Data-Driven Estimation of Effectiveness of COVID-19 Non-pharmaceutical Intervention Policies

Non-pharmaceutical Interventions (NPIs), such as Stay-at-Home, and Face-Mask-Mandate, are essential components of the public health response to contain an outbreak like COVID-19. However, it is very challenging to quantify the individual or joint effectiveness of NPIs and their impact on people from different racial and ethnic groups or communities in general. Therefore, in this paper, we study the following two research questions: 1) How can we quantitatively estimate the effectiveness of different NPI policies pertaining to the COVID-19 pandemic?;and 2) Do these policies have considerably different effects on communities from different races and ethnicity? To answer these questions, we model the impact of an NPI as a joint function of stringency and effectiveness over a duration of time. Consequently, we propose a novel stringency function that can provide an estimate of how strictly an NPI was implemented on a particular day. Next, we applied two popular tree-based discriminative classifiers, considering the change in daily COVID cases and death counts as binary target variables, while using stringency values of different policies as independent features. Finally, we interpreted the learned feature weights as the effectiveness of COVID-19 NPIs. Our experimental results suggest that, at the country level, restaurant closures and stay-at-home policies were most effective in restricting the COVID-19 confirmed cases and death cases respectively;and overall, restaurant closing was most effective in hold-down of COVID-19 cases at individual community levels such as Asian, White, Black, AIAN and, NHPI. Additionally, we also performed a comparative analysis between race-specific effectiveness and country-level effectiveness to see whether different communities were impacted differently. Our findings suggest that the different policies impacted communities (race and ethnicity) differently. © 2022 IEEE.

Did national holidays accelerate COVID-19 diffusion "during the first phase of the” of pandemic in Bangladesh?

Bangladesh registered 20,117,32 confirmed cases of COVID-19 and the death toll crossed the grim milestone of 29,323 across the country as of August 31st, 2022. Despite the enforcement of stringent COVID-19 measures, the country witnessed an accelerated diffusion of coronavirus cases during the national events, inclusive of short festivals, in 2020. The present study aims to examine the association between these national holidays and the COVID-19 trasmission rate in Bangladesh. We employed a mathematical model and calculated the instantaneous reproduction number, Rt, of the 64 districts in Bangladesh to check the dynamics of COVID-19 diffusion. The comprehensive analysis shows a notable escalation of Rt value and thus the enhanced transmission rate in Dhaka and in all industrialized cities during the major events such as, garments reopening and religious holidays in Bangladesh. We further showcase the COVID-19 diffusion explicitly in Dhaka Division at the first phase of the pandemic in Bangladesh. Based on our analysis, a set of measures, including restricted public mobility and the celebration of festivals, alongside improving the public's awareness of the situation, has been recommended to evade the future pandemic risks while running the national festival activities in Bangladesh. © 2023, Intelektual Pustaka Media Utama. All rights reserved.

Knowledge and attitude towards COVID-19 among adult people in Bangladesh: evidence from an online survey

The objective of this study was to examine the levels and determinants of knowledge and attitudes toward COVID-19 among adult people in Bangladesh, using data from an online survey, conducted in May 2021. Descriptive and inferential statistical analysis were performed to extract findings from data. The survey covered 993 respondents. A high level (78.4%) of effective knowledge and positive attitude (78.6%) were observed among the Bangladeshi people. More than eighty percent of the respondents could correctly mention at least one important symptom, mode of transmission, and preventive measures of COVID-19. Good knowledge and positive attitudes were found to be significantly higher among males, living in Dhaka city, having a higher level of education, health professionals, and the wealthiest people. Knowledge about COVID-19 has significant association with positive attitude of people towards COVID-19. Despite the high level of knowledge and positive attitudes, there still prevails some misconceptions among a group of people, as one-third of the respondents opined that COVID-19 is a divine punishment and 13% were in favor of keeping it secrete if COVID-19 infection happen to them. The findings underscore the need for more educational program and behavior change communication (BCC) for the subgroups of the population that has been identified with poor knowledge and negative attitudes towards COVID-19. © 2023, Intelektual Pustaka Media Utama. All rights reserved.

Clinico-epidemiological Characteristics of Asymptomatic and Symptomatic COVID-19-Positive Patients in Bangladesh.

As of August 15, 2020, Bangladesh lost 3591 lives since the first Coronavirus disease 2019 (COVID-19) case announced on March 8. The objective of the study was to report the clinical manifestation of both symptomatic and asymptomatic COVID-19-positive patients. An online-based cross-sectional survey was conducted for initial recruitment of participants with subsequent telephone interview by the three trained physicians in 237 adults with confirmed COVID-19 infection in Bangladesh. The study period was 27 April to 26th May 2020. Consent was ensured before commencing the interview. Collected data were entered in a pre-designed case record form and subsequently analyzed by SPSS 20.0. The mean±SD age at presentation was 41.59±13.73 years and most of the cases were male (73.0%). A total of 90.29% of patients reside in urban areas. Among the positive cases, 13.1% (n=31) were asymptomatic. Asymptomatic cases were significantly more common in households with 2 to 4 members (p=0.008). Both symptomatic and asymptomatic patients shared similar ages of presentation (p=0.23), gender differences (p=0.30) and co-morbidities (p=0.11). Only 5.3% of patients received ICU care during their treatment. The most frequent presentation was fever (88.3%), followed by cough (69.9%), chest pain (34.5%), body ache (31.1%), and sore throat (30.1%). Thirty-nine percent (n=92) of the patients had co-morbidities, with diabetes and hypertension being the most frequently observed. There has been an upsurge in COVID-19 cases in Bangladesh. Patients were mostly middle-aged and male. Typical presentations were fever and cough. Maintenance of social distancing and increased testing are required to meet the current public health challenge.

Long-term Outcomes Following Prolonged Mechanical Ventilation for COVID-19

Introduction: The purpose of this study is to evaluate longterm laryngotracheal outcomes in patients who required 10 or more days of invasive mechanical ventilation (IMV) for COVID-19. Method(s): This is a prospective cohort study of patients previously hospitalized for active COVID-19 infection between January 2020 and March 2021 who required intubation for 10+ days. Subjects who met criteria were enrolled at an outpatient laryngology clinic, where they underwent a clinical evaluation with head and neck exam, nasolaryngoscopy, and patient-reported outcome measures (Voice Handicap Index, EAT-10). Medical history was collected through electronic medical record review. Result(s): In total, 166 patients met criteria based on chart review. Of these patients, 31 (18.6%) were deceased since discharge. Enrolled subjects included 16 patients, 2 women and 14 men, with mean (SD) age of 57.4 (14.12) years. The mean duration (SD) of IMV was 36.8 (21.8) days. Fourteen of 16 patients underwent tracheostomy for prolonged endotracheal intubation. The mean time (SD) from hospital admission to intubation was 2.7 (3.2) days, intubation to tracheostomy or extubation was 13.9 (5.3) days, and tracheostomy to decannulation was 38.1 (22.6) days. Conclusion(s): Patients who required prolonged mechanical ventilation to treat COVID acute respiratory distress syndrome demonstrated significant laryngeal or tracheal pathology during laryngoscopy at 1-year follow-up, though subjectively, their self-reported voice and swallowing deficits were mild.

Emergence of Polarization and Marginalization in Online Education System of Bangladesh Due to COVID-19: Challenges and Policies to Ensure Inclusive Education

Before COVID-19, online learning was almost non-existent in the educational institutions of Bangladesh. Unavailability of Internet and proper devices among the students, lack of training, and the unwillingness of the institutions in integrating a new way of providing education were the main reasons behind the less prevalence of online education in Bangladesh. Due to their lack of experience, design policies, and infrastructural incapacity, educational institutions struggled enormously to make the transition to online learning from face-to-face teaching during this ongoing pandemic. Primary and secondary educational institutions are the major victims of this hasty transformation. Although universities in Bangladesh are trying to continue their regular academic curriculum, the real scenario is far from perfect. To understand the problems of the online education system of Bangladeshi universities, we conducted a survey among 184 students. The user responses were analyzed in two different ways: unsupervised clustering that revealed socio-economic polarization among the students;and feature specific statistical analysis that identified the emerging marginal student groups. Our analysis shows that the factors behind the polarization and marginalization of students include locality, living conditions, primary device for attending class, Internet connectivity etc. Based on these factors, we lay out an inclusive design policy with three action plans that would reduce the polarization and marginalization of university students in online education.

Blended Learning Center Management during COVID-19 Pandemic

The main purpose of this study has to conduct an online survey to get feedback from Daffodil International University(DIU), Bangladesh faculty and students on their perceptions and experiences with Blended Learning Center classrooms. In the midst of the present pandemic crisis, the DIU education system has made a recent change by delivering classes via online BLC (Blended Learning Center) platform. Additionally, this survey analyses the perspectives and considerations of university teachers and students about attending online programs, which have become mandatory because of COVID19. The survey included 9 teachers and 133 students from university. For the aim of data gathering, an online survey method has been used. The study reveals that excellent and regular interaction among students and professors, technical support accessibility, organized online educational modules, and adjustments to allow the conduct of practical lessons are all significant for teachers and students sense of accomplishment using online courses. © 2021 IEEE.

COVID19(alpha) : Interactive Spatio-Temporal Visualization of COVID-19 Symptoms through Tweet Analysis

In this demo, we focus on analyzing COVID-19 related symptoms across the globe reported through tweets by building an interactive spatio-temporal visualization tool, i.e., COVID19(alpha). Using around 462 million tweets collected over a span of six months, COVID19(alpha) provides three different types of visualization tools: 1) Spatial Visualization with a focus on visualizing COVID-19 symptoms across different geographic locations;2) Temporal Visualization with a focus on visualizing the evolution of COVID-19 symptoms over time for a particular geographic location;and 3) Spatio-Temporal Visualization with a focus on combining both spatial and temporal analysis to provide comparative visualizations between two (or more) symptoms across time and space. We believe that health professionals, scientists, and policymakers will be able to leverage this interactive tool to devise better and targeted health intervention policies. Our developed interactive visualization tool is publicly available at https://bijoy-sust.github.io/Covid19/.

MONOSACCHARIDE DERIVATIVES: SYNTHESIS, ANTIMICROBIAL, PASS, ANTIVIRAL AND MOLECULAR DOCKING STUDIES AGAINST SARS-COV-2 M-PRO INHIBITORS

Several carbohydrate-based drugs are currently being used to treat a number of diseases in humans worldwide. Thus, our research group has focused on the synthesis of new methyl alpha-D-mannopyranoside (MDM) derivatives and their antimicrobial evaluation through computational studies. A series of MDM derivatives (2-6) were synthesized through facile regioselective acylation, using the direct method affording 6-O-(3-chlorobenzoyl) derivatives. This isolated 6-O-derivative was further transformed to 2,3,4-tri-O-acyl derivatives, bearing a wide variety of functionalities in a single molecular framework. The structures of the newly designed molecules were elucidated with the aid of IR, H-1 NMR, mass spectroscopy, and elemental analysis. The prediction of the activity spectra for the compounds (PASS) and their in vitro antimicrobial evaluation were performed, demonstrating them to be potential antimicrobial agents. The antimicrobial tests demonstrated that the compounds 3 and 5 were the most potent with the minimum inhibitory concentration (MIC) values, ranging from 0.312 +/- 0.01 to 1.25 +/- 0.03 mg/mL, and minimum bactericidal concentration (MBC) values, ranging from 0.625 +/- 0.02 to 2.50 +/- 0.05 mg/mL. A quantum chemical study was performed to calculate the thermodynamic, molecular orbital and electrostatic potential properties of the designed compounds. Molecular docking simulation was carried out against SARS-CoV-2 M-pro protein 7BQY and 6Y84 to investigate their binding energy and binding tactics with the viral protein, and better binding affinity than that of the parent drug was observed. Also, pharmacokinetic prediction revealed an improved drug-likeness profile for all MDM derivatives.

Transparent Data Dealing: Hyperledger Fabric Based Biomedical Engineering Supply Chain

Blockchain is a decentralized and immutable technology which offers transparency for the digital world, where habitual technology does not. The novel blockchain technology may be employed by many sectors, i.e., healthcare, bank, government services, and supply chain. In particular, Biomedical Engineering Supply Chain (BESC) is a significant part of the medical sector that supplies equipment for the medical sector i.e., Covid-19 testing kit, PPE (Personal Protection Equipment), and medicine. The biomedical product should be able to be traced and the data secured;otherwise, the initial data may be modified and potentially risking patients and the public. Nevertheless, the conventional centralized technology creates a leakage point and as such, compromises data security. This paper proposes a new data dealing approach with using Hyperledger Fabric Blockchain-based BESC to alleviate the centralized controllable and operational issues. The blockchain-based BESC is a novel approach, which can control the users and subsequently eliminate the possibility of tampering within the blockchain system when stored.

Fighting against Fake News during Pandemic Era: Does Providing Related News Help Student Internet Users to Detect COVID-19 Misinformation?

The COVID-19 "infodemic"has resulted in the widespread dissemination of counterfeit medical advice, hoaxes, fake products, and phoney information about the virus and responses. As a result, computational methods for determining any information's authenticity to improve trust in public health awareness and policy decisions are profoundly discussed in the scientific community. Even before the pandemic, mis- and disinformation, including fake news, have been observed in the online world in significant numbers for numerous business, political and personal reasons. Moreover, many of these fake news was published from sources believed to be reliable. In contrast, some other fake news was fabricated in a way that would be easily trusted and shared by the general people in social media. COVID-19 related fake news has enormous effects on both the offline and online community, and thus, it challenges government initiatives for proper health intervention. Therefore, interest in research in this area has risen to understand the problem both socially and technically. In this paper, we attempt to understand how we can help student Internet users of colleges from the lower-middle-income country, Bangladesh, in Southeast Asia, to distinguish COVID-19 misinformation. Our study reveals that providing related news as supplementary information to any online news helps students make better decision about news authenticity. Statistical analyses on the survey data show that male students were found to be more accurate than female students to detect mis- and disinformation;students from the urban areas could detect misleading news better than students from villages;and that students from Science background demonstrated overall best performance, while students from Madrasah background, who are all male, could not produce a significant improvement. We conclude that the female students in general and male students of Madrasah, who spend the least amount of time online among all the student Internet users, are the most vulnerable groups to fake news. © 2021 ACM.