Riad Hossain

Flood is a frequent experience for the people living in Bangladesh, especially in the south-western region. But due to its complexity and multidisciplinary nature, flood management remains a very difficult task. This research focused on finding the most vulnerable areas to flooding for each polder within the Khulna and Satkhira districts since those areas can be identified as one of the most vulnerable areas to flooding. Water level data from fourteen stations of seven rivers (Sibsa, Rupsa-Pasur, Kobadak, Bhadra, Kobadak, Ichamati (Western Border), Betna-Kholpetua, and Satkhira Khal) were analyzed to calculate water levels for 2, 5, 10, 25, and 100-year return period applying normal distribution, extreme value type-I (EV-I), and log person type-III (LP-III) distribution methods. The EV-I distribution method was showing the best fit. The study revealed that station SW243 (Rupsa-Pasur River) in the Dacope region has the most extreme water level, station SW259 (Sibsa River) has the second-highest water level, and station SW254.5 (Satkhira Khal) in Satkhira Sadar has the third-highest water level for the return period of 100 years. A flood inundation map was prepared using the EV-I method’s 10-year return period value. The Analytic Hierarchy Process (AHP) was used to demonstrate the polders’ vulnerability depending on several factors. Overall, polder15 (Ghubra, Satkhira) is the most vulnerable polder, while polder 33 and polder 32 respectively are the second and third most vulnerable polders for flooding, both located in the Dacope region.

A novel coronavirus disease known as COVID-19 has spread globally and brought a public health emergency to all nations. To respond to the pandemic, the Bangladesh Government imposed a nationwide lockdown that may have degraded mental health among residents, in particular, university students and working professionals. We examined clinically significant anxiety levels with the Generalized Anxiety Disorder (GAD-7) scale and perceived stress levels with the Perceived Stress Scale (PSS-4) in an online cross-sectional study with 744 adults. Approximately 70% of respondents were afflicted with clinically significant anxiety levels, and more than 43.82% were afflicted with moderate or high perceived stress levels. Multivariate logistic regression models showed that postgraduates (OR = 2.78, 95% confidence interval [CI] = 1.03–8.75, p < 0.05) were more likely to experience anxiety than their student counterparts. No such differences emerged for working professionals, however. Living with family members compared to living alone was a risk factor for perceived stress among working professionals (OR = 4.05, 95% CI = 1.45–11.32, p < 0.05). COVID-19 stressors such as financial hardship (OR = 1.84, 95% CI = 1.11–3.05, p < 0.05) and worries of family members’ health (OR = 1.84, 95% CI = 1.12–2.99) were risk factors for anxiety among students. Questionable social media news exposure (OR = 2.99, 95% CI = 1.13–7.92, p < 0.05) contributed to the development of mental stress among working professionals. These findings confirm that effective initiatives and proactive efforts from concerned authorities are necessary to cope with the mental health correlates of the COVID-19 pandemic, including in developing contexts such as Bangladesh.

Although Bangladesh has been experiencing frequent flooding that has made colossal damages to lives and properties, overseeing floods remains a difficult task. Due to the complexity, scale, and multidisciplinary nature of flood management, it is a multisectoral activity. Khulna and Satkhira districts, located in the south-western region of Bangladesh, are considered as one of the most vulnerable areas to flooding due to their economic potential, demographic makeup, and adaptive capacity of the population. This research focused on finding the most vulnerable areas to flooding for each polder within the study area. Water level data from fourteen stations of seven rivers (Sibsa, Rupsa-Pasur, Kobadak, Bhadra, Kobadak, Ichamati (Western Border), Betna-Kholpetua, and Satkhira Khal) were analyzed to calculate water levels for 2, 5, 10, 25, and 100-year return period applying normal distribution, Extreme Value Type-I (EV-I), and Log Person Type- III (LP-III) distribution methods. The EV-I distribution method was showing the best fit. The study revealed that station SW243 (Rupsa-Pasur river) in the Dacope region has the most extreme water level, station SW259 (Sibsa river) has the second-highest water level, and station SW254.5 (Satkhira Khal) in Satkhira Sadar has the third-highest water level for the return period of 100 years. A flood inundation map was prepared using the EV-I method's 10-year return period value. The Analytic Hierarchy Process (AHP) was used to demonstrate the polders' vulnerability depending on several factors. Overall, polder15 (Ghubra, Satkhira) is the most vulnerable polder, while polder 33 and polder 32 respectively are the second and third most vulnerable polders for flooding, both located in the Dacope region.

Unverified information concerning COVID-19 can affect mental health. Understanding perceived trust in information sources and associated mental health outcomes during the COVID-19 pandemic is vital to ensure ongoing media coverage of the crisis does not exacerbate mental health impacts. A number of studies have been conducted in other parts of the world to determine associations between information exposure relating to COVID-19 and mental health. However, the mechanism by which trust in information sources may affect mental health is not fully explained in the developing country context. To address this issue, the present study examined associations between perceived trust in three sources of information concerning COVID-19 and anxiety/stress with the mediating effects of COVID-19 stress in Bangladesh. An online cross-sectional study was conducted with 744 Bangladeshi adults between 17 April and 1 May 2020. Perceived trust in traditional, social, and health media for COVID-19 information, demographics, frontline service status, COVID-19-related stressors, anxiety (GAD-7), and stress (PSS-4) were assessed via self-report. Linear regression tested for associations between perceived trust and mental health. Mediation analyses investigated whether COVID-19-related stressors affected perceived trust and mental health associations. In fully adjusted models, more trust in social media was associated with more anxiety (B = 0.03, CI = 0.27–0.97) and stress (B = 0.01, CI = −0.34–0.47), while more trust in traditional media was associated with more anxiety (B = 0.09, CI = 0.17–2.26) but less stress (B = −0.08, CI = −0.89–0.03). Mediation analyses showed that COVID-19-related stressors partially explained associations between perceived trust and anxiety. These findings suggest that trusting social media to provide accurate COVID-19 information may exacerbate poor mental health. These findings also indicate that trusting traditional media (i.e., television, radio, and the newspaper) may have stress-buffering effects. We recommend that responsible authorities call attention to concerns about the trustworthiness of social media as well as broadcast positive and authentic news in traditional media outcomes based on these results.

Vaccination is undoubtedly one of the most effective strategies to halt the COVID-19 pandemic. The current study aimed to investigate the acceptance of COVID-19 vaccination and its associated factors using two health behavior change frameworks: the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). A total of 639 Bangladeshi adults (mean age: 24 years) participated in a cross-sectional online study between July and August 2021. The questionnaire covered questions regarding vaccine intentions, sociodemographic features, health status, perceived trust in/satisfaction with health authorities, reasons for vaccine hesitancy, and factors related to the health behavior change frameworks. Hierarchical logistic regression was employed to determine associations between these predictors and vaccine acceptance. The intention to get a COVID-19 vaccination was expressed among 85% of the participants. In fully adjusted models, students and respondents with more normal body weights reported higher intentions to get vaccinated. Respondents were also more likely to seek vaccination if they reported greater levels of perceived susceptibility, benefits, and cues to action, as well as lower levels of barriers and self-efficacy. Fear of future vaccine side effects was the most common reason for COVID-19 vaccine hesitancy and was expressed by 94% of the vaccine-hesitant respondents. These factors should be considered by health authorities in Bangladesh and perhaps other countries when addressing the plateauing COVID-19 vaccination rates in many populations.

The COVID-19 pandemic has been very destructive to and compromised the functioning of all nations' public health systems. In the absence of a vaccine, healthcare workers have been employed to relentlessly fight against COVID-19. The psychological status of healthcare workers during the pandemic in countries with limited resources, notably Bangladesh, remains unclear. The present study aimed to investigate the psychological states of frontline and non-frontline Bangladeshi healthcare workers during the early stages of the COVID-19 outbreak. An online cross-sectional study was conducted from May 5 to 31, 2020 with 203 respondents. Psychological states were measured with a self-reported numerical scale of fear, the Generalized Anxiety Disorder (GAD-7) scale, and the Patient Health Questionnaire (PHQ-9). The prevalence rates of fear, anxiety, and depression were 60.6, 71.9, and 55.2%, respectively. Compared to non-frontline workers, frontline workers reported higher rates of anxiety (79.0 vs. 67.2%) and depression (65.4 vs. 48.4%). Multivariate logistic regression models showed that working in a public institution, being employed for <5 years, and being over-worked were risk factors for developing psychological distress. Our findings emphasize the need for timely psychological interventions to support the mental well-being of healthcare professionals in Bangladesh.

The COVID-19 pandemic has increased the risk of global public health and has the potential to cause severe food and water insecurity due to economic recession during lockdown for people living in low-middle income countries like Bangladesh where capital resources are scarce. There is growing evidence that household food and water insecurity has been associated with poor psychological outcomes. The objective of this study was to determine the association between household food and water insecurity with mental health and whether these differed among urban-rural households. A cross-sectional online survey was conducted with 545 participants immediately after the COVID-19 lockdown period in Bangladesh (August 1-September 30, 2020). Household food and water security were determined using a 9-item Household Food Insecurity Access Scale (HFIAS) (score range 0-27) and a 12-item Household Water Insecurity Experiences (HWISE) scale (score range 0-36), respectively. The Perceived Stress Scale (PSS) was used to evaluate mental health. Multivariable logistic regression examined the association between household food and water insecurity with perceived stress, adjusting socioeconomic characteristics. An urban-rural stratified analysis was also performed. About 72.84% (397) respondents reported high stress and more than 70% of households suffered from food and water insecurity during the lockdown period. After adjusting covariates, logistic regression model results show that food insecurity was associated with a 1.07-point increase in high perceived stress (OR=1.07, 95% CI=1.01-1.11, p<0.01) while water insecurity was associated with 1.03 times greater odds of high perceived stress (OR=1.03, 95% CI=0.93-1.23, p<0.05). In stratified analysis, only food insecurity was associated with high perceived stress in the urban household (OR=1.08, 95% CI=1.00-1.11, p<0.05). However, none of the household insecurity was associated with perceived stress in rural households. Interventions that promote equal access to resources for low-income individuals will likely to be more effective to alleviate economic burden of pandemic.

Wetland ecosystems provide a wide range of ecosystem services that are often neglected in the decision-making process, resulting in the overexploitation of resources. Quantification of the services generated by this dynamic landscape is critical to developing appropriate conservation priorities for wetland management. The biggest challenge is the lack of adequate knowledge on the economic value of wetland services and proper understanding of potential revenue opportunities associated with it. This chapter introduces an application of an open source tool for estimating the value of freshwater wetland ecosystem services. The Semi-Automatic Classification Plugin (SCP) integrated into the management infrastructure of Quantum Geographic Information Systems (QGIS) can facilitate the supervised classification of multi-spectral satellite images. Thus, a case study of Beel Dakatia, a freshwater wetland of southwest coastal Bangladesh, has been demonstrated to quantify the ecosystem services value (ESV) using the “value transfer method.” This study estimated the total ESV of the wetland by combining Landsat-8 images using land use land cover (LULC) datasets of the year 2020 with its previously published global value coefficients. The LULC was prepared using SCP of QGIS. The study estimated a total ESV of US$42.16 million for Beel Dakatia. The study also found that the more natural ecosystems, e.g., water body and vegetation, contributed the highest (96%) amount of ESV. Regarding ecosystem functions, water regulation contributed the highest (56.13%) ESV, followed by water supply (21.85%) and waste treatment (7.21%). These findings will help policymakers to adopt a sustainable conservation policy for the coastal freshwater wetlands of Bangladesh.