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IntroductionDue to the accelerated pace and quantum of scientific publication during the COVID-19 pandemic, a large number of articles on COVID-19 have been retracted. Pre-prints though not peer-reviewed offer the advantage of rapid dissemination of new findings. In this study, we aim to systematically compare the article characteristics, time to retraction, social media attention, citations, and reasons for retraction between retracted pre-print and peer-reviewed articles on COVID-19.MethodsWe utilized the Retraction Watch database to identify retracted articles on COVID-19 published from 1st January 2020 to 10th March 2022. The articles were reviewed and metadata such as article characteristics (type, category), time to retraction, reasons for retraction, and Altmetric Attention Score (AAS) and citation count were collected.ResultsWe identified 40 retracted pre-prints and 143 retracted peer-reviewed articles. The median (IQR) retraction time for pre-print and peer-reviewed articles was 29 (10-81.5) days and 139 (63-202) days (p = 0.0001). Pre-prints and peer-reviewed article had median (IQR) AAS of 26.5 (4-1155) and 8 (1-38.5), respectively (p = 0.0082). The median (IQR) citation count for pre-prints and peer-reviewed articles was 3 (0-14) and 3 (0-17), respectively (p = 0.5633). The AAS and citation counts were correlated for both pre-prints (r = 0.5200, p = 0.0006) and peer-reviewed articles(r = 0.5909, p = 0.0001). The commonest reason for retraction for pre-prints and peer-reviewed articles concerns about data and results.ConclusionThe increased adoption of pre-prints results in faster identification of erroneous articles compared to the traditional peer-review process.

In today's world, video games have become an integral part of our lives, even for adults. While gaming disorder is now recognized as a disease, the literature is still not extensive regarding various aspects of the obsessive playing of video games. Taking the Player-Unknown's Battlegrounds as an example, this article provides a medical student's perspective on the effects of excessive playing of video games and some positive aspects of video games, which are less talked about.

Objective This study was conducted to assess the traumatic impact of the second wave of coronavirus disease 2019 (COVID-19) pandemic on depression, anxiety, stress, sleep quality, mental well-being, and resilience among the general population of India. Methods An online cross-sectional survey was conducted in May-June, 2021 via Google Forms, which included adult individuals who were willing to participate in the study. The purposive and snowball sampling technique was used to ensure the principle of maximum diversity. Standardised tools [Depression Anxiety and Stress Scale (DASS), Pittsburgh Sleep Quality Index (PSQI), Impact of Event-Revised (IES-R), Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS), and the Brief Resilience Scale (BRS)] were used to collect data. Results A total of 1,109 responses were analysed for this study. Participants of different age groups (mean age: 32.98 ±14.72 years) and different sociodemographics were enrolled. The younger population group (18-34 years) was found to be the most affected among all the age groups. The findings revealed that 44.18% showed posttraumatic stress disorder (PTSD)-like symptoms. About 48.87%, 65.56%, and 22.09% of the participants had significant depression, anxiety, and stress symptoms respectively, and 11.27% had disturbed sleep patterns. Mental well-being was found to be disturbed for 74.75% of the study population, out of which only 4.15% showed high resilience capacity. Conclusion The associated collective psychological trauma mapped out by this paper is a pandemic in itself and needs to be addressed on a scale similar to the efforts being made to curb the physical symptoms of COVID-19.

A qualitative study comprising eight focus group discussions and two in-depth interviews were conducted to explore the social and behavioural changes in young adults during COVID pandemic. Common themes identified were changes in interpersonal and intrapersonal relationships, changes in health-related behaviour, lifestyle modifications and impact on academic and professional life.

Brief AbstractWe analysed SARS-CoV-2 surveillance and contact tracing data from Karnataka, India up to 21 July 2020. We estimated metrics of infectiousness and the tendency for superspreading (overdispersion), and evaluated potential determinants of infectiousness and symptomaticity in COVID-19 cases. Among 956 cases confirmed to be forward-traced, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases, suggesting significant heterogeneity in individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in underlying number of contacts. Secondary attack rate was 3.6% among 16715 close contacts. Transmission was higher when index case was aged >18 years, or was symptomatic (adjusted risk ratio, aRR 3.63), or was lab-confirmed ≥4 days after symptom onset (aRR 3.01). Probability of symptomatic infection increased with age, and symptomatic infectors were 8.16 times more likely to generate symptomatic secondaries. This could potentially cause a snowballing effect on infectiousness and clinical severity across transmission generations; further studies are suggested to confirm this. Mean serial interval was 5.4 days. Adding backward contact tracing and targeting control measures to curb super-spreading may be prudent. Due to low symptomaticity and infectivity, interventions aimed at children might have a relatively small impact on reducing transmission.Structured AbstractBackgroundIndia has experienced the second largest outbreak of COVID-19 globally, yet there is a paucity of studies analysing contact tracing data in the region. Such studies can elucidate essential transmission metrics which can help optimize disease control policies.MethodsWe analysed contact tracing data collected under the Integrated Disease Surveillance Programme from Karnataka, India between 9 March and 21 July 2020. We estimated metrics of disease transmission including the reproduction number (R), overdispersion (k), secondary attack rate (SAR), and serial interval. R and k were jointly estimated using a Bayesian Markov Chain Monte Carlo approach. We evaluated the effect of age and other factors on the risk of transmitting the infection, probability of asymptomatic infection, and mortality due to COVID-19.FindingsUp to 21 July, we found 111 index cases that crossed the super-spreading threshold of ≥8 secondary cases. R and k were most reliably estimated at R 0.75 (95% CI, 0.62-0.91) and k 0.12 (0.11-0.15) for confirmed traced cases (n=956); and R 0.91 (0.72-1.15) and k 0.22 (0.17-0.27) from the three largest clusters (n=394). Among 956 confirmed traced cases, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases. Among 16715 contacts, overall SAR was 3.6% (3.4-3.9) and symptomatic cases were more infectious than asymptomatic cases (SAR 7.7% vs 2.0%; aRR 3.63 [3.04-4.34]). As compared to infectors aged 19-44 years, children were less infectious (aRR 0.21 [0.07-0.66] for 0-5 years and 0.47 [0.32-0.68] for 6-18 years). Infectors who were confirmed ≥4 days after symptom onset were associated with higher infectiousness (aRR 3.01 [2.11-4.31]). Probability of symptomatic infection increased with age, and symptomatic infectors were 8.16 (3.29-20.24) times more likely to generate symptomatic secondaries. Serial interval had a mean of 5.4 (4.4-6.4) days with a Weibull distribution. Overall case fatality rate was 2.5% (2.4-2.7) which increased with age.ConclusionWe found significant heterogeneity in the individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in the underlying number of contacts. To strengthen contact tracing in over-dispersed outbreaks, testing and tracing delays should be minimised, retrospective contact tracing should be considered, and contact tracing performance metrics should be utilised. Targeted measures to reduce potential superspreading events should be implemented. Interventions aimed at children might have a relatively small impact on reducing SARS-CoV-2 transmission owing to their low symptomaticity and infectivity. There is some evidence that symptomatic cases produce secondary cases that are more likely to be symptomatic themselves which may potentially cause a snowballing effect on infectiousness and clinical severity across transmission generations; further studies are needed to confirm this finding.FundingGiridhara R Babu is funded by an Intermediate Fellowship by the Wellcome Trust DBT India Alliance (Clinical and Public Health Research Fellowship); grant number: IA/CPHI/14/1/501499.

Case fatality rate (CFR) and doubling time are important characteristics of any epidemic. For coronavirus disease 2019 (COVID-19), wide variations in the CFR and doubling time have been noted among various countries. Early in the epidemic, CFR calculations involving all patients as denominator do not account for the hospitalised patients who are ill and will die in the future. Hence, we calculated cumulative CFR (cCFR) using only patients whose final clinical outcomes were known at a certain time point. We also estimated the daily average doubling time. Calculating CFR using this method leads to temporal stability in the fatality rates, the cCFR stabilises at different values for different countries. The possible reasons for this are an improved outcome rate by the end of the epidemic and a wider testing strategy. The United States, France, Turkey and China had high cCFR at the start due to low outcome rate. By 22 April, Germany, China and South Korea had a low cCFR. China and South Korea controlled the epidemic and achieved high doubling times. The doubling time in Russia did not cross 10 days during the study period.

After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the disease in the country. This study involves assessing how the disease affected the population in the initial days of the epidemic. Data was collected from government-controlled and crowdsourced websites and analyzed. Studying age and sex parameters of 413 Indian COVID-19 patients, the median age of the affected individuals was found to be 36 years (IQR, 25-54) with 20-39 years males being the most affected group. The number of affected males (66.34%) was more than that of the females (33.66%). Using Susceptible-Infected-Removed (SIR) model, the range of contact rate (β) of India was calculated and the role of public health interventions was assessed. If current contact rate continues, India may have 5583 to 13785 active cases at the end of 21 days lockdown.Article Summary LineThe study gives the epidemiological characteristics of the SARS-CoV-2 epidemic in India, where unlike other countries, the 20-39 years males are most affected, and the SIR model predicts the probable number of cases of COVID-19 by the end of the 21 days lockdown in the country, which will help to develop appropriate public health interventions to control the COVID-19 epidemic.

Background: After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the virus in the country. This included restricted testing, isolation, contact tracing and quarantine, and enforcement of a nation-wide lockdown starting 25 March 2020. The objectives of this study were to i) describe the age, gender distribution, and mortality among COVID-19 patients identified till 14 April 2020 and predict the range of contact rate; and ii) predict the number of COVID-19 infections after 40 days of lockdown. Methods: We used a cross-sectional descriptive design for the first objective and a susceptible-infected-removed model for in silico predictions. We collected data from government-controlled and crowdsourced websites. Results: Studying age and gender parameters of 1161 Indian COVID-19 patients, the median age was 38 years (IQR, 27-52) with 20-39 year-old males being the most affected group. The number of affected patients were 854 (73.6%) men and 307 (26.4%) women. If the current contact rate continues (0.25-27), India may have 110460 to 220575 infected persons at the end of 40 days lockdown. Conclusion: The disease is majorly affecting a younger age group in India. Interventions have been helpful in preventing the worst-case scenario in India but will be unable to prevent the spike in the number of cases.

The Hon'ble Supreme Court of India, on 9th March 2018 legalized Passive Euthanasia by means of the withdrawal of life-support to patients in a permanent vegetative state. The decision was made as part of the verdict in a case involving Aruna Shanbaug, who had been in a Persistent Vegetative State (PVS) until her death in 2015. On the other side, events seemingly inexplicable, outside the range of medical precedents, the Medical Miracles make a question mark on this legalization. A study was conducted taking the views of 96 MBBS students on it based on a questionnaire. There was mixed response from the students and the expectations of some miraculous outcome (in treatments) have been expressed that imposes a still persisting doubt in justified acceptability of legalization of Euthanasia in India.