Digital PCR Applications in the SARS-CoV-2/COVID-19 Era: a Roadmap for Future Outbreaks

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global public health disaster. The current gold standard for the diagnosis of infected patients is real-time reverse transcription-quantitative PCR (RT-qPCR). As effective as this method may be, it is subject to false-negative and -positive results, affecting its precision, especially for the detection of low viral loads in samples. In contrast, digital PCR (dPCR), the third generation of PCR, has been shown to be more effective than the gold standard, RT-qPCR, in detecting low viral loads in samples. In this review article, we selected publications to show the broad-spectrum applications of dPCR, including the development of assays and reference standards, environmental monitoring, mutation detection, and clinical diagnosis of SARS-CoV-2, while comparing it analytically to the gold standard, RT-qPCR. In summary, it is evident that the specificity, sensitivity, reproducibility, and detection limits of RT-dPCR are generally unaffected by common factors that may affect RT-qPCR. As this is the first time that dPCR is being tested in an outbreak of such a magnitude, knowledge of its applications will help chart a course for future diagnosis and monitoring of infectious disease outbreaks. The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global public health disaster. The current gold standard for the diagnosis of infected patients is real-time reverse transcription-quantitative PCR (RT-qPCR).

Automated summary

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has created a global public health crisis. While RT-qPCR is the current gold standard for diagnosis, dPCR has shown to be more effective in detecting low viral loads. Understanding the applications of dPCR will help shape future diagnosis and monitoring of infectious disease outbreaks.