Country Clustering Analysis of COVID-19 Pandemic Dynamics: Insights and Implications for Future Preparedness
Abstract: The COVID-19 pandemic has presented diverse challenges to nations worldwide, necessitating a comprehensive understanding of countries' varied responses to the crisis. This paper conducts a meticulous analysis of multiple features to explore the dynamics observed during the pandemic, including epidemiological statistics, demographic indicators, economic metrics, geographical information, health indicators, mobility patterns, weather data, and government responses.
Using data sourced from the Google Health COVID-19 Open Data Repository, covering over 20,000 locations globally, this study employs clustering techniques to categorize countries into three distinct clusters. Each cluster exhibits unique characteristics, providing valuable insights into their respective pandemic experiences. Additionally, the paper offers a thorough examination of the factors influencing cluster performance, shedding light on the determinants of success or challenges faced by countries during the crisis.
The research outcomes serve as a valuable resource for public health professionals, researchers, and policymakers, facilitating a better understanding of pandemic management. By discerning patterns across different clusters, this study aids in formulating effective strategies and policies, with potential implications for bolstering global preparedness in the event of future health emergencies.
Keywords: COVID-19 pandemic, country clustering, epidemiological analysis, pandemic dynamics, public health, global preparedness, government response, data analysis, pandemic management, crisis response.
If you find this analysis valuable and wish to use or adapt it for your own projects, feel free to do so! To replicate the analysis, clone this GitHub repository to your local machine. In the spirit of open collaboration, we kindly ask that you acknowledge and cite the original work in your own publications or projects. Include the title of the original work, your name as the author, the repository URL, the publication year, and any relevant identifiers such as a DOI. Your citation helps recognize the effort and time put into creating this analysis. Thank you for your interest and happy analyzing!