No abstract

Objectives This study aimed to determine the impact of the COVID-19 pandemic on the psychological, mental health and quality of life among Bangladeshi residents. Study design A purposive cross-sectional study of quality of life during the COVID-19 pandemic was performed. Methods Respondents completed a modified questionnaire that determined the Impact of Event Scale (IES), indicators of psychological distress impact, impact on government strategies, awareness and lifestyles, and impact on expectation of quality life change. A total of 465 (male = 330 and female = 135) respondents participated in this study. Results The overall mean age of respondents was 28.42 ± 7.07 years, and 63.4%, 44.1% and 50.3% were unmarried, were in the middle-income family group and had a masters or PhD qualification, respectively. The overall mean IES score of respondents was 80.89 ± 8.91, which reflects a stressful impact of the COVID-19 pandemic on physical and mental health problems. Only 27.75% of respondents had an IES score ≥75. More than half of respondents (57.8%) reported that they did not feel lonely and hopeless. In terms of preventative measures, the majority of the respondents (80.2%) reported that they did not wash their hands frequently with soap and sanitiser for at least 20 s to reduce spread of the virus. During the pandemic, more than half of the respondents (56.8%) claimed that they faced serious problems in education. Conclusions The ongoing COVID-19 pandemic has resulted in significant mental and physical health problems.

Humidity (atmospheric moisture) is an important atmospheric component and has significant influence on plant growth and development. The rate of growth and the form that a plant attains is controlled by humidity. The present study is an attempt to analyze the seasonal humidity’s of Bangladesh by employing appropriate statistical techniques. The main objective of this study is to examine humidity over time in Bangladesh and find a suitable model for forecasting. This study utilizes humidity data from Bangladesh Meteorological Department (BMD), recorded at 6 divisional meteorological stations for the period of 1976 to 2015. This study found that annual average humidity of Bangladesh is 78.88%. Initially data set is checked for whether it is stationary or not through Augmented Dickey Fuller test. Data was found non-stationary but it was transformed to stationary after taking first difference. Then seasonal ARIMA model was built using Box and Jenkins approach. After examining of all diagnostic procedures, ARIMA (2,0,1)(2,1,1)12 model has been identified as an appropriate model for forecasting  60 months (2016-2020) seasonal humidity.

No abstract