COVID-19 Testing in Various Countries

I compared the emphasis on testing between various countries, over the seven month period from December 31st 2019 to July 30th 2020. Many countries did not report cases in the early months, but the mean comparison over the extended period is insightful about policy. Testing requires government funding, and one confirmatory scatter plot could be total_tests vs. gdp_per_capita for all the countries, to see if there is a linear association between higher gdp_per_capita and a higher number of tests administered. Poorer countries cannot be blamed for not testing everyone. Even if they did, the health care facilities are not there for everyone, and it would be far better to take care of oneself at home.

The first scatterplot displayed below in Figure 1, shows three outliers – countries, that have tested about 5 million (50 lakh) citizens – United States, Russia, and India. Most countries have tested fewer than 40 lakh citizens; even those with high GDP per capita of over $45,000.

Figure 1 – GDP per capita vs. Total Tests

RankLocationMean (Total Tests) in lakhs
1United States168,58,182
4United Kingdom35,94,482

Table 1Countries who have administered Total Tests in excess of 25 lakhs

For the rest of the world, I chose 68 countries, whose GDP per capita is less than $45,000, and who have tested less than 40 lakh citizens. The plot in Figure 2, has two components. There is an upward linear trend of increased testing with higher GDP per capita, that is indicated by the red dots. The variable meantt represents the mean of total tests performed and is represented along the y-axis. These countries have been able to mobilise and ramp up health care workers and testing. There is also a horizontal band of countries, indicated by the blue dots, that are not testing commensurate with their high GDP per capita. These countries have tested below 10 lakh citizens. This may be due to the unavailability of qualified medical workers, or lack of kits, or some other reason.

Figure 2 – Linear Association

The test positivity rate (TPR) is the fraction of the tested population, that has been diagnosed as COVID-19 positive. This can be an indicator of how much the infection has spread through the population. Data for the period up to July 30th was available for 87 countries and was averaged out. The histogram below in Figure 3, shows that TPR is less than 20% for almost all of them, and is less than 5% for most of the countries. Only for four countries, they are above 20%. The worst affected countries are Peru (67.5%) and Brazil (62.9%). Ecuador has 51.6% TPR. Two more badly affected countries, are Bolivia and Panama which have a TPR of 28.1% and 20.3% respectively. These are based on 7 months of data, and a seven-day rolling average may highlight other countries.

Figure 3 – Test Positivity Rate for 87 countries

Caveat Emptor: The charts obtained, and conclusions are drawn are based on particular assumptions and statistical techniques applied and may contradict official reports that are based on other more standard procedures;  These experiments with data are only to further refine the data exploration, towards more accurate and definitive conclusions.

Dr. Badri Toppur
Associate Professor, Rajalakshmi School of Business, Chennai
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