ABSTRACT
BackgroundThe SARS-CoV-2 Omicron variants BA.2.74, BA.2.75 and BA.2.76 have appeared recently in India and have already spread to over 40 countries. They have acquired additional mutations in their spike protein compared to BA.2, branching away on the SARS-CoV-2 phylogenetic tree. These added mutations, over and above those of the parental BA.2 variant, have raised concerns about the impact on viral pathogenicity, transmissibility, and immune evasion properties of the new variants. Material and MethodsA total of 990 RT-PCR positive SARS-CoV-2 samples, with a cycle threshold value (Ct) less than 25, were processed for SARS-CoV-2 whole genome sequencing between 3rd June 2022 to 7th August 2022. All corresponding demographic and clinical data were recorded and analyzed using Microsoft(R) Excel. ResultsOut of 990 samples sequenced, BA.2.75 (23.03%) was the predominant Omicron sublineage, followed by BA.2.38 (21.01%), BA.5 (9.70%), BA.2 (9.09%), BA.2.74 (8.89%) and BA.2.76 (5.56%). A total of 228 cases of BA.2.74, BA.2.75 and BA.2.76 were contacted by telephone, of which 215 (94.30%) were symptomatic with mild symptoms, and 13 (5.70%) had no symptoms. Fever (82.02%) was the most common symptom, followed by cough (49.12%), cold (35.97%), fatigue (27.19%), headache (21.05%) and myalgia (20.61%). Of the 228 cases, 195 (85.53%) cases recovered at home, and 33 (14.47%) required institutional quarantine. Recovery with conservative treatment was observed in 92.98% of cases, while 4.83% required additional oxygen therapy. Only 03 (1.32%) cases had poor outcomes resulting in death, and the remaining 225 (98.68%) had a good outcome. Among the 228 cases, 219 (96.05%) cases were vaccinated with COVID-19 vaccine; of these 72.60% had received both doses, 26.03% had also received the precautionary booster dose, while 1.37% were incompletely vaccinated with a single dose of vaccine. ConclusionThe current study indicates that the three BA.2 sublineages are causing mild disease in India. However, BA.2.75 has key mutations that are notable for accelerated growth and transmission and require close and effective monitoring.
Subject(s)
Headache , Fever , COVID-19 , Myalgia , FatigueABSTRACT
COVID-19 is one of the most dangerous viruses which caused a pandemic in human life, not only in terms of direct casualties but also regarding socio-economic impact. The outbreak quickly spread around the world. The 1st anniversary of the global Corona virus pandemic gets passed away in 2021, but still, no way to tell how long the pandemic will continue. After analyzing a report by WHO of covid-19, to minimize the rate of covid-19 transmission, our national government advised citizens to wear face masks. A model using deep learning and MobileNetV2 for face mask detection is presented. This method was trained and checked on the real-time dataset. There are 3,833 images in the Medical Masks Dataset, including 1918 images of people wearing no mask and 1915 images of people wearing masks. We adopted OpenCV to detect faces in real-time from a live stream captured with our webcam. With the aid of computer vision and deep learning, we hope to classify whether or not the person in the video stream is wearing a face mask. If the camera captures a face without a mask an Email notification will be sent out to the administrator and the system alarm will ring.