Data | In the battle against COVID-19, severity of lockdown matters less than testing rates

Stranded people being screened at Chennai Central before boarding the Shramik Special to Manipur on May 10.

Stranded people being screened at Chennai Central before boarding the Shramik Special to Manipur on May 10.   | Photo Credit: R. Ragu

It has been nearly a month and a half since India enforced a stringent lockdown to arrest the COVID19 outbreak. Cases have recently continued to rise in the country at a relatively fast pace, even as the lockdown has brought the economy to its knees.

There were other countries that also enforced stringent lockdowns in order to implement a physical distancing strategy that will halt the increase in COVID19 infections, but there were significant variances in testing rates conducted across such countries. How does higher testing, stringent lockdown, both or a lack of both influence outcomes across countries, is the question that we seek to answer in this Data Point article.

To measure which approach led to better outcomes, we analysed four parameters – tests per million population, stringency of the lockdown, case doubling time and volume of cases. The parameters were compared on three specific dates March 25, April 15 and May 4 (the dates on which India announced or extended its nation-wide lockdown) for 46 nations which had maintained consistent data in this period.

How to read the charts

The graphs plot tests conducted per million people against how stringent a country’s lockdown was as on March 25, April 15 and May 4. Each circle corresponds to a country. The colour red for the circle denotes a case doubling time of <16 days; yellow circle denotes a doubling time of 16-35 days; green circle denotes a doubling time of > 35 days on that date.

The size of the circles correspond to the absolute number of confirmed COVID-19 cases on that date. Stringency is calculated based on 17 indicators such as school closures and restrictions in movement. The index was created by the Oxford University (more details:

Doubling time is the estimated number of days it takes for the number of cases to double in a nation. Here the doubling time was considered for infection counts in the last ten days for the three dates. The higher the number of days, the fewer the new infections in a country.

A quadrant-wise breakdown

The charts are divided into 4 sections, based on the median numbers of both tests and the stringency index.

1. Top left: Relatively less stringent lockdown, more tests

2. Bottom left: Relatively less stringent lockdown, fewer tests

3. Top right: Relatively more stringent lockdown, more tests

4. Bottom right: Relatively more stringent lockdown, fewer tests

Graph 1: As of March 25

In the initial days, as the number of infections was low in most countries, the cases doubled within 15 days. Most of the nations were therefore in the “red” category with the exception of South Korea and Qatar.

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Observations from graph 1

1. India belonged to section 4 (a more stringent lockdown, and fewer tests). Though cases were doubling faster as in other countries, the overall case load was still smaller compared to countries such as the U.S. and Italy.

2. The only country in green - South Korea - was in section 3 (a stringent lockdown and more tests conducted). This was an early sign that such an approach worked.

Graph 2: As of April 15

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Observations from graph 2

1. It is interesting to note the approach taken by Iceland, Norway, Austria and Thailand, the four new countries which turned green and also kept the circle sizes smaller. Iceland conducted a very high number of tests and kept the lockdown relatively less stringent on both March 25 and April 15. Austria on March 25 had the second most stringent lockdown in the world but relaxed it later once the doubling time increased. It too conducted a relatively higher number of tests. Norway, on March 25, had one of the least stringent lockdowns but it increased the severity on April 25 despite keeping the case count low, while also conducting a relatively higher number of tests. In all these three cases, the approach towards stringency of lockdown varied but the higher number of tests remained a constant.

2. Thailand was the odd one out. It featured in section 2 (relatively less stringent lockdown, fewer tests) on both dates and still managed to keep the case count low and increased the doubling time.

3. India continued to be in section 4. The case count had increased a bit and it still remained in the red category (low doubling time).

A look at data as of May 4 throws in more clarity.

Graph 3: As of May 4

The graph on May 4 shows that more nations had successfully increased their doubling time and also kept the case count low. Circles coloured green appear in every section of the graph.

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Observations from graph 3

1. Of the 15 nations in section 1, one is in red (6%), 10 are in green (66%).

2. Of the eight nations in section 3, two are in red (25%); four are in green (50%)

3. Of the 17 nations in section 4, eight are in red (47%); five are in green (29%).

3. Section 2 is unfit for analysis as Ethiopia has conducted very few tests and there are two few countries to come to a conclusion.

In sum, a higher share of countries in sections 1 and 3 increased the doubling time (turned green) than those in section 4. This indicates that the countries that tested more were able to reduce the infection growth rate better though the lockdown policy varied.

India, along with Bolivia, Pakistan, Bangladesh and Mexico continue to occupy the bottom most part of the section 4 on all three dates.  All these countries continue to be in the red category(low doubling time) with circle sizes (case load) consistently rising every passing day.

This comparative exercise across countries clearly illustrate the centrality of a higher testing rate of the population in curbing the COVID19 outbreak. Stringent lockdowns and mandated physical distancing might have lessened the case load and given a breather to the public health system, but this has not arrested the infection growth rates sufficiently in countries which have imposed them as they did not ramp up their testing rates relative to the rest of the world.

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Printable version | Aug 15, 2020 8:24:12 PM |

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