The current coronavirus disease 19 (COVID-19) outbreak has been declared to be a pandemic by the World Health Organization (WHO). It is evolving daily and has jeopardized life globally across social and economic fronts. One of the six key strategic objectives identified by the WHO to manage COVID-19 is to communicate critical information to all communities and prevent the spread of misinformation. We analyzed content on YouTube.com, a widely used web-based platform for medical and epidemiological information. Methods YouTube search results using two keywords were analyzed each in six languages-English, Arabic, Bengali, Dutch, Hindi, and Nigerian Pidgin on April 8, 2020. Forty videos in each of the six languages (i.e., a total of 240 videos) were included for analysis in the study. Two reviewers conducted independent analyses for each language. The inter-observer agreement was evaluated with the kappa coefficient (κ). Modified DISCERN index and Medical Information and Content Index (MICI) scores were used for the reliability of content presented in the videos and information quality assessment, respectively. Analysis of variance, Kruskal-Wallis, Mann-Whitney test, and chi-square tests were done appropriately for data analysis. A p-value of less than 0.05 was considered statistically significant. All calculations were performed using SPSS Statistics for Windows, Version 21.0 (IBM Corp, Armonk, NY).

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Background: Cardiac arrhythmia cannot be overlooked in patients with coronavirus disease 2019 (COVID-19) as it carries a great influence on the outcomes. Hence, this study aimed to build concrete evidence regarding the incidence of cardiac arrhythmia in patients with COVID-19. Methods: We performed a systematic search for trusted databases/search engines including PubMed, Scopus, Cochrane library and web of science. After screening, the relevant data were extracted and the incidences from the different included studies were pooled for meta-analysis. Results: Nine studies were finally included in our study consisting of 1445 patients. The results of meta-analysis showed that the incidence of arrhythmia in patients with COVID-19 was 19.7% with 95% confidence interval (CI) ranging from 11.7 to 27.6%. There was also a significant heterogeneity (I2 = 94.67%). Conclusion: Cardiac arrhythmias were highly frequent in patients with COVID-19 and observed in 19.7% of them. Appropriate monitoring by electrocardiogram with accurate and early identification of arrhythmias is important for better management and outcomes.

In this paper, we propose a relay selection method for cooperative communication systems (CCS) employing the QPSK modulation scheme. The relay nodes forward their reliability to the destination node, utilizing a quantized reliability-relaying (QRR) scheme. The reliability is divided into five different levels by the relay nodes, according to the loglikelihood ratio (LLR) value of the received signal from the source node. Then, a suitable symbol is forwarded to the destination node if the relay node is set as active. A relay node is set as active if the reliability of the received signal is beyond a certain threshold. We provide analysis of the LLR for QPSK and carry out numerical simulations comparing the bit error rate (BER) of the QRR method against regular decode-and-forward (DF) and the best relay selection algorithms. A channel estimation algorithm is utilized to evaluate the performance of the system, as well as calculations of the normalized mean squared error (NMSE) of the channels. The special case of a system employing BPSK is also investigated.