Ultimate COVID-19 Detection Protocol Based on Saliva Sampling and qRT-PCR with Risk Probability Assessment


Won J., Kazan H. H., Kwon J., Park M., ERGÜN M. A., ÖZCAN KABASAKAL S., ...Daha Fazla

EXPERIMENTAL NEUROBIOLOGY, cilt.30, sa.1, ss.13-31, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 30 Sayı: 1
  • Basım Tarihi: 2021
  • Doi Numarası: 10.5607/en20063
  • Dergi Adı: EXPERIMENTAL NEUROBIOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE
  • Sayfa Sayıları: ss.13-31
  • Gazi Üniversitesi Adresli: Evet

Özet

In the era of COVID-19 outbreak, various efforts are undertaken to develop a quick, easy, inexpensive, and accurate way for diagnosis. Although many commercial diagnostic kits are available, detailed scientific evaluation is lacking, making the public vulnerable to fear of false-positive results. Moreover, current tissue sampling method from respiratory tract requires personal contact of medical staff with a potential asymptomatic SARS-COV-2 carrier and calls for safe and less invasive sampling method. Here, we have developed a convenient detection protocol for SARS-COV-2 based on a non-invasive saliva self-sampling method by extending our previous studies on development of a laboratory-safe and low-cost detection protocol based on qRT-PCR. We tested and compared various self-sampling methods of self-pharyngeal swab and self-saliva sampling from non-carrier volunteers. We found that the self-saliva sampling procedure gave expected negative results from all of the non-carrier volunteers within 2 hours, indicating cost-effectiveness, speed and reliability of the saliva-based method. For an automated assessment of the sampling quality and degree of positivity for COVID-19, we developed scalable formulae based on a logistic classification model using both cycle threshold and melting temperature from the qRT-PCR results. Our newly developed protocol will allow easy sampling and spatial-separation between patient and experimenter for guaranteed safety. Furthermore, our newly established risk assessment formula can be applied to a large-scale diagnosis in health institutions and agencies around the world.