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Are we testing intelligently?

Today is the 48th day of the harshest lockdown of the world, implemented in India, beginning 24th March 2020, in an attempt to tame the COVID-19 growth. The third phase of the lockdown will end on 18th May, but no one is sure whether the Government will extend it further or not. There is no doubt that the lockdown has enabled the country to substantially curb the COVID-19 growth rate but the way the lockdown was imposed from the top without any deliberations with the State Governments resulted in chaos for millions of Indians. Even after 48 long days, there are no signs of flattening the infection or even in the foreseeable future, instead it is growing with a polynomial curve trajectory. This is quite worrying because many other countries that imposed an extended lockdown, similar to India, witnessed a drastic drop in the number of new cases.

On April 25, Niti Aayog member Dr. V.K. Paul, a retired professor at AIIMS, New Delhi claimed that the decision of the lockdown was timely and the curve has begun to flatten. To prove this point he displayed the above chart where it was projected that the new cases showed a downward trend and may hit zero as on 16th May. This was a time when India’s total infections crossed 24,000 mark and showed a growth of an average of 1388 daily new cases in 7 days. Luv Agarwal, Joint Secretary to the Ministry of Health and Family Welfare, who is now infamous for exaggeration of figures and misinterpretation of data, also asserted that India is flattening the curve.

However, the infection growth shows no mood to follow a declining trend instead it steadily grows totally discarding Government’s tall claims. As of today, it touched around 63,000 cases and during the last 7 days an average of 3610 daily cases were reported. This figure is 2.6 times the daily growth rate which was prevailing two weeks before the tall claim of zero growth rate prediction was made by the mandarins of the Indian Government. If anyone wonders why the Government throws these types of fictional projections, then re-look at the various projections done during the botched up demonetisation time - this therefore is not surprising!


Dr. Randeep Guleria, director of AIIMS recently in an interview admitted that India isn’t seeing a declining trend in new COVID-19 cases. He flagged that, “the major problem right now is that we are not seeing a declining trend. After 40 days of stringent lockdown, which got further extended, the case count should have come down. Many other countries have recorded a downward trend in their COVID-19 curve.” Unlike demonetisation, here the data is scattered over 36 entities of the Indian Republic, total number of the States and Union Territories, which eliminate, to a great extent, the possibilities of data suppression done during the demonetisation by RBI’s rigid central control. Moreover, it is really difficult to keep the infected cases and deaths under wraps unlike the return of the demonetised currency. States are responsible for managing the COVID-19 cases at the ground. As all States are not governed by the same party as the Central Government, the media is no more bound to follow the subservient behaviour shown by them during the demonetisation. This is quite evident now, even the mainstream media started raising probing questions about the mortality figures and inconsistent data releases from some States.

Though I am not an epidemiologist, I had done some projections based on my knowledge in mathematics and relying on rich experience in data analysis. The methodology followed was discussed in detail in the earlier blog post dated 21st April. In the above blog post, it was predicted that India would cross 35,000 infections by 30th April and it did exactly that. Now after analysing the present trend, my analysis shows that India may cross 80,000 infections by 15th May and 1,00,000 infections by 20th May.

However in this blog, I earnestly try to ponder over India’s testing as well as mitigation strategy based on the scant data available in the public domain. This dissection of the testing data was done by viewing it through three main time periods viz. pre-lock down, first lock down and second lock down, for a meaningful comparison.


Instead of guided by the benefit of history, genetics, virology, and current epidemiology, Indian Government not only remains as a mute spectator but also became an active participant to promote anti-science, superstitions and fake medicines as the remedy of COVID-19 advocated by some of their ardent supporters and spiritual gurus in the pre-lockdown period.

To check any epidemic under control, whether it happens inside the country or abroad, the first attempt would be to cork up the import from the origin of the epidemic through rigorous and meticulous containment strategy. A fool proof containment strategy demands to block all entries of the import of the epidemic to the country, by identifying and isolating the infected persons, at the very point of entry itself. It is imperative to follow the scientific advice to save any country from the onslaught of a pandemic, as there are no vaccines and antiviral drugs available. But the Indian Government shut their eyes against the conflicting messages peddled in the name of Ayurveda and the magical powers of cow urine and dung. Instead of educating and alerting the public, the mainstream media shamelessly gave those charlatans headlines in the front pages and carried their interviews in the prime time!


COVID-19 originated from China, India's neighbour, with whom the country enjoys a strong business relationship. Moreover, China also being a manufacturing hub, most of the global business community travelled in and out of China, exposing many international travellers to the COVID-19, who inadvertently spread the virus to others at the international airports and flights. Our policy makers failed to heed to the scientific advice given by the scientists from ICMR that the thermal screening would not identify more than 50% of the infected travellers, as they remain asymptomatic in the early stages of the infection. I have deliberated this  in detail along with how the bull-headed testing strategy led to a colossal failure to identify and isolate COVID-19 imports into India in the early days in an article published in the Frontline.

India failed to screen all international travellers for many weeks in the initial phase and also let a good number of infected people even from the designated countries to the country due to the flawed thermal screening policy. If India had decided for a strict monitoring regime by isolating and testing all the travellers or demand for a COVID-19 negative certificate from day one, India would have been able to trap and isolate a brute majority of import of the COVID-19 infections. As India let loose a lot of infected travellers to the country, which cannot be undone now by pressing an UNDO button, next logical step was to identify the infected people as early as possible and isolate them before they inadvertently spread the virus to anyone who get in contact with them in that long asymptomatic window.

This is not at all a wisdom in hindsight, as enough literature from international experts vouch for it and even our scientists from ICMR forewarned about the vulnerabilities of adopting thermal screening alone as a containment strategy. India's testing now reveals that several cases where people remained without any symptoms for as long as 4 weeks emerged as covid cases confirming several experts' view that thermal scanning hardly captured 20% to 25% of the infected travellers.


The first infected case of COVID-19 was reported from Kerala on 30th January. If the data from that date up to 23rd March is examined, it can be seen that India was able to trace and identify only 471 cases in that long window. During the above 54 days window India had done only 20717 tests, ie, just less than 384 tests per day. Another point to note that 70% of the above tests were done in the final 6 days between 18th March to 23rd March.

Globally many scientific literatures are available arguing for an early detection strategy, which would pay huge dividends in containing and mitigating the virus spread. Many international epidemiologists reiterated that early detection and early response was the key. They argued that it should be followed by isolating and treating each virus case citing the examples of Taiwan, Iceland, New Zealand etc. This strategy is very well explained by the renowned epidemiologist Dr. Larry Brilliant in this TED Talk.

Not just global, but even in our own backyard, we have a suge success story thanks to this same strategy - Kerala. Kerala’s success of containment can squarely be attributed to this trace, test, isolate and treat strategy adopted by them. Kerala as of 23rd March, identified 95 cases and tested 3082 persons which is  15% of the total tests done in all over India up until then. Meanwhile, India identified only a total of 471 cases, out of which 95 infections identified by Kerala i.e.  20% of the all India figure, this is especially when Kerala’s population is just 2.6% of India. Chhattisgarh is another State in India, which adopted a similar strategy, but with less fanfare and attention.

No one will have a difference of opinion that this 54 days lockdown was a huge window of opportunity to brainstorm our capabilities, our limitations and chalk out a strategic plan to move forward. Did the central government discuss State Governments or were they left alone to deal with this health emergency in the ground? Whether we procured enough test kits, PPEs and other essential medical materials before those became a scarce material in the global market? Whether India thought about the disruptions and chaos unleashed due to a lockdown without prior notice? Whether India ever cared about the subsistence of  its poorest of the poor? Whether India had an exit plan, forget plan B & C, before announcing the lockdown? Answers for all these questions are a depressing zilch!


The first lockdown was intended for 21 days starting from 24th March to 14th April. Let us take stock of the testing strategy adopted during this period. The number of tests saw a substantial increase from 20,717 on 23rd March to 2,44,893 on 14th April. This is an 11.8 times increase in the total tests done and this implies India did 182 tests per million (TPM) of its population against 15 TPM, as on 23rd March, which was abysmally low compared to global standards. In the same period, India detected 10307 cases, which is 21.9 times of the cases as on 23rd March. This indicated that when India tested more, it started detecting more cases!

Several experts suggest that looking at the representative testing figures of TPM in isolation may not be helpful to identify all facets, instead they suggest to look at that data along with the number of tests that are needed to find each COVID-19 case, let us call it as tests/case (In the earlier blogpost, I discussed about the percentage of positive cases per each test done. Tests/case is an inverse of that figure).

Let me explain the logic behind this new number of tests per case. This number represents how many tests need to be done to identify a positive COVID-19 case at any given location. This is in resonance with the slogan that "test more and find more", because when the testing is increased it will lead to detect more cases on a proportional basis. If this number shows an increasing trend when you test more, this indicates that the more testing coverage detects lesser cases in that location. Conversely, when you amplify the testing, less number of tests are required to find each positive case, means that there are more undetected cases infections prevails in that location which warrants more testing till the number of tests required to detect positive cases showing an increased trend.

Hence researchers made a case that if representative testing value TPM increases along with the tests/case increases it indicates that that country is in better control in containing the pandemic. Vice versa, if the TPM value increases but tests/case decreases, it indicates that there are undetected cases and it warrants scaling up the testing extensively.  Of course, this logic has some limitations, when it is applied to unique cases of chasing super spreaders in a particular cluster.

A high mortality rate is a broad indication of the late detection of the infected cases which leads to death - they inadvertently spread the virus in that long window of asymptomatic stage, presence of more immunodeficient people infected with the virus, poor health infrastructure and manpower at disposal, etc. Hence some researchers insisted that along with the above two parameters, mortality rate should also be considered and these three parameters viewed in conjunction would give a holistic idea of the infection prevailing in the country.

This table shows how these TPM and tests/case values changed during the first lockdown period between India and Kerala. While India’s TPM increased, corresponding Tests/Case showed a decreasing trend, which indicated that there are more infections undetected in the country and the growth of the epidemic is not in control. As far as Kerala is concerned while the TPM increased, there is an increase in the tests/cases, showing comparatively better control with the all India scenario.

If Indian Government had ramped up its testing based on an intelligent strategy of focusing more extensive testing in the identified hotspots along with sentinel testing of health workers and other vulnerable population who are subjected to more exposure and also gone for random representative testing in the places, which are not exposed to enough testing with a sole mission to trace, identify, isolate and treat the virus, India would have been in much better control of the epidemic by end of the first lockdown period itself. It is quite baffling why ICMR held on to a limited testing regime when this lockdown was a perfect opportunity to try the large scale mitigation by adopting an extensive testing strategy to trace and test the travellers, who escaped through the porous thermal screening. Is it because of the failure to stock enough test kits or due to some unscientific view prevailed over sensible scientific opinion, which we witnessed during demonetisation in a perverse manner? ICMR only relaxed the testing criteria as late as 9th April to test a more vulnerable population including all people with SARI, asymptomatic direct and high risk contacts and all symptomatic ILI.

When the second lockdown ended on 3rd May, India had done more than 10 lakh tests, confirmed cases touched 37671 and the corresponding representative figure was 777 TPM. India entered into the club of first ten countries on the basis of sheer volume of tests done but India's TPM figures are abysmally low in comparison with global representative figures. Kerala in the meanwhile, identified 499 infections and the testing figure was 909 TPM. Kerala's infections now only constitute 1.3% of the all India infections, a dramatic fall from 20% prior to the lockdown.

Let us compare the scenario of India and Kerala again. Though India’s testing increased by 4.3 times during this second lockdown period, the tests/case only showed a marginal increase of 1.17%, this further warrant that India should test more extensively and intelligently as discussed in the earlier paragraph.

Meanwhile Kerala’s test per case increased 1.56 times, my personal opinion derived through extensive review of literature is that Kerala should go for more sentinel testing and random representative testing of its population either through rRT-PCR testing or Rapid Antibody testing, as the above tests/case increase is not enough to lower the guard.


To get a wider perspective of the above concept let us examine how the above parameters for India’s highly infected states fare in comparison with the three States who had shown a better control in mitigation. As I collected testing figures pertaining to all States only from 28th March, for pre-lock down comparison used that date instead of 23rd March.

Here you can see that the top five highly infected states, the tests/case figure is very low, especially Maharashtra, Gujarat and Delhi are well below the national average of 28 tests per case. As in the case of Maharashtra, Delhi, Rajasthan where tests/case figures decreased even while TPM increased manifold. This data point indicates strongly that there are more infections still undetected in these states and they should enhance their testing in an extensive way. While Gujarat's tests per case remain the same even though they ramped up tests by 97 times, it also demands that they should also enhance their testing.

Delhi remains a major concern here, as its TPM increased from 57 to 2147, corresponding to the tests per case decreased to more than 50%. At present every13 tests returns a positive COVID-19 infection, and this means that Delhi has  no choice but to go for extensive and strategic testing. Though Tamil Nadu tests/case figures showed a marginal increase from 40 to 49, that reduction is not substantial.

Kerala’s case is already discussed while comparing their case with the all India scenario. But looking at the figure of tests/cases of Chattisgarh, I reiterate that Kerala should do more testing in the coming days. Karnataka ramped up their testing substantially and their tests/cases showed a high increase, which can be termed as the evidence of a good control.

Chhattisgarh, which showed a remarkable increase of 46 times in TPM value, while its tests/case increased substantially to 5.3 times and this figure is the highest among the States I made a comparison. Chhattisgarh is another State like Kerala who had attempted early tracing of the cases. Though they don’t have an expatriate population like Kerala, they have a huge chunk of migrant labours spread all over the country, estimated to be more than 2 lakhs. They have kept more than 80,000 people under surveillance at home and hospitals together in the initial phase in comparison with Kerala’s figure of 1.7 lakh though they had less air travellers’ inflow in comparison with Kerala. This along with rigorous contact tracing with gearing up their public health infrastructure are the major reasons that they are able to contain the spread of the virus.


As on 9th May, India had done more than 15 lakhs tests with 1131 TPM and detected around 60,000 cases but tests per case is now reduced to 26 from the value of 28 on 3rd May. These two maps will give a fair idea of the TPM value as well as tests/case value of various Indian States.

As Telangana Government hasn’t published any testing data since 29th April, their data is ignored in the above maps. Based on the above deliberations, this data can be easily interpreted for the remaining states - an exercise left for the readers.


The maps shown above clearly exhibit the high variance of testing as well as detection rates among various States and Union Territories. These data from various entities are still not available in a single national platform, though I continuously argue for this from the pre-lockdown era.

During my research I observed various countries, for example Estonia and Iceland, made their information available in an exhaustive manner. But the Indian Government's data releases of COVID-19 to the public is bare minimum and rudimentary. It is quite disheartening to see that the Government’s projections are based on CGR (compound growth rate) instead of citing projections based on epidemiological model studies. Also it is quite perplexing to see that the officials talk about doubling rates alone without referring to the changes in R-naught values during an epidemic, this is especially important for Mumbai, Ahmedabad and Delhi metro cities. It can be taken as indication that the epidemiologists were side-lined by certain financial experts and administrators in the Government, who cannot fully grapple the nuances of how an epidemic grows, an esoteric branch of medicine.

When a premier research organisation like ICMR is content with releasing just cumulative national testing numbers alone in a single line press bulletin every day, it is really depressing. India still has no national baseline reporting time, hence various State Governments report data at various times of the day, making data analysis more complex.

While some states show total number of tests without specifying whether that number includes repeat tests and the rapid antibody tests (which were withdrawn after a couple of days due to the faulty kits procured by ICMR), other states give their repeat test numbers in a detailed manner. Some states provide positive cases and negative cases explicitly but did not mention whether these numbers include repetitive tests done on the same people or not. Telangana's testing figures are not available in the public domain since April 29th, and the limited data that is there was released after a huge gap. No information is available in the public domain about the testing done by Lakshadweep, interestingly that is the only entity in the Indian Union, which has no testing laboratories or sample collection centre.

As neither ICMR nor MoHFW has yet shown any positive signals to publish the State-wise testing figures, there is no uniformity in the testing figures between various State Government figures. Also there is a huge difference when adding all 36 entities testing figures, this figure is higher by a huge margin in comparison with the all India testing figures released by the ICMR. 

It is high time that India should closely look at the district level testing and detection and should release the district level testing data, this will give a macro level monitoring information. India should employ an intelligent testing strategy discussed in the earlier paragraphs fully utilising the remaining window of the third lock down. India started to bring its overseas citizens and also permitted the movement of stranded migrant labours and other citizens. Hence India should start an intelligent testing regime on a war footing basis, listening to the advice by epidemiologists. As these influx of people to the States will bring new variables into the existing scenario and will create huge challenges for the States. Monsoon is also fast approaching which could cause a spike in the various vector diseases.

This warrants more detailed data in the public domain viz. numbers of imported cases, primary and secondary contacts, non-traceable infections, confirmed cases, active cases, deceased cases, age and gender of the individuals, all historical data from day one at least on State level but preferably at district level, etc. This will help independent epidemiologists and policy makers to analyse and suggest more meaningful ways to mitigate this imminent danger. These inputs will definitely help the administrators to have more detailed and divergent viewpoints to take suitable policy decisions.

Let me end my scribbling with a hope that our tryst with data may see a sea change in the coming days!


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