Reporting adverse events of ChAdOx1 nCoV-19 coronavirus vaccine (Recombinant) among the vaccinated healthcare professionals: A cross-sectional survey.

Background & objectives: The safety of the ChAdOx1 nCoV-19 vaccine is a cause of concern for many who have been vaccinated. The people have multiple concerns and fear regarding the adverse events of the vaccine. Thus, this study was undertaken to establish the safety profile of ChAdOx1 nCoV-19 Corona Virus Vaccine (Recombinant) among the healthcare professionals. Methods: This was a descriptive cross-sectional survey. After taking clearance from the institutional ethics committee 1500 healthcare professionals, who had their vaccination in the past two weeks were selected. They were provided with an online survey proforma regarding adverse events following immunization (AEFIs) of COVID-19 vaccine developed using google forms with an informed consent form affixed to it. Results: A total of 1036 individuals participated in the study. The mean and median (inter quartile range) age of the participants was 37.7 ±11.25 and 35 (29-46) yr, respectively. Of these, 52.1 per cent were female, 29.3 per cent were doctors, 33.4 per cent were nurses and 9.5 per cent were paramedical staff. Forty six per cent participants experienced one or more minor AEFIs such as pain, tenderness, redness, etc. at the injection site. Fatigue (31.75%), generalized feeling of unwell (28.57%), muscle pain (23.16%) and fever (21.71%) were the most commonly reported systemic AEFIs followed by headache (20.07%), dizziness (10.03%) and joint pains (15.25%). Most of them experienced these AEFIs within 24 h of the first dose of administration. About 42 per cent of the participants took oral antipyretics/analgesics for managing the AEFIs. Interpretation & conclusions: ChAdOx1 nCoV-19 Corona Virus Vaccine was found to be associated with mild local and systemic AEFIs that were more common after the first dose as compared to the second dose. There adverse events could be dealt with oral over-the-counter medications, with no requirement of hospitalization.

Silver Nanoparticles Biosynthesis, Characterization, Antimicrobial Activities, Applications, Cytotoxicity and Safety Issues: An Updated Review.

Rapid advances in nanotechnology have led to its emergence as a tool for the development of green synthesized noble metal nanoparticles, especially silver nanoparticles (AgNPs), for applications in diverse fields such as human health, the environment and industry. The importance of AgNPs is because of their unique physicochemical and antimicrobial properties, with a myriad of activities that are applicable in various fields, including the pharmaceutical industry. Countries with high biodiversity require the collection and transformation of information about biological assets into processes, associations, methods and tools that must be combined with the sustainable utilization of biological diversity. Therefore, this review paper discusses the applicable studies of the biosynthesis of AgNPs and their antimicrobial activities towards microorganisms in different areas viz. medicine and agriculture. The confirmed antiviral properties of AgNPs promote their applicability for SARS-CoV-2 treatment, based on assimilating the virus' activities with those of similar viruses via in vivo studies. In this review, an insight into the cytotoxicity and safety issues of AgNPs, along with their future prospects, is also provided.

Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach.

In the aftermath of the COVID-19 pandemic, supply chains experienced an unprecedented challenge to fulfill consumers' demand. As a vital operational component, manual order picking operations are highly prone to infection spread among the workers, and thus, susceptible to interruption. This study revisits the well-known order batching problem by considering a new overlap objective that measures the time pickers work in close vicinity of each other and acts as a proxy of infection spread risk. For this purpose, a multi-objective optimization model and three multi-objective metaheuristics with an effective seeding procedure are proposed and are tested on the data obtained from a major US-based logistics company. Through extensive numerical experiments and comparison with the company's current practices, the results are discussed, and some managerial insights are offered. It is found that the picking capacity can have a determining impact on reducing the risk of infection spread through minimizing the picking overlap.