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Studies focusing on the safety and common side effects of vaccines play a crucial role in enhancing public acceptance of vaccination. Research is scarce regarding the usage of COVID-19 vaccines and the side effects experienced by health professions students in India and other countries. This study aimed to document self-reported side effects associated with COVID-19 vaccination among medical and dental students of six medical and dental colleges and teaching hospitals in four states (Tamil Nadu, Madhya Pradesh, Gujarat, and West Bengal) of India. A cross-sectional survey using purposive sampling of medical and dental students was conducted from 26 April to 26 May 2021. Data was collected using a Google Forms questionnaire capturing information regarding receiving COVID-19 vaccines, side effects and symptoms, onset and duration of symptoms, use of treatment to alleviate symptoms, awareness of haematologic risks associated with vaccination, and side effects from previous (non-COVID-19) vaccinations. The majority (94.5%) of participants received both doses of the Covishield/AstraZeneca COVID-19 vaccine. Among participants ( n  = 492), 45.3% ( n  = 223) reported one or more side effects. The most frequently reported side effects were soreness of the injected arm (80.3%), tiredness (78.5%), fever (71.3%), headache (64.1%), and hypersomnia (58.7%). The two most common severe symptoms were fever (14.8%) and headache (13%). Most side effects appeared on the day of vaccination: soreness of the injection site (57%), fever (43.1%), and tiredness (42.6%). Most reported symptoms persisted for one to three days-soreness of the injection site (53%), fever (47.1%), and headache (42.6%). Logistic regression showed that women were almost 85% less likely to report side effects. The study's findings corroborate the safety of the Covishield/AstraZeneca vaccine's first dose, evidenced by the relatively minor and transient nature of the side effects. However, the study underscores the necessity for ongoing research to assess the long-term impacts of COVID-19 vaccines, especially in the context of booster doses, thereby contributing to the global understanding of vaccine safety and efficacy., Competing Interests: Russell Kabir is an Academic Editor for PeerJ. The other authors declare that they have no competing interests., (©2024 Majumder et al.)

Background: Several countries adopted lockdown to slowdown the exponential transmission of the coronavirus disease (COVID-19) epidemic. Disease transmission models and the epidemic forecasts at the national level steer the policy to implement appropriate intervention strategies and budgeting. However, it is critical to design a data-driven reliable model for nowcasting for smaller populations, in particular metro cities., Objective: The aim of this study is to analyze the transition of the epidemic from subexponential to exponential transmission in the Chennai metro zone and to analyze the probability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) secondary infections while availing the public transport systems in the city., Methods: A single geographical zone "Chennai-Metro-Merge" was constructed by combining Chennai District with three bordering districts. Subexponential and exponential models were developed to analyze and predict the progression of the COVID-19 epidemic. Probabilistic models were applied to assess the probability of secondary infections while availing public transport after the release of the lockdown., Results: The model predicted that transition from subexponential to exponential transmission occurs around the eighth week after the reporting of a cluster of cases. The probability of secondary infections with a single index case in an enclosure of the city bus, the suburban train general coach, and the ladies coach was found to be 0.192, 0.074, and 0.114, respectively., Conclusions: Nowcasting at the early stage of the epidemic predicts the probable time point of the exponential transmission and alerts the public health system. After the lockdown release, public transportation will be the major source of SARS-CoV-2 transmission in metro cities, and appropriate strategies based on nowcasting are needed., (©Kamalanand Krishnamurthy, Bakiya Ambikapathy, Ashwani Kumar, Lourduraj De Britto. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 18.09.2020.)

Background: The World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and predicting the effects of lockdown on future COVID-19 cases with a specific focus on India., Objective: The objective of this work was to develop and validate a mathematical model and to assess the impact of various lockdown scenarios on COVID-19 transmission in India., Methods: A model consisting of a framework of ordinary differential equations was developed by incorporating the actual reported cases in 14 countries. After validation, the model was applied to predict COVID-19 transmission in India for different intervention scenarios in terms of lockdown for 4, 14, 21, 42, and 60 days. We also assessed the situations of enhanced exposure due to aggregation of individuals in transit stations and shopping malls before the lockdown., Results: The developed model is efficient in predicting the number of COVID-19 cases compared to the actual reported cases in 14 countries. For India, the model predicted marked reductions in cases for the intervention periods of 14 and 21 days of lockdown and significant reduction for 42 days of lockdown. Such intervention exceeding 42 days does not result in measurable improvement. Finally, for the scenario of "panic shopping" or situations where there is a sudden increase in the factors leading to higher exposure to infection, the model predicted an exponential transmission, resulting in failure of the considered intervention strategy., Conclusions: Implementation of a strict lockdown for a period of at least 21 days is expected to reduce the transmission of COVID-19. However, a further extension of up to 42 days is required to significantly reduce the transmission of COVID-19 in India. Any relaxation in the lockdown may lead to exponential transmission, resulting in a heavy burden on the health care system in the country., (©Bakiya Ambikapathy, Kamalanand Krishnamurthy. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 07.05.2020.)

Ten bacterial strains that utilize cyanide (CN) as a nitrogen source were isolated from cassava factory wastewater after enrichment in a liquid media containing sodium cyanide (1 mM) and glucose (0.2% w/v). The strains could tolerate and grow in cyanide concentrations of up to 5 mM. Increased cyanide levels in the media caused an extension of lag phase in the bacterial growth indicating that they need some period of acclimatisation. The rate of cyanide removal by the strains depends on the initial cyanide and glucose concentrations. When initial cyanide and glucose concentrations were increased up to 5 mM, cyanide removal rate increased up to 63 and 61 per cent by Bacillus pumilus and Pseudomonas putida. Metabolic products such as ammonia and formate were detected in culture supernatants, suggesting a direct hydrolytic pathway without an intermediate formamide. The study clearly demonstrates the potential of aerobic treatment with cyanide degrading bacteria for cyanide removal in cassava factory wastewaters.