Effectiveness of BBV152/Covaxin and AZD1222/Covishield vaccines against severe COVID-19 and B.1.617.2/Delta variant in India, 2021: a multi-centric hospital-based case-control study.

OBJECTIVES: India introduced BBV152/Covaxin and AZD1222/Covishield vaccines in January 2021. We estimated the effectiveness of these vaccines against severe COVID-19 among individuals aged ≥45 years. METHODS: We did a multi-centric, hospital-based, case-control study between May and July 2021. Cases were severe COVID-19 patients, and controls were COVID-19 negative individuals from 11 hospitals. Vaccine effectiveness (VE) was estimated for complete (2 doses ≥ 14 days) and partial (1 dose ≥ 21 days) vaccination; interval between two vaccine doses and vaccination against the Delta variant. We used the random effects logistic regression model to calculate the adjusted odds ratios (aOR) with a 95% confidence interval (CI) after adjusting for relevant known confounders. RESULTS: We enrolled 1143 cases and 2541 control patients. The VE of complete vaccination was 85% (95% CI: 79-89%) with AZD1222/Covishield and 71% (95% CI: 57-81%) with BBV152/Covaxin. The VE was highest for 6-8 weeks between two doses of AZD1222/Covishield (94%, 95% CI: 86-97%) and BBV152/Covaxin (93%, 95% CI: 34-99%). The VE estimates were similar against the Delta strain and sub-lineages. CONCLUSION: BBV152/Covaxin and AZD1222/Covishield were effective against severe COVID-19 among the Indian population during the period of dominance of the highly transmissible Delta variant in the second wave of the pandemic. An escalation of two-dose coverage with COVID-19 vaccines is critical to reduce severe COVID-19 and further mitigate the pandemic in the country.

Modulation of neutrophil (dys)function by Ayurvedic herbs and its potential influence on SARS-CoV-2 infection.

For centuries, traditional medicines of Ayurveda have been in use to manage infectious and non-infectious diseases. The key embodiment of traditional medicines is the holistic system of approach in the management of human diseases. SARS-CoV-2 (COVID-19) infection is an ongoing pandemic, which has emerged as the major health threat worldwide and is causing significant stress, morbidity and mortality. Studies from the individuals with SARS-CoV-2 infection have shown significant immune dysregulation and cytokine overproduction. Neutrophilia and neutrophil to lymphocyte ratio has been correlated to poor outcome due to the disease. Neutrophils, component of innate immune system, upon stimulation expel DNA along with histones and granular proteins to form extracellular traps (NETs). Although, these DNA lattices possess beneficial activity in trapping and eliminating pathogens, NETs may also cause adverse effects by inducing immunothrombosis and tissue damage in diseases including Type 2 Diabetes and atherosclerosis. Tissues of SARS-CoV-2 infected subjects showed microthrombi with neutrophil-platelet infiltration and serum showed elevated NETs components, suggesting large involvement and uncontrolled activation of neutrophils leading to pathogenesis and associated organ damage. Hence, traditional Ayurvedic herbs exhibiting anti-inflammatory and antioxidant properties may act in a manner that might prove beneficial in targeting over-functioning of neutrophils and there by promoting normal immune homeostasis. In the present manuscript, we have reviewed and discussed pathological importance of NETs formation in SARS-CoV-2 infections and discuss how various Ayurvedic herbs can be explored to modulate neutrophil function and inhibit NETs formation in the context of a) anti-microbial activity to enhance neutrophil function, b) immunomodulatory effects to maintain neutrophil mediated immune homeostasis and c) to inhibit NETs mediated thrombosis.

CAD systems for automatic detection and classification of COVID-19 in nano CT lung image by using machine learning technique

The WHO has declared Human Coronavirus (HCoV) ongoing outbreak to be a global public health emergency. Corona virus (HCoV) was reported two months ago in Wuhan, China. Health care systems over the world get into a chaotic mode due to limited capacity and a hectic increase of suspected coronavirus cases. The one thing that everybody is trying to do is to reduce the effect of cause created for a patient. This study will show how Machine Learning technique can be used for classifying the infected and healthy lung using the nano scaling imaging technique of computed tomography (CT) lung scans. Pre-processing is used to reduce the effect of intensity variations and for noise removal between CT slices. Then thresholding and other morphological operation is used to separately isolate the background of the CT lung scan. Each dataset that we take undergoes a texture-based feature extraction method in which it uses GLCM along with a wrapper method for optimization. The obtained features are classified using a Deep convolutional neural network, which will classify in several layers. By giving our input of scan images it will train in an efficient manner and gives us an accuracy of 99%.