Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV

Quantitative SARS-CoV-2 exposure assessment for workers in wastewater treatment plants using Monte-Carlo simulation

Several studies on COVID-19 pandemic have shown that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originating from human stool are detected in raw sewage for several days, leading to potential health risks for workers due to the production of bioaerosols and droplets during wastewater treatment process. In this study, data of SARS-CoV-2 concentrations in wastewater were gathered from literatures, and a quantitative microbial risk assessment with Monte Carlo simulation was used to estimate the daily probability of infection risk through exposure to viable infectious viral airborne particles of the workers during four seasons and under six environmental conditions. Inhalation of bioaerosols and direct ingestion of wastewater droplets were selected as exposure pathways. Spearman rank correlation coefficients were used for sensitivity analysis to identify the variables with the greatest influence on the infection risk probability. It was found that the daily probability of infection risk decreased with temperature (T) and relative humidity (RH) increase. The probability of direct droplet ingestion exposure pathway was higher than that of the bioaerosol inhalation pathway. The sensitivity analysis indicated that the most sensitive variable for both exposure pathways was the concentration of SARS-CoV-2 in stool. So, appropriate aeration systems, covering facilities, and effective ventilation are suggested to implement in wastewater treatment plants (WWTPs) to reduce emission concentration. Further to this, the exposure time (t) had a larger variance contribution than T and RH for the bioaerosol inhalation pathway. Implementing measures such as adding more work shifts, mandating personal protective equipment for all workers, and implementing coverage for treatment processes can significantly reduce the risk of infection among workers at WWTPs. These measures are particularly effective during environmental conditions with low temperatures and humidity levels.

Dose–Response Meta-Analysis of Corticosteroid Effects in SARS Outbreak: A Model for Risk Stratification and Screening Strategy for Osteonecrosis of Femoral Head Post-Corticosteroid Therapy for COVID-19

Corticosteroids (CS) have been used in the management regimens for COVID-19 disease to mitigate the cytokine storm and ill effects of the pulmonary inflammatory cascade. With the rampant use of CS, clinicians started reporting the occurrence of osteonecrosis of the femoral head (OFH). In this systematic review, we aim to analyze the literature and identify the definitive cumulative dose and duration of CS needed for the development of OFH based on the SARS model and generate a risk-based screening recommendation for OFH in convalescent COVID-19 patients to facilitate early identification and management. An electronic database search was conducted until December 2022 in PubMed, Web of Science, Embase, and CNKI (China Knowledge Resource Integrated Database). Studies involving CS therapy and osteonecrosis data in SARS patients were included. Three authors independently extracted the data from the included studies and a dose–response meta-analysis was performed for various doses and duration of CS utilized in the included studies. We selected 12 articles with 1728 patients in the analysis. The mean age was 33.41 (±4.93) years. The mean dosage of CS administered was 4.64 (±4.7) g which was administered for a mean duration of 29.91 (±12.3) days. The risk of osteonecrosis increases at pooled OR of 1.16 (95% CI 1.09–1.23, p < 0.001) per 2.0 g increase in the cumulative dose of CS usage. Similarly, the risk increases at pooled OR of 1.02 (95% CI 1.01–1.03, p < 0.001) per 5 days of increase in the cumulative duration of CS usage. A cumulative dosage of 4 g and a duration of 15 days were determined as the critical cut-off for the non-linear dose–response relationship observed. Appropriate and frequent screening of these individuals at regular intervals would help in the identification of the disease at an early stage in order to treat them appropriately.

Online Predictor Using Machine Learning to Predict Novel Coronavirus and Other Pathogenic Viruses

The problem of virus classification is always a subject of concern for virology or epidemiology over the decades. In this regard, a machine learning technique can be used to predict the novel coronavirus by considering its sequence. Thus, we are proposing a machine learning-based novel coronavirus prediction technique, called COVID-Predictor, where 1000 sequences of SARS-CoV-1, MERS-CoV, SARS-CoV-2, and other viruses are used to train a Naive Bayes classifier so that it can predict any unknown sequences of these viruses. The model has been validated using 10-fold cross-validation in comparison with other machine learning techniques. The results show the superiority of our predictor by achieving an average 99.7% accuracy on an unseen validation set of viruses. The same pre-trained model has been used to design a web-based application where sequences of unknown viruses can be uploaded to predict the novel coronavirus.

Strong humoral immune responses against SARS-CoV-2 Spike after BNT162b2 mRNA vaccination with a 16-week interval between doses

The standard regimen of the BNT162b2 mRNA vaccine for SARS-CoV-2 includes two doses administered three weeks apart. However, some public health authorities spaced these doses, raising questions about efficacy. We analyzed longitudinal humoral responses against the D614G strain and variants of concern for SARS-CoV-2 in a cohort of SARS-CoV-2-naive and previously infected individuals who received the BNT162b2 mRNA vaccine with sixteen weeks between doses. While administering a second dose to previously infected individuals did not significantly improve humoral responses, these responses significantly increased in naive individuals after a 16-week spaced second dose, achieving similar levels as in previously infected individuals. Comparing these responses to those elicited in individuals receiving a short (4-week) dose interval showed that a 16-week interval induced more robust responses among naive vaccinees. These findings suggest that a longer interval between vaccine doses does not compromise efficacy and may allow greater flexibility in vaccine administration.

Strategies for COVID-19 Epidemiological Surveillance in India: Overall Policies Till June 2021

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has gripped the entire world, almost paralysing the human race in its entirety. The virus rapidly transmits via human-to-human medium resulting in a massive increase of patients with COVID-19. In order to curb the spread of the disease, an immediate action of complete lockdown was implemented across the globe. India with a population of over 1.3 billion was not an exception and took the challenge to execute phase-wise lockdown, unlock and partial lockdown activities. In this study, we intend to summarise these different phases that the Government of India (GoI) imposed to fight against SARS-CoV-2 so that it can act as a reference guideline to help controlling future waves of COVID-19 and similar pandemic situations in India.