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Fulltext Factors Associated with the Perception of Risk and Knowledge of Contracting the SARS-Cov-2 among Adults in Bangladesh: Analysis of Online Surveys

Abir T, Kalimullah NA, Osuagwu UL, Yazdani DMN, Mamun AA, Husain T, et al.

Int J Environ Res Public Health, 2020 Jul 21;17(14).
PMID: 32708161 DOI: 10.3390/ijerph17145252

This study investigated the perception and awareness of risk among adult participants in Bangladesh about Coronavirus Disease 2019 (COVID-19). During the lockdown era in Bangladesh at two different time points, from 26-31 March 2020 (early lockdown) and 11-16 May 2020 (late lockdown), two self-administered online surveys were conducted on 1005 respondents (322 and 683 participants, respectively) via social media. To examine risk perception and knowledge-related factors towards COVID-19, univariate and multiple linear regression models were employed. Scores of mean knowledge (8.4 vs. 8.1, p = 0.022) and perception of risk (11.2 vs. 10.6, p < 0.001) differed significantly between early and late lockdown. There was a significant decrease in perceived risk scores for contracting SARS-Cov-2 [β = -0.85, 95%CI: -1.31, -0.39], while knowledge about SARS-Cov-2 decreased insignificantly [β = -0.22, 95%CI: -0.46, 0.03] in late lockdown compared with early lockdown period. Self-quarantine was a common factor linked to increased perceived risks and knowledge of SARS-Cov-2 during the lockdown period. Any effort to increase public awareness and comprehension of SARS-Cov-2 in Bangladesh will then offer preference to males, who did not practice self-quarantine and are less worried about the propagation of this kind of virus.
ECG waveform generation from radar signals: A deep learning perspective

Chowdhury FA, Hosain MK, Bin Islam MS, Hossain MS, Basak P, Mahmud S, et al.

Comput Biol Med, 2024 May 11;176:108555.
PMID: 38749323 DOI: 10.1016/j.compbiomed.2024.108555

Cardiovascular diagnostics relies heavily on the ECG (ECG), which reveals significant information about heart rhythm and function. Despite their significance, traditional ECG measures employing electrodes have limitations. As a result of extended electrode attachments, patients may experience skin irritation or pain, and motion artifacts may interfere with signal accuracy. Additionally, ECG monitoring usually requires highly trained professionals and specialized equipment, which increases the treatment's complexity and cost. In critical care scenarios, such as continuous monitoring of hospitalized patients, wearable sensors for collecting ECG data may be difficult to use. Although there are issues with ECG, it remains a valuable tool for diagnosing and monitoring cardiac disorders due to its non-invasive nature and the detailed information it provides about the heart. The goal of this study is to present an innovative method for generating continuous ECG waveforms from non-contact radar data by using Deep Learning. The method can eliminate the need for invasive or wearable biosensors and expensive equipment to collect ECGs. In this paper, we propose the MultiResLinkNet, a one-dimensional convolutional neural network (1D CNN) model for generating ECG signals from radar waveforms. With the help of a publicly accessible radar benchmark dataset, an end-to-end DL architecture is trained and assessed. There are six ports of raw radar data in this dataset, along with ground truth physiological signals collected from 30 participants in five distinct scenarios: Resting, Valsalva, Apnea, Tilt-up, and Tilt-down. By using strong temporal and spectral measurements, we assessed our proposed framework's ability to convert ECG data from Radar signals in three distinct scenarios, namely Resting, Valsalva, and Apnea (RVA). ECG segmentation performed better by MultiResLinkNet than by state-of-the-art networks in both combined and individual cases. As a result of the simulations, the resting, valsalva, and RVA scenarios showed the highest average temporal values, respectively: 66.09523 ± 19.33, 60.13625 ± 21.92, and 61.86265 ± 21.37. In addition, it exhibited the highest spectral correlation values (82.4388 ± 18.42 (Resting), 77.05186 ± 23.26 (Valsalva), 74.65785 ± 23.17 (Apnea), and 79.96201 ± 20.82 (RVA)), along with minimal temporal and spectral errors in almost every case. The qualitative evaluation revealed strong similarities between generated and actual ECG waveforms. As a result of our method of forecasting ECG patterns from remote radar data, we can monitor high-risk patients, especially those undergoing surgery.
Psychological Impact of COVID-19 Pandemic in Bangladesh: Analysis of a Cross-Sectional Survey

Abir T, Osuagwu UL, Kalimullah NA, Yazdani DMN, Husain T, Basak P, et al.

Health Secur, 2021 08 03;19(5):468-478.
PMID: 34348050 DOI: 10.1089/hs.2020.0205

The COVID-19 pandemic has generated fear, panic, distress, anxiety, and depression among many people in Bangladesh. In this cross-sectional study, we examined factors associated with different levels of psychological impact as a result of COVID-19 in Bangladesh. From April 1 to 30, 2020, we used a self-administered online questionnaire to collect data from 10,609 respondents. Using the Impact of Event Scale-Revised to assess the psychological impact of the COVID-19 pandemic on respondents, we categorized the levels of impact as normal, mild, moderate, or severe. Ordinal logistic regression was used to examine the associated factors. The prevalence of mild, moderate, and severe psychological impact was 10.2%, 4.8%, and 45.5%, respectively. Multivariate analysis revealed that the odds of reporting normal vs mild, moderate, or severe psychological impact were 5.9 times higher for people living in the Chittagong Division, 1.7 times higher for women with lower education levels, 3.0 times higher among those who were divorced or separated, 1.8 times higher for those working full time, and 2.4 times higher for those living in shared apartments. The odds of reporting a psychological impact were also higher among people who did not enforce protective measures inside the home, those in self-quarantine, those who did not wear face masks, and those who did not comply with World Health Organization precautionary measures. Increased psychological health risks due to COVID-19 were significantly higher among people who experienced chills, headache, cough, breathing difficulties, dizziness, and sore throat before data collection. Our results showed that 1 in 2 respondents experienced a significant psychological impact as a result of the COVID-19 pandemic. Public health researchers should consider these factors when targeting interventions that would have a protective effect on the individual's psychological health during a pandemic or future disease outbreak.
Fulltext Dengue in Dhaka, Bangladesh: Hospital-based cross-sectional KAP assessment at Dhaka North and Dhaka South City Corporation area

Abir T, Ekwudu O, Kalimullah NA, Nur-A Yazdani DM, Al Mamun A, Basak P, et al.

PLoS One, 2021;16(3):e0249135.
PMID: 33784366 DOI: 10.1371/journal.pone.0249135

Dengue, the most important mosquito-borne viral disease of humans is a recurring global health problem. In Bangladesh, dengue outbreaks are on the increase despite the efforts of government and it is not clear what the understanding of the general Dhaka population towards dengue fever is. Knowledge, attitude and practice (KAP) studies are essential guides in public health interventions. Hence, using KAP, this study aims to assess patient-perspectives with regards to factors associated with dengue, as well as investigate the associated factors between the two corporations in Dhaka. A Hospital-based cross-sectional study of 242 fever patients from two city-corporations in Dhaka (Dhaka North City Corporations, DNCC (n = 91, 37.6%) and Dhaka South City Corporation, DSCC (n = 151, 62.4%) was conducted using pre-tested KAP items. Wilcoxon's Rank Sum was used to determine the KAP by DNCC, DSCC and both corporations and multivariate Poisson regression analyses. The two corporations were analysed separately due to the differences in income distribution, concentration of slums, hospitals and clinics. The study found that more than half of the study population were knowledgeable about dengue (mean percentage scores was 52%), possess an appropriate and acceptable attitude towards the disease (69.2%), and about two thirds of the respondents (71.4%) engaged in practices towards its prevention. After adjusting for the potential cofounders, the factors associated with KAP about dengue fever varied between DNCC and DSCC; with duration of residency and use of mosquito nets were associated with knowledge in the north while income class and age were associated with knowledge and attitude in the south. In the pooled analysis (combining both corporations), knowledge of dengue was associated with good practice towards dengue fever among the respondents. The duration of residence in Dhaka (10+ years), not using mosquito nets and length of time spent in the hospital (7+ days) due to dengue, and decreased knowledge (Adjusted coefficient (β) = -0.01, 95%CI: -0.02, -0.01) were associated with attitude towards dengue in DNCC. On the other hand, middle-high income class, age (40+ years) and increased knowledge were associated with practice towards dengue in DSCC (β = 0.02, 95%CI: 0.01, 0.03). Efforts to increase knowledge about dengue fever through education by the administrations of both corporations would benefit from targeting these high-risk groups for a more sustainable outcome.
Fulltext Prevalence and Factors Associated with Mental Health Impact of COVID-19 Pandemic in Bangladesh: A Survey-Based Cross-Sectional Study

Abir T, Kalimullah NA, Osuagwu UL, Nur-A Yazdani DM, Husain T, Goson PC, et al.

Ann Glob Health, 2021 04 26;87(1):43.
PMID: 33981590 DOI: 10.5334/aogh.3269

Background: Feelings of isolation, insecurity, and instability triggered by COVID-19 could have a long-term impact on the mental health status of individuals.
Objectives: The aim of this study was to examine the prevalence of mental health symptoms (anxiety, depression, and stress) in Bangladesh and the factors associated with these symptoms during the COVID-19 pandemic.
Methods: From 1 to 30 April 2020, we used a validated self-administered questionnaire to conduct a cross-sectional study on 10,609 participants through an online survey platform. We assessed mental health status using the Depression, Anxiety, and Stress Scale (DASS-21). The total depression, anxiety, and stress subscale scores were divided into normal, mild, moderate, severe, and multinomial logistic regression was used to examine associated factors.
Findings: The prevalence of depressive symptoms was 15%, 34%, and 15% for mild, moderate, and severe depressive symptoms, respectively. The prevalence of anxiety symptoms was 59% for severe anxiety symptoms, 14% for moderate anxiety symptoms, and 14% for mild anxiety symptoms, while the prevalence for stress levels were 16% for severe stress level, 22% for moderate stress level, and 13% for mild stress level. Multivariate analyses revealed that the most consistent factors associated with mild, moderate, and severe of the three mental health subscales (depression, anxiety, and stress) were respondents who lived in Dhaka and Rangpur division, females, those who self-quarantined in the previous seven days before the survey, and those respondents who experienced chills, breathing difficulty, dizziness, and sore throat.
Conclusion: Our results showed that about 64%, 87%, and 61% of the respondents in Bangladesh reported high levels of depression, anxiety, and stress, respectively. There is a need for mental health support targeting women and those who self-quarantined or lived in Dhaka and Rangpur during the pandemic.