## 3 Database Building  
The following section outlines the database architecture established for the correlation analysis component of this study. It is a dynamic, time-based database that aggregates records from various open-database sources across the globe, encompassing data from numerous countries. The primary sources were carefully selected based on their high level of availability, daily updates, and global reach, ensuring the most current and consistent data for analysis. These primary sources encompass the following:  
* GitHub, which is a provider of Internet hosting for software development ([[https://github.com/](https://github.com/)]([https://github.com/](https://github.com/)), accessed on 1 November 2021);
* Eurocontrol, which is a pan-European civil military organization dedicated to supporting European aviation ([[https://www.eurocontrol.int/](https://www.eurocontrol.int/)]([https://www.eurocontrol.int/](https://www.eurocontrol.int/)), accessed on 1 November 2021);
* Oxford government responses ([[https://covidtracker.bsg.ox.ac.uk](https://covidtracker.bsg.ox.ac.uk)]([https://covidtracker.bsg.ox.ac.uk](https://covidtracker.bsg.ox.ac.uk)), accessed on 1 November 2021);
* Apple mobility trends ([[https://covid19.apple.com/mobility](https://covid19.apple.com/mobility)]([https://covid19.apple.com/mobility](https://covid19.apple.com/mobility)), accessed on 1 November 2021), available upon request;
* Epidemiology open data, community mobility open data ([[https://ourworldindata.org/covid-google-mobility-trends](https://ourworldindata.org/covid-google-mobility-trends)]([https://ourworldindata.org/covid-google-mobility-trends](https://ourworldindata.org/covid-google-mobility-trends)), accessed on 1 November 2021);
* Geography, healthcare system, and demographics data. Table 1 presents the detailed list of open sources selected for the database construction and daily record fulfillment. A brief description and the URL gives the reader more detailed info and a direct link to collect and update new data. The data sources at our disposal can be categorized as \"static\" and \"dynamic\" datasets. Figure 1 exemplifies the merging process of the datasets, including geography, demographics, and health-related indicators. We make a clear distinction between time-dependent feature sets and time-invariant feature sets. The former pertains to the epidemiology waves, government restrictions, and their consequential impacts on the mobility of inhabitants. The latter elucidates the geographical, demographical, and infrastructural attributes of the countries under observation. Our specific focus lies in the healthcare system, encompassing factors such as life expectancy, the number of hospital beds, and the availability of nursing staff, among others. Appendix A presents a detailed description of the database structure and features. In the context of a given country, the term \"wave\" denotes the period of a pandemic disease characterized by a substantial increase in new cases, followed by a subsequent decrease or stabilization. Table 2 provides a comprehensive account of these periods for the specific set of countries under scrutiny for correlation and comparative analysis, as delineated in the subsequent sections.