Theses and Dissertations

Date of Award


Document Type


Degree Name

Master of Science (MS)


Applied Statistics and Data Science

First Advisor

Dr. Tamer Oraby

Second Advisor

Dr. Zhijun Qiao

Third Advisor

Dr. Santanu Chakraborty


Coronavirus Disease (COVID-19), caused by the SARS-CoV-2 virus, is an infectious disease that quickly became a pandemic spreading with different patterns in each country. Travel bans, lockdowns, social distancing, and non-essential business closures caused significant economic disruptions and stalled growth worldwide in the pandemic’s first year. In almost every country, public health officials forced and/or encouraged Nonpharmaceutical Interventions (NPIs) such as contact tracing, social distancing, masks, and quarantine. Human behavioral decision-making regarding social isolation significantly impedes global success in containing the pandemic. This thesis focuses on human behaviors and cultures related to the decision-making of social isolation during the pandemic. Within a COVID-19 disease transmission model, we created a conceptual and deterministic model of human behavior and cultures. This study emphasizes the importance of human behavior in successful disease control strategies. Additionally, we introduce a back engineering approach to determine whether cultures are explained by the courses of COVID-19 epidemics. We used a deep learning technique based on a convolutional neural network (CNN) to predict cultures from COVID-19 courses. In this system, CNN is used for deep feature extraction with ordinary convolution and with residual blocks. Also, a novel concept is introduced that converts tabular data into an image using matrix transformation and image processing validated by identifying some well-known function. Despite having a small and novel data set, we have achieved an 80-95% accuracy, depending on the cultural measures.


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