COVID-19 infection, and reinfection, and vaccine effectiveness against symptomatic infection among health care workers in the setting of omicron variant transmission in New Delhi, India.

Background: Surge of SARS CoV-2 infections ascribed to omicron variant began in December 2021 in New Delhi. We determined the infection and reinfection density in a cohort of health care workers (HCWs) along with vaccine effectiveness (VE) against symptomatic infection within omicron transmission period (considered from December 01, 2021 to February 25, 2022. Methods: This is an observational study from the All India Institute of Medical Sciences, New Delhi. Data were collected telephonically. Person-time at risk was counted from November 30, 2021 till date of infection/ reinfection, or date of interview. Comparison of clinical features and severity was done with previous pandemic periods. VE was estimated using test-negative case-control design [matched pairs (for age and sex)]. Vaccination status was compared and adjusted odds ratios (OR) were computed by conditional logistic regression. VE was estimated as (1-adjusted OR)X100-. Findings: 11474 HCWs participated in this study. The mean age was 36⋅2 (±10⋅7) years. Complete vaccination with two doses were reported by 9522 (83%) HCWs [8394 (88%) Covaxin and 1072 Covishield (11%)]. The incidence density of all infections and reinfection during the omicron transmission period was 34⋅8 [95% Confidence Interval (CI): 33⋅5-36⋅2] and 45⋅6 [95% CI: 42⋅9-48⋅5] per 10000 person days respectively. The infection was milder as compared to previous periods. VE was 52⋅5% (95% CI: 3⋅9-76⋅5, p = 0⋅036) for those who were tested within 14-60 days of receiving second dose and beyond this period (61-180 days), modest effect was observed. Interpretation: Almost one-fifth of HCWs were infected with SARS CoV-2 during omicron transmission period, with predominant mild spectrum of COVID-19 disease. Waning effects of vaccine protection were noted with increase in time intervals since vaccination. Funding: None.

Convolutional neural network based CT scan classification method for COVID-19 test validation.

Given the novel corona virus discovered in Wuhan, China, in December 2019, due to the high false-negative rate of RT-PCR and the time-consuming to obtain the results, research has proved that computed tomography (CT) has become an auxiliary One of the essential means of diagnosis and treatment of new corona virus pneumonia. Since few COVID-19 CT datasets are currently available, it is proposed to use conditional generative adversarial networks to enhance data to obtain CT datasets with more samples to reduce the risk of over fitting. In addition, a BIN residual block-based method is proposed. The improved U-Net network is used for image segmentation and then combined with multi-layer perception for classification prediction. By comparing with network models such as AlexNet and GoogleNet, it is concluded that the proposed BUF-Net network model has the best performance, reaching an accuracy rate of 93%. Using Grad-CAM technology to visualize the system's output can more intuitively illustrate the critical role of CT images in diagnosing COVID-19. Applying deep learning using the proposed techniques suggested by the above study in medical imaging can help radiologists achieve more effective diagnoses that is the main objective of the research. On the basis of the foregoing, this study proposes to employ CGAN technology to augment the restricted data set, integrate the residual block into the U-Net network, and combine multi-layer perception in order to construct new network architecture for COVID-19 detection using CT images. -19. Given the scarcity of COVID-19 CT datasets, it is proposed that conditional generative adversarial networks be used to augment data in order to obtain CT datasets with more samples and therefore lower the danger of overfitting.

Nutraceuticals in HIV and COVID-19-Related Neurological Complications: Opportunity to Use Extracellular Vesicles as Drug Delivery Modality.

People living with HIV/AIDS (PLWHA) are at an increased risk of severe and critical COVID-19 infection. There is a steady increase in neurological complications associated with COVID-19 infection, exacerbating HIV-associated neurocognitive disorders (HAND) in PLWHA. Nutraceuticals, such as phytochemicals from medicinal plants and dietary supplements, have been used as adjunct therapies for many disease conditions, including viral infections. Appropriate use of these adjunct therapies with antiviral proprieties may be beneficial in treating and/or prophylaxis of neurological complications associated with these co-infections. However, most of these nutraceuticals have poor bioavailability and cannot cross the blood-brain barrier (BBB). To overcome this challenge, extracellular vesicles (EVs), biological nanovesicles, can be used. Due to their intrinsic features of biocompatibility, stability, and their ability to cross BBB, as well as inherent homing capabilities, EVs hold immense promise for therapeutic drug delivery to the brain. Therefore, in this review, we summarize the potential role of different nutraceuticals in reducing HIV- and COVID-19-associated neurological complications and the use of EVs as nutraceutical/drug delivery vehicles to treat HIV, COVID-19, and other brain disorders.

SARS-CoV-2 Reinfection Rate and Estimated Effectiveness of the Inactivated Whole Virion Vaccine BBV152 Against Reinfection Among Health Care Workers in New Delhi, India.

Importance: A surge of COVID-19 occurred from March to June 2021, in New Delhi, India, linked to the B.1.617.2 (Delta) variant of SARS-CoV-2. COVID-19 vaccines were rolled out for health care workers (HCWs) starting in January 2021. Objective: To assess the incidence density of reinfection among a cohort of HCWs and estimate the effectiveness of the inactivated whole virion vaccine BBV152 against reinfection. Design, Setting, and Participants: This was a retrospective cohort study among HCWs working at a tertiary care center in New Delhi, India. Exposures: Vaccination with 0, 1, or 2 doses of BBV152. Main Outcomes and Measures: The HCWs were categorized as fully vaccinated (with 2 doses and ≥15 days after the second dose), partially vaccinated (with 1 dose or 2 doses with <15 days after the second dose), or unvaccinated. The incidence density of COVID-19 reinfection per 100 person-years was computed, and events from March 3, 2020, to June 18, 2021, were included for analysis. Unadjusted and adjusted hazard ratios (HRs) were estimated using a Cox proportional hazards model. Estimated vaccine effectiveness (1 - adjusted HR) was reported. Results: Among 15 244 HCWs who participated in the study, 4978 (32.7%) were diagnosed with COVID-19. The mean (SD) age was 36.6 (10.3) years, and 55.0% were male. The reinfection incidence density was 7.26 (95% CI: 6.09-8.66) per 100 person-years (124 HCWs [2.5%], total person follow-up period of 1696 person-years as time at risk). Fully vaccinated HCWs had lower risk of reinfection (HR, 0.14 [95% CI, 0.08-0.23]), symptomatic reinfection (HR, 0.13 [95% CI, 0.07-0.24]), and asymptomatic reinfection (HR, 0.16 [95% CI, 0.05-0.53]) compared with unvaccinated HCWs. Accordingly, among the 3 vaccine categories, reinfection was observed in 60 of 472 (12.7%) of unvaccinated (incidence density, 18.05 per 100 person-years; 95% CI, 14.02-23.25), 39 of 356 (11.0%) of partially vaccinated (incidence density 15.62 per 100 person-years; 95% CI, 11.42-21.38), and 17 of 1089 (1.6%) fully vaccinated (incidence density 2.18 per 100 person-years; 95% CI, 1.35-3.51) HCWs. The estimated effectiveness of BBV152 against reinfection was 86% (95% CI, 77%-92%); symptomatic reinfection, 87% (95% CI, 76%-93%); and asymptomatic reinfection, 84% (95% CI, 47%-95%) among fully vaccinated HCWs. Partial vaccination was not associated with reduced risk of reinfection. Conclusions and Relevance: These findings suggest that BBV152 was associated with protection against both symptomatic and asymptomatic reinfection in HCWs after a complete vaccination schedule, when the predominant circulating variant was B.1.617.2.

Hyperinflammation and Immune Response Generation in COVID-19.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) pandemic has affected millions of people worldwide. The pathophysiology of this virus is not very clearly known, thus, enormous efforts are being made by the scientific community to delineate its evading mechanism. In this review, we have summarized the hyperinflammation and humoral and cell-mediated immune response generated in human body after infection with the SARS-CoV-2 virus. The inflammatory response generated after infection by increased proinflammatory cytokines and chemokines, and complement proteins activation may likely contribute to disease severity. We also discussed the other factors that may affect immunity and could be important comorbidities in the disease severity and outcome.