Socio-economic, cultural, and environmental influences on COVID-19 pandemic outcome -- excess mortality

DESCRIPTION:

This is a capstone research project for the Certificate in Applied Data Science (CADS) at my undergraduate institution, Wesleyan University, on the topic of "Understanding the Variances in COVID-19 Pandemic Outcome - Excess Mortality - with Social, Cultural, and Environmental Factors".

• AUTHOR: Jiner Zheng
• FACULTY SPONSOR: Prof. Maryam Gooyabadi

Useful Code Sources:

• DTW.Rmd contains code for data cleaning, data management, functions of producing excess deaths using ARIMA/GARCH, & implementations of hierarchical clustering analyses on Time Series data based on Euclidean distances and Dynamic Time Warping (DTW) distances.

• K-medoids.Rmd contains code for implementing K-Medoids clustering on mix-typed data with computations of the Gower distance.

Note: you can also set up the environment using JZ-capstone.Rproj in R.

Other Materials:

• JZ-capstone.pdf contains my presentation slides outlining our literature reviews, measures and analytical methods, findings, and recommendations.

• JZ_CADS_capstone_spring2022.pdf is the final paper of this presented work.