Assessing flooding extent and potential exposure to river pollution from urbanizing peripheral rivers within Greater Dhaka watershed (preprint)

Greater Dhaka area is home to large industrial clusters that are driving economic growth and the poverty reduction efforts of Bangladesh. These clusters are located around peripheral rivers- Turag, Buriganga, Dhaleswari, Balu, Shitalakhya, Bangshi, and Tongi-Khal, which are important for water transport, environment, and eco-systems where flooding of floodplains in monsoon is an integral part. The economic growth with minimal environmental regulations had led to severe degradation of the rivers and floodplains environment affecting livelihood, health and well-being of the people. Monsoon time exposure to polluted water is yet to be studied and addressed scientifically. This study looked into the water quality and flooding situation of Greater Dhaka for two successive monsoons through extensive river sampling coupled with estimation of flooded area and exposed population through use of remote sensing tools. Sentinel 1’s Synthetic Aperture Radar (SAR) images are used for flood mapping considering cost-effectiveness and its advantages for data scarce regions. The estimated exposed population to flooding was over 668 thousand in 2019 and over one million in 2020 where the water quality ranged from highly polluted to moderately polluted. These point to a need for taking monsoon time exposure seriously in policy making process and design appropriate interventions.

Seroprevalence of IgG Antibody against SARS-CoV-2 Nucleocapsid protein and Associated Risk Factors (preprint)

Estimation of antibody development against SARS-CoV-2 is essential means for understanding the immune response against the virus. We reported IgG antibody development status against Nucleocapsid protein of the virus and compared with lifestyle (health and food habits), co-existing diseases, vaccination and COVID-19 infection status. ELISA (Enzyme Linked Immunosorbent Assay) was performed to assess IgG antibodies targeted against the Nucleocapsid protein of SARS-CoV-2 in participants (n=500). In this seroprevalence study, serological data were estimated for a period of 10 months in the participants who were aged 10 years and above. Sociodemographic and risk factors related data were collected through a written questionnaire and chi-square test was performed to determine the association with seropositivity. The overall seroprevalence of anti-SARS-CoV-2 antibodies among the study subjects was 47.8%. Estimates were highest among the participants of 21-40 years old (55.1%), and lowest in older aged (>60 years) participants (39.5%). Among the Sinopharm vaccinated individuals 81.8% had developed anti-Nucleocapsid antibody. Physical exercise and existence of comorbidities like hypertension and diabetes were the distinguishing factors between seropositive and seronegative individuals. Seropositivity rate largely varied among symptomatic (67%) and asymptomatic (33.1%) COVID-19 infected participants. The findings suggest that residents of Dhaka city had a higher prevalence of anti-nucleocapsid antibody in the second year of the pandemic. This indicates the improvement of immunological status among the population. Finally, the study emphasizes on maintaining active and healthy lifestyle to improve immunity. However, the absence of IgG antibodies in many cases of COVID-19 infected individuals suggests that antibodies wane with time.

Behavioural changes in air-conditioner use owing to the COVID-19 movement control order in Malaysia.

Remote work (working from home) became a norm rather than an exception for the global workforce during the COVID-19 pandemic, influencing every facet of life in both positive and negative ways. The stringent action of the Malaysian government in enacting the Movement Control Order (MCO) motivated the investigation of its impact on the energy consumption behaviour of working people regarding air-conditioner (AC) use. To this end, this study conducted a cross-sectional survey through an online platform. An ordinal logistic regression model (ORL) was used to analyse the collected data of 1873 respondents to determine the factors influencing the ordinal variable of interest, AC-usage behaviour during remote work. Next, the variable with unordered categories, the MCO-induced change in AC-usage behaviour, was analysed using a multinomial regression model (MLT) to identify the potential determinants. Finally, a reason analysis unveiled aspects behind the transition in AC use during remote work. This study identified stopping AC use during remote work despite using it at the office before the MCO period as the most significant change in AC-usage behaviour due to MCO. This change was frequently adopted by people with medium-level incomes and high electricity bills. By contrast, participants unfamiliar with their electricity bill were most likely to start AC use during remote work, although they did not use it before the MCO. Participants working remotely in the communal spaces of their houses preferred to stop using ACs during MCO compared to private room users. Furthermore, age group and ethnicity significantly influenced AC-usage behaviour in remote work and changes in such demeanours. These findings recommend policy interventions to expedite limited AC use for a sustainable energy sector, even during future climatic emergencies .

Indoor Air Quality and Health Outcomes in Employees Working from Home during the COVID-19 Pandemic: A Pilot Study

Indoor air quality (IAQ) has a substantial impact on public health. Since the beginning of the COVID-19 pandemic, more employees have worked remotely from home to minimize in-person contacts. This pilot study aims to measure the difference in workplace IAQ before and during the pandemic and its impact on employees’health. The levels of fine particulate matter (PM2.5) and total volatile organic chemicals (tVOC) were measured in the employees’offices before the COVID-19 pandemic and at homes while working from home during the pandemic using Foobot air monitors. The frequencies of six sick building syndrome (SBS) symptoms were evaluated at each period of monitoring. The result showed PM2.5 levels in households while working from home were significantly higher than in offices while working at the office for all participants (p < 0.05). The PM2.5 levels in all households exceeded the health-based annual mean standard (12 µg/m3), whereas 90% of offices were in compliance. The tVOC levels were all below the standard (500 µg/m3). We also found a higher frequency of SBS symptoms were observed while working from home as the IAQ was worse at home. This study suggested that working from home might have a detrimental health impact due to poor IAQ and providing interventions to remote employees should be considered.

Prevalence of anxiety and depression in South Asia during COVID-19: A systematic review and meta-analysis.

INTRODUCTION: The COVID-19 pandemic has impacted biopsychosocial health and wellbeing globally. Pre-pandemic studies suggest a high prevalence of common mental disorders, including anxiety and depression in South Asian countries, which may aggravate during this pandemic. This systematic meta-analytic review was conducted to estimate the pooled prevalence of anxiety and depression in South Asian countries during the COVID-19 pandemic. METHOD: We systematically searched for cross-sectional studies on eight major bibliographic databases and additional sources up to October 12, 2020, that reported the prevalence of anxiety or depression in any of the eight South Asian countries. A random-effects model was used to calculate the pooled proportion of anxiety and depression. RESULTS: A total of 35 studies representing 41,402 participants were included in this review. The pooled prevalence of anxiety in 31 studies with a pooled sample of 28,877 was 41.3% (95% confidence interval [CI]: 34.7-48.1, I 2 = 99.18%). Moreover, the pooled prevalence of depression was 34.1% (95% CI: 28.9-39.4, I 2 = 99%) among 37,437 participants in 28 studies. Among the South Asian countries, India had a higher number of studies, whereas Bangladesh and Pakistan had a higher pooled prevalence of anxiety and depression. No studies were identified from Afghanistan, Bhutan, and Maldives. Studies in this review had high heterogeneity, high publication bias confirmed by Egger's test, and varying prevalence rates across sub-groups. CONCLUSION: South Asian countries have high prevalence rates of anxiety and depression, suggesting a heavy psychosocial burden during this pandemic. Clinical and public mental health interventions should be prioritized alongside improving the social determinants of mental health in these countries. Lastly, a low number of studies with high heterogeneity requires further research exploring the psychosocial epidemiology during COVID-19, which may inform better mental health policymaking and practice in South Asia.

Prevalence of anxiety and depression in South Asia during COVID-19: A systematic review and meta-analysis (preprint)

Introduction: The COVID-19 pandemic has impacted biopsychosocial health and wellbeing globally. Pre-pandemic studies suggest a high prevalence of common mental disorders, including anxiety and depression in South Asian countries, which may aggravate during this pandemic. This systematic meta-analytic review was conducted to estimate the pooled prevalence of anxiety and depression in South Asian countries during the COVID-19 pandemic. Method: We systematically searched for cross-sectional studies on eight major bibliographic databases and additional sources up to October 12, 2020, that reported the prevalence of anxiety or depression in any of the eight South Asian countries. A random-effects model was used to calculate the pooled proportion of anxiety and depression. Results: A total of 35 studies representing 41,402 participants were included in this review. The pooled prevalence of anxiety in 31 studies with a pooled sample of 28,877 was 41.3% (95% confidence interval [CI]: 34.7-48.1, I2 = 99.18%). Moreover, the pooled prevalence of depression was 34.1% (95% CI: 28.9-39.4, I2 = 99%) among 37,437 participants in 28 studies. Among the South Asian countries, India had a higher number of studies, whereas Bangladesh and Pakistan had a higher pooled prevalence of anxiety and depression. No studies were identified from Afghanistan, Bhutan, and Maldives. Studies in this review had high heterogeneity and varying prevalence across sub-groups. Conclusion: South Asian countries have high prevalence rates of anxiety and depression, suggesting a heavy psychosocial burden during this pandemic. Clinical and public mental health interventions should be prioritized alongside improving the social determinants of mental health in these countries. Lastly, a low number of studies with high heterogeneity requires further research exploring the psychosocial epidemiology during COVID-19, which may inform better mental health policymaking and practice in South Asia.

Low-Cost Remote Sensing IoT based Smartphone Controlled Robot for Virus Affected People (preprint)

This modern era is the era of IoT and Robotics. In current times the whole world is suffering from the Covid-19 pandemic. This paper represents an IoT based Robot that will help the virus affected people. This robot will be able to collect data from virus affected people and send those data to a cloud database. The collected data can be analyzed from the cloud platform. The robot is designed as a low-cost device and can be controlled via smartphones. Bluetooth sensors, temperature sensors, and other sensors are used to collect data from the patient and to control the robot. Wi-fi communication is used to send the collected sensor data to cloud database. The prototype is successfully worked and showed good results.