A randomized controlled pilot study of add-on therapy of CIM-MEG19 (standardized Andrographis paniculata formulation) in mild to moderate COVID-19.

Background: Traditional knowledge and scientific shreds of evidence strongly support the repurpose of Kalmegh (Andrographis paniculata, CIM-MEG19) as an alternate therapy for prophylactic management and treatment of severe acute respiratory syndrome coronavirus (SARS-CoV) and associated health disorders. Purpose: The study aimed to assess the efficacy and safety of the CIM-MEG19 (standardized A. paniculata extract formulation), a proprietary Ayurvedic medicine in the COVID-19 management, clinical recovery, and outcomes in terms of hospitalization days as well as any sign of severity due to drug-drug interaction between CIM-MEG19 TM and standard of care (SoC). Methods: A randomized, parallel-group, active-controlled interventional pilot clinical study was conducted. The Group-A subjects were assigned to CIM-MEG19 add-on to SoC treatment using modern medicine without antiviral drug whereas Group-B patients with SoC treatment using modern medicine and recommended antiviral drug for COVID-19 management. Eighty RTPCR (real-time polymerase chain reaction) positive and eligible COVID-19 patients of age >18 years, having mild or moderate severity, were enrolled. Results: Clinical improvement in reduction of symptoms showed significant (p<0.0001) results in the average days in subjects of group-A (Investigational intervention arm) compared to Group B (SoC). The RT-PCR investigation exhibited COVID negative for 50 % in CIM-MEG19 add-on and 47% in SoC treatment after 8-11 days. Similarly, biochemical investigations showed that CIM-MEG19 group-A had a significant (p ≤ 0.05) effect on C-Reactive Protein (CRP) and Interleukin-6 (IL-6) after 14 days of treatment. Additionally, improvement in D-Dimer, ESR, and LDH in CIM-MEG19 add-on therapy was also observed. Conclusions: The study demonstrated an excellent safety profile, declining the severity of the infection and halting the disease advancement/progression. CIM-Meg19 might be used as a potential natural drug for treating COVID-19.

Effect of an online mindfulness program on stress in Indian adults during COVID-19 pandemic: A randomized controlled preliminary study.

Background: The Indian population is suffering from a high prevalence of mental stress and the situation has been worsened by the COVID-19 pandemic. Mindfulness, which can also be conducted online, has been used as a stress-relieving therapy in the Western world. There is not much experience with mindfulness in the Indian population. The COVID-19 pandemic demands the development of alternative therapies which can reach out to the masses at a minimal cost, avoiding direct personal contact. The researchers wanted to explore the potential of mindfulness as a stress-relieving therapy. Aim: To note any improvement in perceived stress of the participants compared to the controls. Methods: Ninety apparently healthy adults were randomized into group M (all of whom participated in an online mindfulness program) and group C (all of whom attended placebo sessions), with 45 participants each. Final sample size was n = 42 (group M) and n = 38 (group C). The perceived stress was measured using the perceived stress scale before and after the program. Qualitative data was collected in the form of written responses to the question "Which aspect of mindfulness meditation appealed to you the most for stress relief?" and some themes were formed. Results: There was a significant decrease in perceived stress scale scores on completion of the program in group M. "Positive mental state" and "non-judgmental" were the most prominent emergent themes suggested by the participants, as per the qualitative data analysis. Conclusion: This preliminary study sees potential in an online mindfulness program as an alternative stress-relieving therapy. Further research is suggested to substantiate the results and optimize the implementation.

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).