Ideas

No, India’s Covid-19 Cases Are Not Low Because We Are Testing Less

Covid 19 
Snapshot
  • The logic by a news portal that India’s minimal instances of coronavirus is because of ‘minimal testing’, is absurd.

    On a deeper analysis, we may safely assume that it’s just bias at play — where data is suitably tortured to reach a predetermined conclusion.

Covid-19, the disease caused by SARS-CoV-2, has claimed more than 7,000 deaths worldwide. The number of cases across the globe have ballooned past 180,000. Now, there are more Covid-19 cases outside than inside China, the origin of the virus.

In India, total confirmed cases are 125 out of which two people have died, 17 are foreign nationals and 13 people have recovered.

It’s one of the select few big countries that has the lowest number of cases. The obvious reason behind this is the early panic shown by the government in responding to the fast-spreading disease.

Severe travel restrictions came on 26 February, five days before two new cases were reported in India, limited to passengers coming from China. These were updated regularly. On 11 March, more extensive measures were announced, suspending all non-work, non-diplomatic visas and announcing mandatory 14-day quarantine for all travellers coming from top hotspots.

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Yesterday, the government added countries in the Middle East to the list as well and put a complete ban on flights from European countries.

On top of this, the government has been screening passengers at airports for high viral load much before the Western countries started doing it.

The government has been aggressively doing contact-tracing of thousands of people who came in contact with the infected.

Thousands more are under community surveillance and are being checked for symptoms.

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All these measures, which are being updated regularly and improvised quickly depending on the evolving situation, have helped India contain the outbreak and made sure that India is still in Stage 2 of this pandemic (Stage 1 is when a country has only imported cases, stage 2 is when there is local transmission, stage 3 is when “community transmission” has started and stage 4 is a full-blown pandemic).

However, some “professional pessimists” and obsessive compulsive critics of the government are not able to digest the low number of cases in India. India has few cases because it is not doing enough tests, they claim.

One digital news portal even came up with a novel metric of “tests per million population” to show India as far behind countries such as South Korea, the United States, the United Kingdom, Italy and China.

This is absurd to say the least, and not just because India’s population is more than most of these countries combined.

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It’s a perfect way of torturing the data enough to reach a conclusion that is in line with one’s bias.

First of all, if India is to be compared with these countries, then we have to compare it to them when they had cases at India’s level, not at where they are currently. India is far ahead of them. When the US had 400 cases and India only 34, the former had conducted less than 2,000 tests while the latter had done more than 3,400.

And while making such comparisons and concluding that “less number of cases is due to less testing” as proved to be the case in some countries, we shouldn’t forget that India has done more than any other country in putting border restrictions, which has reduced the probability of community transmission that had already happened in those countries which woke up too late.

India has been well ahead of the curve because it realised early that stopping the import of virus at airports is easier than controlling its spread later in the communities.

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When the case number is low and resources are limited, as is the case with Covid-19 diagnostic kits as well as healthcare infrastructure, it makes much more sense to concentrate efforts in limiting spread from high probability areas (like airports) which is exactly what India has done.

Second, the critics do not understand how sampling works.

“When we conduct a sample survey over a large population, the sample-size required to ensure that the accuracy of a result lies within a certain confidence interval does not vary much as the population increases beyond a certain point. For instance, in a town of 100,000 people, to attain a 95 per cent confidence interval, one just needs 383 respondents to a survey. If the town has 500,000 or 1,000,000 people, just 384 respondents are required,” says a group of techies who run the Twitter handle and blog “The Learning Point”, popular for sifting data on education in India and posting valuable insights on it. (Read this Twitter thread on their criticism of “tests per million” metric used by a publication)

“Though medical testing is quite different from accurate sampling for a survey, some of the general principles are similar: to test for the spread of an epidemic, the number of tests doesn't have to depend on population-size,” the techies add.

They suggest a better strategy than mindlessly going for indiscriminate testing across the country: conduct a few random tests per district — and then identify districts where the infection has spread; and the focus on testing only those districts.

In any case, 13 labs have been doing random sampling for the past one month to check if there has been any community transmission.

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The labs are testing 20 samples of influenza-like illnesses (ILIs) and severe acute respiratory infection (SARI) periodically for Covid-19 and all have returned negative results.

Starting today, 51 labs will start doing the same to look for signs of community transmission.

One can make the case that we need to test more random samples than just 20, but not that our case load is low because we are testing less.

Third, the critics do not understand that all tests are not equal and more testing at this stage can do more harm than good. As Dr Anupam Singh, MD Internal Medicine, explains in this Twitter thread, metrics like sensitivity and specificity matter a lot in testing and accuracy is not 100 per cent. When a country has very few cases of Covid-19 like India has, there is a real possibility that many patients who don’t have the disease would be flagged positive by the tests.

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“From (available) literature, a sensitivity of 85 per cent and Specificity of 98 per cent is seen for RT-PCR. So, in what prior-risk range is this test useful? For the Covid-19 test of RT-PCR, this prior risk works out from 2.6 per cent to 80 per cent. Thus, if prevalence of Covid-19 in India (or individual risk is less than 2 per cent), chance of false positive (is high). If prior probability is greater than 80 per cent, chance of false negative (is high). So, a test is helpful only in that grey zone,” Dr Singh explains.

As Dr J. Mariano Anto Bruno Mascarenhas, a neurosurgeon says, “Too Little Testing is Bad. Too Much Testing is Bad.”

Therefore, it is critical that we get the timing of scaling testing right, otherwise, we will have a lot of cases showing up positive when they don’t have Covid-19.

This not only creates panic but also depletes scarce resources whether healthcare facilities or test kits, something that those who are actual patients may need later.

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Fourth, the critics do not understand that the Covid-19 test has a very limited purpose compared to tests which detect other illnesses.

“Treatment of Covid-19 is not based on the test result. It is based on organ function. There is no specific drug which kills or prevents multiplication of Covid-19. So what do we do in the hospital? If Covid-19 attacks lungs, the patient can't breathe, we give them oxygen in face mask if attack is less. If attack is more, we put them on ventilator. If the virus attacks kidney, we need to give dialysis to the patient. So, treatment depends on how good or bad the lung is or liver is or kidney is,” explains Dr Bruno Mascarehnhas.

“The test result has no role in treatment of the individual. Treatment depends on how each organ in the patient functions,” he says.

However, there is one use of the test. “We can know how many people are affected and whether the rate of spread is more or less with time. For that, it is enough to test a certain number of people. That is what we are now doing. Many people have confused this with, say, blood sugar tests where we measure blood sugar and modify insulin or tablet dose according to the test result,” he adds. (Read this twitter thread by Dr Bruno clarifying various doubts regarding Covid-19 testing)

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“Testing is more useful for administrative purposes than the treatment purposes,” he puts it succinctly.

Dr Anupam Singh says, even in Wuhan, the epicentre of virus, doctors didn’t start testing indiscriminately. They followed a proper algorithm as shown in the picture below.

So, what the government can do in the short term is to give the doctors at the hospitals the authority to send any sample of their patient for a Covid-19 test if they suspect the Coronavirus infection in them.

To sum up: Should we be testing more? Yes. But are India’s Covid-19 cases low because we haven’t done enough testing? Absolutely not.

While we increase testing going forward, India has rightly focussed on expanding its testing capacity.

From 10 labs at the start of this month to 72 labs doing Covid-19 testing, the growth has been good.

In addition to this, 70 more government labs have been readied to start testing.

Moreover, the government says that around 60 private labs will soon get permission to start testing. This means that India will be able to do 20,000 tests per day (assuming testing of 100 samples each at every lab).

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At the stage that India is in, this is more than enough. But constant improvising and more and more decentralisation of testing will be the natural way forward.

Clarification by The Learning Point: The example of sampling is not meant to be an analogy for the kind of testing required at this point of time. It is only intended to show how the required number of samples or tests are seldom required to be in direct proportion to the population size. Testing ideally requires to zoom in on each case of infection, but even for that - the probability of an office-goer in Mumbai being infected is far greater than someone in a remote or rural area of Jharkhand at this point, so it makes sense to focus testing efforts accordingly.

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