Evacuation dilemmas of coastal households during cyclone Amphan and amidst the COVID-19 pandemic: a study of the Southwestern region of Bangladesh.

Cyclone Amphan battered the coastal communities in the southwestern part of Bangladesh in 2020 during the COVID-19 pandemic. These coastal communities were experiencing such a situation for the first time and faced the dilemma of whether to stay at home and embrace the cyclone or be exposed to the COVID-19 virus in the cyclone shelters by evacuating. This article intends to explore individuals' decisions regarding whether to evacuate in response to cyclone Amphan and in light of the risks of the COVID-19 pandemic. Consequently, this study investigated evacuation behaviors among the households and explored the impacts of COVID-19 during the evacuation procedures. We conducted household surveys to collect primary information and undertook 378 samples for interviews at a precision level of 0.05 in fourteen villages. Despite the utmost effort of the government, the results demonstrated that 96.6% of people in the coastal area received a cyclone evacuation order before the cyclone's landfall, and only 42% of people followed the evacuation order. The majority of households chose to stay at home because of fear of COVID-19 exposure in the crowded shelters. Although half of the evacuees were housed in cyclone shelters, COVID-19 preventive measures were apparently not set in place. Thus, this study will assist in crafting future government policies to enhance disaster evacuation plans by providing insights from the pandemic that can inform disaster management plans in the Global South.

Machine learning to analyse omic-data for COVID-19 diagnosis and prognosis.

BACKGROUND: With the global spread of COVID-19, the world has seen many patients, including many severe cases. The rapid development of machine learning (ML) has made significant disease diagnosis and prediction achievements. Current studies have confirmed that omics data at the host level can reflect the development process and prognosis of the disease. Since early diagnosis and effective treatment of severe COVID-19 patients remains challenging, this research aims to use omics data in different ML models for COVID-19 diagnosis and prognosis. We used several ML models on omics data of a large number of individuals to first predict whether patients are COVID-19 positive or negative, followed by the severity of the disease. RESULTS: On the COVID-19 diagnosis task, we got the best AUC of 0.99 with our multilayer perceptron model and the highest F1-score of 0.95 with our logistic regression (LR) model. For the severity prediction task, we achieved the highest accuracy of 0.76 with an LR model. Beyond classification and predictive modeling, our study founds ML models performed better on integrated multi-omics data, rather than single omics. By comparing top features from different omics dataset, we also found the robustness of our model, with a wider range of applicability in diverse dataset related to COVID-19. Additionally, we have found that omics-based models performed better than image or physiological feature-based models, proving the importance of the omics-based dataset for future model development. CONCLUSIONS: This study diagnoses COVID-19 positive cases and predicts accurate severity levels. It lowers the dependence on clinical data and professional judgment, by leveraging the utilization of state-of-the-art models. our model showed wider applicability across different omics dataset, which is highly transferable in other respiratory or similar diseases. Hospital and public health care mechanisms can optimize the distribution of medical resources and improve the robustness of the medical system.

Factors associated with Facebook addiction among university students amid the COVID-19 pandemic: Findings from an online cross-sectional survey.

BACKGROUND: Facebook addiction (FA) has been suggested as a potential behavioral addiction. There is a severe lack of research evidence regarding the Facebook addiction behavior among university students during the ongoing COVID-19 pandemic. The aim of this study was to determine factors associated with Facebook addiction among Bangladeshi university students. METHODS: A cross-sectional online survey was conducted among 2,161 Bangladeshi university students during the COVID-19 pandemic from June 2021 to September 2021. A well fitted regression model in R programming language was used for this study. RESULTS: Female respondents and those whose family monthly income was <25,000 BDT were more addicted to Facebook than other respondents. Respondents who lost a family member or a relative to COVID-19, engaged in physical activities (exercise) during the pandemic, used Facebook for work purposes or used Facebook to relieve daily stress were more addicted to Facebook. CONCLUSION: Overuse of social media is problematic as it can trigger several mental health symptoms, especially among students. Adequate and effective interventions are required to educate students about the dangers of Facebook addiction and to provide an alternative, healthy options.

COVID-19 Burdens on Livelihood Opportunities: A Study of Easy-Bike Drivers in Rangpur City, Bangladesh

This research explores the nexus between COVID-19 and the livelihoods of easy-bike (three-wheeler human hauliers) drivers using a case study of Rangpur City, Bangladesh. Although easy-bike has become a prevalent form of paratransit among city-dwellers in medium-sized cities in Bangladesh, many passengers are now avoiding such paratransit to maintain health and safety guidelines during the COVID-19 pandemic. The pandemic has negatively affected easy-bike drivers' income in many medium-sized cities. To conduct this study, we collected primary data from the field, with the health and safety guidelines recommended by the government of Bangladesh in consideration. The results demonstrate a decreasing number of trips due to government policy changes under the COVID-19 pandemic, influencing people's earnings associated with this transit system. We summarized the data to capture the attention of policymakers, who may need to introduce any foreseeable action to assist workers of different professions in need of economic assistance in cities outside of the capital city in Bangladesh. Moreover, we suggest the need to consider these urban transport workers as a vulnerable group for livelihood assistance within the country.

Factors associated with suicidal behavior among university students in Bangladesh after one year of COVID-19 pandemic.

BACKGROUND: The COVID-19 outbreak spillovers mental health burden where suicide is a common psychological public health issue that affects people all over the world. This study aimed to explore the factors associated with suicidal behavior among university students in Bangladesh after one year of the COVID-19 outbreak. METHODS: An online cross-sectional survey was conducted among 2100 Bangladeshi university students aged ≥18 years from April 29 to May 15, 2021. The survey questionnaire contained socio-demographic information, COVID-19 related physical and psychosocial factors (CRPPF), preventive response to psychological stress, and the Suicidal Behaviors Questionnaire-Revised (SBQ-R) scale. Descriptive statistics along with logistic regression were performed for statistical analysis. RESULTS: About 47.90% of the students were at risk of suicidal behavior, and female students were very likely to be at risk of suicidal behavior than their male counterparts (AOR = 2.28; 95% CI: 1.86 to 2.81). Keeping distance from friends or family (AOR = 1.66; 95% CI: 1.34 to 2.04), having relationship problems (AOR = 2.20; 95% CI: 1.79 to 2.70), feeling own selves as burden to families (AOR = 2.50; 95% CI: 2.02 to 3.11), and being stressed of lockdown (AOR = 1.56; 95% CI: 1.19 to 2.03) were highlighted as some of the significant factors associated with increased risk of suicidal behavior. CONCLUSION: University students were exposed to several factors that impose the risk of developing suicidal behavior. Concerned authorities should design & implement appropriate strategies for ensuring suicidal prevention besides their mental well-being.

Is Bitcoin a hedge? How extreme volatility can destroy the hedge property

A large literature tests whether Bitcoin can hedge portfolio risk, i.e. reduce the risk if added to a portfolio. Intuitively, given the extreme volatility and thus risk of Bitcoin and cryptocurrencies, the idea that Bitcoin is a hedge may be puzzling. Indeed, we show that for extreme levels of volatility, Bitcoin does not reduce the risk if added to a benchmark equity portfolio. This is not only true on average but also holds for sub-samples, including the COVID-19 crisis period. We conclude that a focus on correlations is not sufficient for extreme levels of volatility.

Revisiting disaster preparedness in coastal communities since 1970s in Bangladesh with an emphasis on the case of tropical cyclone Amphan in May 2020

The geographical location and development of Bangladesh means that the country is vulnerable to tropical cyclones. Cyclones are becoming more frequent and severe due to the effects of climate change [1]. Since 2007, more than 5,000 people have died, and damage runs into billions of dollars due to cyclones. This study aims to conduct an assessment of early preparation measures on cyclonic events since the 1970s with an emphasis on cyclone Amphan, May 2020 in Bangladesh. The study adopted a desk-based systematic survey of secondary literature. Technological advancement and better communication improve early warning significantly. However, the results show that the disaster preparedness to reduce the effect of cyclonic disaster has many limitations which need to be addressed, particularly by (i) involvement of mosques’ Imams (leaders) and school teachers in warning dissemination management since they are the most respected people in the society and, (ii) awareness of, and improved confidence in early warning and evacuation orders with (iii) gender issues addressed to facilitate equality in decision making. The quantity and quality of cyclone shelters need to be improved to ensure sufficient space. There appears to be a role for security forces in the emergency evacuation process as they have proven effective during Covid-19, where they were deployed to ensure that citizens did not leave home unnecessarily, which minimized the death toll. Continuous review and research on disaster risk reduction needs to be conducted, at all stages of cyclonic disaster management as increased severity and frequency of cyclones unavoidable for Bangladesh.