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A look at COVID-19 Data and the Importance of Testing

Since the outbreak of COVID-19 there have been over 1.6M confirmed cases and 97k deaths globally.[1] Some countries have fared better than others, which lends the question, what are the best actions a governmental entity can take to mitigate - or wholly eliminate - the spread of a virus like COVID-19 without creating long-lasting issues?
Adam Whalen


This study utilizes primary and secondary research to answer this question. The data indicates that a robust and systematic approach to testing the population, and then isolating cases, is the most effective option.

A Look at Five Countries

In order to come to this conclusion, we first aggregated infection, mortality, and testing data for five countries: Italy, Germany, South Korea, the United Kingdom, and the United States. The reason for choosing these entities was twofold. First, they largely enacted “social distancing” recommendations and/or measures within the same timeframe (between March 18th and March 25th).[2] Second, they had varying degrees of differences that aided in understanding how one country fared versus another. 

5 Countries - Cases & Deaths per Capita

In analyzing cases (infections) & deaths per capita, we found that Italy was hit the hardest by the outbreak, with the United States and the United Kingdom somewhere in the middle, and Germany and South Korea handling the outbreak very well. But as we mentioned, social distancing measures are largely equal, so what are the differentiating factors? The answer is the number of tests conducted on the South Korean and German population in the early days of the outbreak. This high number allowed them to catch asymptomatic and pre-symptomatic carriers before they could spread the disease. These findings are visualized in the graphs above and below and verified with secondary data sources.[3]

Tests Administered per Capita (Cumulative Sum)
Source:; retrieved 04/09/2020
Total Tests Delivered per Capita
Source:; retrieved 04/09/2020

Comparison between Seoul and New York City

For a more granular and comparable understanding of this finding, we focused on two cities for further analysis; Seoul and New York City. We chose these two cities because of the similar population sizes (9.78 M and 9.62 M) and density levels (16,000 sq km and 10,715 sq km). Further, Seoul and New York City share key differences which we can use to explain the varying levels of the outbreak. Those differences include such things as “mask” stigmas not being as prominent in Seoul, different degrees of policy response and action after the first outbreak was found, and the two cities testing capacity being different.

South Korea & New York State - Tests per Day
Source:; retrieved 04/09/2020 &; retrieved 04/09/2020

After 46 days since the first infection, Seoul had 200 confirmed cases of COVID-19. In New York City, it took just ten such days to reach this mark. As of April 5th, New York City had over 4k deaths, with Seoul yet to register a single one. These findings are visualized in the graphs above and below.

Seoul & NCY - Deceased Cases per Day
Source:; retrieved 04/09/2020 & NYC Department of Health on GitHub; retrieved 04/09/2020

So how did Seoul and South Korea succeed, where New York City and the United States failed?
The answer is testing, testing, and more testing. The South Korean government was “shipping thousands of kits daily (with the current ability to administer 100k a day),” and was able to source the initial outbreak to the city of Daegu, allowing them to refrain from lockdown orders in places like Seoul. Additionally, the region was “primed for the coronavirus emergency”[4] after the MERS outbreak in 2015 that gave them a playbook for how to handle an infectious disease. 

South Korea & New York State - Tests per Day
Source:; retrieved 04/09/2020 &; retrieved 04/09/2020

The Result of not being Able to Test

As a result of not being able to test in the early days, New York City has had to enact a full shelter-in-place order, with a moving end date that has left citizen confidence shattered. Seoul has primarily been able to remain open, and the economic impact is substantial. The unemployment rate for the United States and New York City is somewhere between 8 to 12%, whereas South Korea is close to its pre-outbreak levels of 3.3 percent.[5] Consumer confidence is also higher in South Korea, with the Composite Consumer Sentiment Index (CCSI) at 96.9 in March and 78.4 in April, compared to the United States which was 89.1 in March and 71 in April. This indicates South Korea’s population is ready to spend and engage with the economy. Of course, this is just looking at the economic impacts of the outbreak, but the medical numbers are just as staggering. The United States is seeing 95.4 cases and 2.6 deaths per capita, with South Korea as low as 19.8 cases and 0.3 deaths per capita. The underlying difference is still testing, with South Korea having administered 893 tests per capita, and the United States at 538.

Presentation of our findings.

Three Approaches of Response by Governmental Bodies

In conclusion, for a pandemic like COVID-19, there are three possibles approaches of response by governmental bodies. The first is herd immunity, which is not an off-taken tactic due to the severe loss of life that accompanies it. The second is social distancing measures, which can have severe economic impacts that can last long beyond the response, and in many cases, fail to mitigate deaths in the short-term. The last approach – and this is the one taken by South Korea – is an extensive system of testing and case isolation to track and remove virus-carriers from the population as soon as possible to mitigate outbreaks. As we consider the potential of another outbreak – or a second wave of COVID-19 – ramping up testing abilities is integral to handling the situation without extreme social distancing measures that spike unemployment rates and wreak havoc on society. While the United States has unique challenges that make replicating South Korea nigh impossible, South Korea’s approach seems to be the way to go as a model to prepare for further pandemics. 

This analysis was created as part of the COVID-19 challenge hosted by the Informations Systems Department at the David Eccles School of Business at the University of Utah.
Adam and I were awarded an “Honorable Mention.”
We made some minor adjustments to the text compared to the summary we turned in. The main sponsor of the event was Domo. Domos business intelligence platform was used to create the graphs.

More Information about the challenge can be found here.

[1], Retrieved: 2020/04/06
[2], Retrieved: 2020/04/06
[3], Retrieved: 2020/04/06
[4], Retrieved: 2020/04/06
[5], Retrieved: 2020/04/06

Header Image by 🇨🇭 Claudio Schwarz | @purzlbaum on Unsplash

Data Sources:
Country Case Data; retrieved 04/09/2020

Country Test Data; retrieved 04/09/2020

City Data
Seoul:; retrieved 04/09/2020
NYC: NYC Department of Health on GitHub; retrieved 04/09/2020

Testing Data
South Korea:; retrieved 04/09/2020
New York State:;retrieved 04/09/2020

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About Jonas Vitt

Born and raised in Karlsruhe, in the south-west of Germany, Jonas is currently pursuing a Master of Science in Business Analytics at the David Eccles School of Business at the University of Utah in Salt Lake City, UT. He finished his Bachelor’s degree in Business Administration with a focus on marketing at Pforzheim University in July 2019.

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