Meta-analysis • Biostatistics • Bayesian Statistics • Econometrics • Machine learning

Prevalence and Seroprevalence of Dengue Infection: A Meta-analysis

July, 2023 - Present

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Influence of Social Factors on Perceptions of Climate Knowledge: A Case Study of Khulna City Corporation, Bangladesh

August, 2022 - January, 2023

Climate change has emerged as a critical global issue, necessitating concerted efforts from policymakers to establish climate justice and foster green development. Bangladesh, positioned in the global south, stands as one of the most vulnerable countries to climate change impacts. Understanding community perceptions and knowledge regarding climate-related issues is essential for effective mitigation and adaptation strategies. However , comprehensive studies addressing these aspects are yet lacking from this country. This study, therefore, focuses on Khulna City Corporation in Bangladesh, one of the worst victims of climate change impacts, to assess the populace's level of basic climate change knowledge and their awareness of initiatives undertaken by stakeholders. Furthermore, it examines how social factors such as gender, age, religion, profession, and location shape individuals' perceptions of climate change. The study also explores how governmental organizations (GOs), non-governmental organizations (NGOs), and international non-governmental organizations (INGOs) could utilize this information to achieve climate justice in Bangladesh. This study shows that many residents in the Khulna City Corporation lack basic understanding of climate change causes and solutions. Additionally, they are not concerned with any activities taken by different groups to address this issue.

The causes and Consequences of Road Accident in Bangladesh

April, 2022 - January, 2023

One of Bangladesh’s biggest issues right now is road accidents. It is the cause of many fatalities and injuries that negatively impact human life. The main objective of this research is to identify the reasons behind the increasing road accidents in Bangladesh. In this research, data on road accidents for the years 2006 to 2020 in Bangladesh were collected by reading daily newspapers. The technique of generalized linear models (GLMs) were used in this study. Because of the Poisson regression model’s overdispersion, a Negative Binomial regression model was applied for the purpose of the best-suited model. This study has found that the number of road accidents in Bangladesh was increasing and that the majority of them occurred during the winter and rainy seasons. A driver’s careless driving of the vehicle accounts for 62.117% of all road accident causes, whereas loss of control of the vehicle was responsible for 20.82% of all accidents. It was found in this study that the majority of accidents took place in divisional and highly populated cities, with Dhaka having the highest frequency. On the basis of correlation and regression analysis, it was determined that population growth is the root cause of road accidents. Population growth could explain the 31.42% variation in the number of road accidents. The causes of road accidents were found to have a to have a significant effect on road accidents on the basis of the Poisson regression model. As there exists overdispersion in the Poisson regression model, a Negative Binomial regression model has been found to be the best-suited technique for modeling causes of road accidents.

Ahsan, J., Roy, S., & Huq, A. S. (2021). An In-depth Estimation of Road Traffic Accident Cost in Bangladesh, International Conference on Sustainable Development in Technology for 4th Industrial Revolution 2021, 2021, 12–13.