Different Countries’ COVID-19 trend and policy

This is the final project of IS590PR, this project is Type II

Purpose

By finding out the relation between each country’s policies and their COVID-19 confirmed rate change, to know which policy, treatment would be the helpful to control the outbreak

Data Source

https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset
Google Trend

Hypothesis

(1) Mass test could help decrease the outbreak efficiently
(2) Countries that people does wearing mask would have lower rate of confirmed number

Method

Using linear regression to find the obvious slope change Using data visualization to choose countries that have interesting trend and do deeper investigation

Result

Germany

• Confirmed trend

• Mask google trend

Start doing more than 100,000 tests daily at early April
daily rate of confirmed number: 2990 -> 1780

We use German word --- maske to get the google trend data in Germany.
We can see that started from early April, the awareness of wearing mask is getting higher in Germany, and thus the confirmed number getting flatten afterwards.

Korea

• Confirmed trend

• Mask google trend

By mid-March, 270,000 South Koreans had been tested
daily rate of confirmed number: 482 -> 110 -> 21

We use Korean word --- 마스크 to get the google trend data in South Korea.
We can see that started from mid March, the awareness of wearing mask is getting higher in South Korea, and thus the confirmed number getting flatten afterwards.

Conclusion

Hypothesis that mass test would be helpful is valid for Germany, Korea
Hypothesis that wearing mask would be helpful is valid for Germany, Korea