Flipped classroom: How higher education institutions (HEIs) of Bangladesh could move forward during COVID-19 pandemic.

Due to COVID-19 pandemic, Bangladesh along with most of the developing countries is facing unexpected impediments towards functioning their regular activities. Most importantly, schools at all levels and Higher Educational Institutions (HEIs) have been completely shut down since March 26, 2020 that directly obliged stakeholders (Ministry of Education, institutes authorities, parents and other relevant bodies) to adopt online education. Due to having very less experience, in many cases no experience at all, of conducting teaching and learning wholly online by HEIs of Bangladesh, myriad challenges have been encountered by teachers and students. In order to find out a viable technique for dealing with these challenges, this paper addresses two research questions: What are the available open Source technologies that could be used as an alternative of paid LMS system for any developing countries during this COVID-19 pandemic? and Is exiting flipped classroom technique suitable for continuing teaching and learning during COVID-19 pandemic? In an effort to solve the above mentioned questions, a case study method was adopted. The findings of this study propose a pathway (framework) through which the HEIs of developing countries will be able to continue teaching and learning without investing money and organizing training during this COVID-19 pandemic and similar other emergency situations. This strategy provides a simple but reliable emergency means which is based on flipped classroom theory. The HEIs of Bangladesh particularly, and other developing countries generally will be benefited from this proposed framework while they do not have established means to carry their teaching and learning. This paper lastly addresses a few limitations of this framework and provides guidelines to the policymakers on how to incorporate it into the HEIs during this emergency context.

A Delphi-Based Consensus Statement: Recommendation for Physiotherapy Management and Rehabilitation of People Living with Long COVID in Bangladesh (preprint)

Background: A Delphi-Based Consensus Statement: Recommendation for Physiotherapy Management and Rehabilitation of people living with Long COVID in Bangladesh Background: Covid-19 is a new and deadly virus with global consequences with special vulnerabilities in Bangladesh. The World Health Organization confirmed 22,451,122,614 cases and 4,627,540 deaths, worldwide (13th September 2021). In the United Kingdom, 1.5% of the estimated population of 970,000, suffers from Long COVID. Physiotherapy plays a vital role both in decreasing the number of deaths during the acute stage and improving function for patients across the spectrum of severity in the acute, sub-acute, and long-term context. Objectives: This Delphi-Based Consensus, provides recommendations for physiotherapy management and rehabilitation of people living with Long COVID. It includes recommendations for physiotherapy management for acute and subacute respiratory complications, a specific prescriptive exercise guideline for fatigue and musculoskeletal dysfunction and for improving psychological outcomes through combination of both counseling and rehabilitation. Methods: A team of 8 national and 6 international experts working in different disciplines were provided with studies on physiotherapy interventions in Long COVID-19 and were asked to provide treatment opinions based on the current literature for musculoskeletal, neurorehabilitation, respiratory, cardiac and psychological health domains. Statements were ranked and presented with individual opinions measured on a 10-point Likert Scale. The mean scores for each intervention were calculated and a manuscript with recommended physiotherapy interventions was prepared based on currently available evidence as presented and agreed upon by expert consensus. Findings: Experts recommended the following interventions based on mean agreement scores: diaphragmatic breathing (Mean = 7.5), thoracic expansion (with shoulder elevation) (Mean =8.5) and expiratory muscle training (Mean=6.3) for respiratory rehabilitation. Mild to moderate graded exercise (Mean= 7.7) was suggested for recovery from fatigue and McKenzie directional preference exercises for low back pain (Mean= 8.6), neck pain (Mean =7.9) and knee pain (Mean =8.3). Additionally, communicative and educative strategies were recommended for the rehabilitation of COVID-19. Conclusion: This consensus is structured according to the expert opinions of medical and rehabilitation professionals and based on current literature to recommend a series of rehabilitation interventions for physiotherapy professionals to manage Long COVID cases.Funding: This research has not been funded by any other external organization nor received any grants from commercial or not-for-profit organizations.Declaration of Interests: None declared.Ethics Approval Statement: Ethical permission was obtained from the Centre for the Rehabilitation of the Paralysed (CRP) ethics committee. The reference number CRP-R&E-0401-337.Trial Registration: Trial registration from the WHO Clinical trial registry platform, the reference number CTRI/2020/10/028179.

Evaluation of the performance of the COVID-19 rapid antigen tests in a tertiary level hospital in Bangladesh. (preprint)

Background: While the COVID-19 pandemic is a worldwide crisis, tests with high sensitivity and specificity are essential for identifying and managing COVID-19 patients. Globally, several rapid antigen tests RATs for COVID-19 have been developed, but their clinical efficacy has not been well established. This study aimed to evaluate the performance of several rapid antigen tests (RATs) to diagnose SARS-CoV-2 infection. Methods: : This prospective observational study was conducted at Shaheed Suhrawardy Medical College hospital from February 2021 to April 2021 in Dhaka, Bangladesh. This study included the patients admitted in this hospital at the COVID-19 isolation unit or referred from the triage facility of the outdoor department of this hospital suspected as COVID-19 case. Two nasopharyngeal samples were collected simultaneously. one sample was used on the spot for the RAT. The other was sent to the adjacent Shaheed Suhrawardy Medical College COVID-19 RT-PCR laboratory for real-time reverse transcription-polymerase chain reaction (qRT-PCR). The performance of the RAT was evaluated using the results of qRT-PCR as a reference. Results: : A total of 223 patients were included in this study, and the real-time RT-PCR detected SARS-CoV-2 in 84 (37.7%) patients. Of these 84 patients, 9 (10.7%) were asymptomatic. The overall sensitivity and specificity of RATs were 78.6% and 99.3%, respectively. The sensitivity was 81.3% in symptomatic cases and 55.6% in asymptomatic cases. False-negatives were observed in 18 patients, 3 of whom were asymptomatic and had a low viral load (cycle threshold (Ct) > 30). The detection rate of RATs was 100% when the Ct value was up to 24. The detection rate was 42.3% when the Ct was >29. The detection rate of RATs was 92.3% when the onset of symptoms was within three days. The detection rate was 33.3% when the onset of symptoms was >7 days. Conclusions: : RATs for COVID-19 used in this study delivered an acceptable performance in patients with high viral load and within the first week of the onset of symptoms. They can be used as a supplementary method to RT-PCR for the diagnosis of COVID-19 patients.

Potential long term adverse health outcomes of COVID-19

The coronavirus disease 2019(COVID-19) pandemic poses an extraordinary challenges to patients, communities and overall health care systems. It has resulted in millions of people infected worldwide and has indirectly devastated even more individuals with prolonged post-infectious symptoms. The burden of survivors having post-COVID symptoms is likely to be huge. Multidisciplinary post-COVID-19 clinics are now playing a pivotal role addressing both persistent symptoms and potential long term sequelae. In this review, we tried to summarize the adverse health outcomes based on current evidences, assess the potential risk of long-term complications and make certain recommendations.

Sex-specific epidemiological and clinical characteristics of Covid-19 patients in the southeast region of Bangladesh (preprint)

Background COVID-19 has become a global pandemic with a high growth rate of confirmed cases. In Bangladesh, both mortality and affected rates are increasing at an alarming rate. Therefore, more comprehensive studies of the epidemiological and clinical characteristics of COVID-19 are required to control this pandemic. Purpose The present study aimed to compare and analyze the sex-specific epidemiological, clinical characteristics, comorbidities, and other information of confirmed COVID-19 patients from the southeast region in Bangladesh for the first time. Methods 385 lab-confirmed cases were studied out of 2,471 tested samples between 5 June and 10 September 2020. RT-PCR was used for COVID-19 identification and SPSS (version 25) for statistical data analysis. Results We found that male patients were roughly affected compared to females patients (male 74.30% vs. female 25.7%) with an average age of 34.86 ± 15.442 years, and B (+ve) blood group has been identified as a high-risk factor for COVID-19 infection. Workplace, local market, and bank were signified as sex-specific risk zone ( p < 0.001). Pre-existing medical conditions such as diabetes, hypertension, cardiovascular and respiratory diseases were identified among the patients. Less than half of the confirmed COVID-19 cases in the southeast region were asymptomatic (37.73%) and more prevalent among females than males (male vs. female: 36.84% vs. 40.51%, p = 0.001). Conclusions The findings may help health authorities and the government take necessary steps for identification and isolation, treatment, prevention, and control of this global pandemic.

Genome-wide identification and prediction of SARS-CoV-2 mutations show an abundance of variants: Integrated study of bioinformatics and deep neural learning (preprint)

Genomic data analysis is a fundamental system for monitoring pathogen evolution and the outbreak of infectious diseases. Based on bioinformatics and deep learning, this study was designed to identify the genomic variability of SARS-CoV-2 worldwide and predict the impending mutation rate. Analysis of 259044 SARS-CoV-2 isolates identify 3334545 mutations (14.01 mutations per isolate), suggesting a high mutation rate. Strains from India showed the highest no. of mutations (48) followed by Scotland, USA, Netherlands, Norway, and France having up to 36 mutations. Besides the most prominently occurring mutations (D416G, F106F, P314L, and UTR:C241T), we identify L93L, A222V, A199A, V30L, and A220V mutations which are in the top 10 most frequent mutations. Multi-nucleotide mutations GGG>AAC, CC>TT, TG>CA, and AT>TA have come up in our analysis which are in the top 20 mutational cohort. Future mutation rate analysis predicts a 17%, 7%, and 3% increment of C>T, A>G, and A>T, respectively in the future. Conversely, 7%, 7%, and 6% decrement is estimated for T>C, G>A, and G>T mutations, respectively. T>G\A, C>G\A, and A>T\C are not anticipated in the future. Since SARS-CoV-2 is evolving continuously, our findings will facilitate the tracking of mutations and help to map the progression of the COVID-19 intensity worldwide.

Engineering students’ readiness for online learning amidst the COVID-19 pandemic: Scale validation and lessons learned from a developing country (preprint)

Background: - Engineering education utilizes a face-to-face model for delivery of course materials and workshops. The recent outbreak of the COVID-19 pandemic imposed a countrywide lockdown and forced education institutes to shift to an internet-based online delivery mode. Purpose: /Hypothesis - This study developed an instrument to meticulously measure the students’ readiness for online learning in a pandemic situation. A situation like COVID-19 accelerates a long-standing issue of digital inequality among the students in education. The study proposed a reconceptualised model for students’ online readiness for emergencies like COVID-19. The proposed model consists of (a) motivation, (b) self-efficacy, and (c) situational factors. Design: /Method - The proposed model was validated with the engineering students (for pilot study N = 68 and main study N = 988) from several universities in Bangladesh. To validate the underlying relationships between the latent constructs, an exploratory factor analysis (EFA) was performed followed by structural equation modelling (SEM) for the construct validity of the measurement model and to assess the model fit. Results: - The findings showed that besides motivation and self-efficacy, the situational factors describing the contextual dynamics emerging from the COVID-19 significantly influenced the student's online readiness. Conclusions: - The impact of situational factors on student readiness for online learning is complex, specially during events such as the COVID-19 pandemic. By analyzing the collected data, it is evident that current practices of teaching should be blended with face-to-face, synchronous and asynchronous internet-based learning. We argue that digital inequality is an important factor influencing student readiness for online learning.

Coping with COVID-19 Pandemic: A Population-Based Study in Bangladesh (preprint)

ABSTRACT This study aims to investigate coping strategies used by Bangladeshi citizens during the COVID-19 pandemic. Design Prospective, cross-sectional survey of adults (N=2001) living in Bangladesh. Methods Participants were interviewed for socio-demographic data and completed the Bengali translated Brief-COPE Inventory. Statistical data analysis was conducted using SPSS (Version 20). Results Participants (N=2001), aged 18 to 86 years, were recruited from eight administrative divisions within Bangladesh (mean age 31.85±14.2 years). Male to female participant ratio was 53.4% (n=1074) to 46.6% (n=927). Higher scores were reported for approach coping styles (29.83±8.9), with lower scores reported for avoidant coping styles (20.83 ± 6.05). Humor coping scores were reported at 2.68±1.3 and religion coping scores at 5.64±1.8. Both men and women showed similar coping styles. Multivariate analysis found a significant relationship between male gender and both humor and avoidant coping (p Conclusion Participants in this study coped with the COVID-19 pandemic by utilizing a combination of coping strategies. Factor 1 revealed both avoidant and approach coping strategies and Factor 2 revealed a combination of humor and avoidant coping strategies. Overall, a higher utilization of approach coping strategies was reported, which has previously been associated with better physical and mental health outcomes. Religion was found to be a coping strategy for all participants. Future research may focus on understanding resilience in vulnerable populations, including people with disability or with migrant or refugee status in Bangladesh.

First detection of SARS-CoV-2 genetic material in the vicinity of COVID-19 isolation centre through wastewater surveillance in Bangladesh (preprint)

In the course of a COVID-19 pandemic, 0.33 million people got infected in Bangladesh, we made the first and successful attempt to detect SARS-CoV-2 viruses' genetic material in the vicinity wastewaters of an isolation centre i.e. Shaheed Bhulu Stadium, situated at Noakhali. The idea was to understand the genetic loading variation, both temporal and distance-wise in the nearby wastewater drains when the number of infected COVID-19 patients is not varying much. Owing to the fact that isolation center, in general, always contained a constant number of 200 COVID-19 patients, the prime objective of the study was to check if several drains carrying RNA of coronavirus are actually getting diluted or accumulated along with the sewage network. Our finding suggested that while the temporal variation of the genetic load decreased in small drains over the span of 50 days, the main sewer exhibited accumulation of SARS-CoV-2 RNA. Other interesting finding displays that probably distance of sampling location in meters is not likely to have a significant impact on gene detection concentration, although the quantity of the RNA extracted in the downstream of the drain was higher. These findings are of immense value from the perspective of wastewater surveillance of COVID-19, as they largely imply that we do not need to monitor every wastewater system, and probably major drains monitoring may illustrate the city health. Perhaps, we are reporting the accumulation of SARS-CoV-2 genetic material along the sewer network i.e. from primary to tertiary drains. The study sought further data collection in this line to simulate conditions prevailed in the most of south Asian country and to shed further light on the temporal variation and decay/accumulation processes of the genetic load of the SARS-COV-2.

Covidex: an ultrafast and accurate tool for virus subtyping (preprint)

Covidex is an open-source, alignment-free machine learning subtyping tool for viral species. It is a shiny app that allows a fast and accurate classification in pre-defined clusters for SARS-CoV-2 and FMDV genome sequences. The user can also build its own classification models with the Covidex model generator. AvailabilityCovidex is open-source, cross-platform compatible, and is available under the terms of the GNU General Public License v3 (http://www.gnu.org/licenses/gpl.txt). Covidex is available via SourceForge https://sourceforge.net/projects/covidex or the web application https://cacciabue.shinyapps.io/shiny2/ Contactcacciabue.marco@inta.gob.ar; marcocacciabue@yahoo.com

Temporal landscape of mutation accumulation in SARS-CoV-2 genomes from Bangladesh: possible implications from the ongoing outbreak in Bangladesh (preprint)

Along with intrinsic evolution, adaptation to selective pressure in new environments might have resulted in the circulatory SARS-CoV-2 strains in response to the geoenvironmental conditions of a country and the demographic profile of its population. Thus the analysis of genomic mutations of these circulatory strains may give an insight into the molecular basis of SARS-CoV-2 pathogenesis and evolution favoring the development of effective treatment and containment strategies. With this target, the current study traced the evolutionary route and mutational frequency of 198 Bangladesh originated SARS-CoV-2 genomic sequences available in the GISAID platform over a period of 13 weeks as of 14 July 2020. The analyses were performed using MEGA 7, Swiss Model Repository, Virus Pathogen Resource and Jalview visualization. Our analysis identified that majority of the circulating strains in the country belong to B and/or L type among cluster A to Z and strikingly differ from both the reference genome and the first sequenced genome from Bangladesh. Mutations in Nonspecific protein 2 (NSP2), NSP3, RNA dependent RNA polymerase (RdRp), Helicase, Spike, ORF3a, and Nucleocapsid (N) protein were common in the circulating strains with varying degrees and the most unique mutations(UM) were found in NSP3 (UM-18). But no or limited changes were observed in NSP9, NSP11, E (Envelope), NSP7a, ORF 6, and ORF 7b suggesting the possible conserved functions of those proteins in SARS-CoV-2 propagation. However, along with D614G mutation, more than 20 different mutations in the Spike protein were detected basically in the S2 domain. Besides, mutations in SR-rich region of N protein and P323L in RDRP were also present. However, the mutation accumulation showed an association with sex and age of the COVID-19 positive cases. So, identification of these mutational accumulation patterns may greatly facilitate drug/ vaccine development deciphering the age and the sex dependent differential susceptibility to COVID-19.

Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach (preprint)

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores -9.1, -7.4, and -7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.