ABSTRACT
Real-time PCR is the gold standard test for the diagnosis of COVID-19. It is a nuclear-derived method for identifying the presence of genetic material of any pathogen, including virus. As per the Indian Council of Medical Research (ICMR), there are no reliable studies that prove a definitive direct correlation between the Ct value and infectiousness and severity of the disease by using epidemiological data, and also it does not change the course of treatment or disease management. The Ct value may differ depending on the test kit used or the testing machine. In the indistinct level of RT-PCR, many analytical research interventions would be necessary to explore separate mathematical algorithms for the accurate detection of viral plasma load with respect to various epidemiological, clinical, and age-related attributes. Scientifically, the RT-PCR mechanism is directly augmented with various epidemiological attributes. The present study formulates an RT-PCR data-driven model to project the significant changes in Ct value in association with different demographical, clinical, and epidemiological parameters. As per the model outputs, it was observed that there is a strong correlation between the threshold value (Ct) and the age-specific incidence of COVID(p < 0.01; odds 8.36) with respect to demographic characteristics of the patients. Travel history (traveled from abroad), BMI > 30 kg/mm3, high economy (Income >80000 INR per annum, and urban population are seen to have higher Ct value as compared to rural population. The summary of the results concludes that the Ct value showed a significant difference in elderly and comorbid patients. The demographic profile being a predisposing factor is necessary to substitute the RT-PCR test to derive the Ct value accurately.
