Chapter 7 Conclusion

In terms of our key findings, this project investigated COVID-19 related data in the global scale across countries as well as in the state-level within the United States. When we analyzed country data, we first identified representative countries using economic indicators as well as health indicators. We found that health indicators have a noticable negative correlation to the mortality rate related to COVID, whereas economic indicators did not pose much effect. Specifically, countries with high health indicators (better health and medical conditions) typically have lower COVID mortality rates. In this project, we looked at life expectancy. As we found that health indicators have more effect to COVID mortality rates, we constructed a d3 interactive scatter plot with different health indicators. For future directions, it would be interesting to filter countries based on other health indicators not covered in the project. You could use our interactive graph to select the variable of your interest.

For the state-level analysis, we categorized Democratic and Republican states to look at any differences in terms of response time for mitigation after the first confirmed case and effectiveness in mitigation measured by percentage decrease in people mobility in different settings. We found that even though the red states react faster than the blue states, it seems that the policies of the blue states are more effective than that of the red states as indicated by a larger percentage decrease in mobility. We also looked at the popularity of types of vaccination across all states. Among the three types of vaccines, Pfizer, Moderna, and Janssen, Pfizer’s vaccines are the most popular in each quarter of 2021.

In terms of limitations of the project, the health indicators for state-level within the USA is lacking. As they are shown to be important in the country-level, it would be interesting to gather more data to look at any differences within the USA. There can also be difference in the relationship, as reflected in a scatter plot, between two of the same health indicators for the state-level vs. the country level. Moreover, it would be beneficial to have the population statistic at the same time as the number of COVID cases. In this way, we can normalize our data by the population for each region to get a more accurate comparison of the effect. Last but not least, there are other data sets within the platform such as hospitalization records, vaccination facility accessibility, etc. which could be used for further analysis.