsequently analyzed for the presence of SARS-CoV-2 RNA using established polymerase chain reaction (PCR) procedures. The collection systems consisted of a biological diary (CoronaCal) where subjects dab their saliva onto ovals printed onto paper. The dried samples are covered with a sticker that includes a symptom checklist to create a biological diary. Each sheet of letter paper can accommodate up to 14 serial samples. ResultsIn a pilot study, ten subjects used CoronaCals for durations of nine to 44 days. SARS-CoV-2 RNA was extracted and detected in CoronaCals from nine of nine people with either Covid-19 symptoms or exposure to someone with Covid-19, and in zero of one asymptomatic person. The CoronaCals were stored for up to 70 days at room temperature during collection and then frozen for up to four months before analysis, suggesting that SARS-CoV-2 RNA is stable once dried onto paper. Interestingly, the temporal pattern of symptoms was not well correlated with SARS-CoV-2 RNA in serial daily collections for up to 44 days. In addition, SARS-CoV-2 positivity was discontinuous over time in most cases but persisted for up to 24 days. ConclusionsWe conclude that sampling of saliva on simple paper CoronaCals may provide a useful method to study the natural history and epidemiology of Covid-19. The CoronaCal collection and testing method we developed is also easy to implement, inexpensive, non-invasive, and scalable. More broadly, the approach can be used to archive biological samples for retrospective analysis to deepen epidemiological understanding during viral disease outbreaks and to provide information about the natural history of emerging infections.