Explained: How to read India’s Covid-19 data

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Do we have enough data?

The current pandemic is one of the most data-rich global health crises in history, and this is true for India as well. As concerned citizens, we would like to use this data to answer questions such as:

• Do declining case numbers actually mean a decline in the epidemic?
• What are the best indicators for assessing a decline or flare-up?
• How effective is the test-trace-treat strategy in our city?

For nearly every district and for all major cities in India, we have information all through the pandemic about three quantities: daily numbers of tests, identified positives, and deaths. With these numbers, we can create two meaningful quantities: the ratio between the identified positives and tests, which is called “test positivity”; and the ratio between deaths and identified positives, called Case Fatality Rate (CFR). The deaths on any day are from positives identified over a fortnight or so before that day, which have to be considered in obtaining the CFR.

How many should be tested?

In a standard Test-Trace-Treat strategy, this can be answered as follows: Let one individual, let’s call him Mr X, test positive (Test stage). Next, health workers will speak to Mr X and find out everyone he has been in contact with (Trace stage). Suppose Mr X has come in contact with 20 people. He spent a lot of time with 5 of them (high risk) and briefly met the others (low risk).

In an ideal world, all these 20 contacts should be tested, but constraints of time, money, people and equipment usually do not allow that. If only high-risk contacts are tested, many are likely to be positive and therefore the test positivity is likely to be very high. If more and more contacts are tested, the likelihood that many contacts are positive decreases (since low-risk contacts may not get infected). Since identified positive persons cannot infect others because they are isolated, a low test positivity indicates that the epidemic is likely to be contained effectively.

Is test positivity always a good indicator?

Test positivity is a good benchmark at the earliest stages of the epidemic. Once the infection has spread sufficiently through the population, the chain of infection is no longer clear. Then if Mr X went to the market and caught the infection from who-knows-where or passed on the infection to God-knows-who, the test positivity may not reduce even when the number of tests is increased. This is a bad situation of course, since it is indicative of widespread infection, with many asymptomatic cases.

Test positivity can be also used as an indicator to mark the decline of the epidemic. As the epidemic ends, the number of tests being done will decline and the test positivity is likely to stay constant or decline as well. However, as the number of tests decline, if an increase of test positivity is observed, then the reduction in the number of tests should be taken as a matter of concern. It is then necessary to increase the number of tests.

Can we improve on test positivity as an indicator?

As we saw, test positivity by itself does not give enough information to understand the progress of the epidemic at all stages. Moreover, there can be many infected people who are asymptomatic and who therefore remain undetected. Such asymptomatic people can infect others, and it is necessary to estimate their number to understand the progression of the epidemic. That is where the Case Fatality Rate (CFR) comes into play.

To understand the use of CFR, we need to introduce another indicator called the Infection Fatality Rate (IFR). CFR tells us how many of the identified positive persons have died. But there will be many unidentified positive persons as well. IFR is the ratio of deaths to the total number of infected persons, identified or unidentified. IFR is usually much lower than CFR — because of the large number of unidentified positive persons — and can be considered a constant for a disease for a given age group. There are ways to estimate the total number of positive persons in a locality (Pune’s serological survey did this in certain electoral wards).

Let us say the IFR for Covid-19 is 0.3%. This means out of every 1,000 infected people, 3 are likely to die. If the CFR is 1%, out of 300 identified infections, 3 people have died. The implication is that around 700 Covid-19 positive people have not been identified. If CFR were 2%, 6 people would have died, which would require an underlying population of 1,400 infected but undetected people. This is a hypothetical example, but it illustrates the fact that the higher the CFR, the greater the number of unidentified infections.

So, what have we learned?

A simple analysis of more or less readily available pandemic data tells us the following:

• High test positivity and high CFR: Testing needs to be ramped up and door-to-door surveys may be necessary to identify infections before the disease turns rampant.

High test positivity and low CFR: The infection has spread through the population, but the health system is responding well, keeping deaths low. The number of unidentified positives is not high. But this could also imply under-reporting of deaths, which needs to be investigated.

Low test positivity and low CFR: The epidemic is likely under control.

Low test positivity and high CFR: Provides contradictory information, and may point to attempts at keeping the test positivity artificially low.

Pune city’s trajectory

Pune has been one of the worst affected cities in India. The availability of data makes it easy to analyse, based on the above reasoning, how the city handled the epidemic. Figure 1 compares the weekly positive cases against test positivity in Pune from April 2020 until May 2021. In the very beginning of the pandemic, test positivity was fairly high even though the number of cases was low, indicating that there were a large number of unidentified cases by early April 2020 itself. It is likely that only the high-risk contacts were being tested due to limited availability of tests.

Figure 1: Weekly cases and test positivity in Pune city

During the peak of the first wave, the test positivity shot up to really high levels, indicating that the spread of the infection was quite large and that the testing capacity was simply not sufficient. While the number of cases dropped quite sharply in October, the test positivity dropped but remained fairly steady at around 10% until nearly the end of December, indicating that there was a latent infection load in the population that never really went away. The test positivity reached its lowest values in January 2021, but started to rapidly increase in the first week of February, before the increase in cases themselves, thus providing a forewarning.

Since March, a rapid increase of testing ensured that the test positivity in Pune did not reach the levels of the first wave even though the number of cases was much larger. Indeed, the test positivity started dropping before the actual number of cases in April 2021, which points to a better performance of the public health system during the current wave in Pune.

Figure 2 shows that the CFR paints a similar but complementary picture. The high CFR in May 2020 indicates that the spread of Covid-19 was much higher than what the cases indicated, and the lack of preparedness of the health system. The CFR remained constant between mid-July and mid-October 2020, then started rising again. This again points to the fact that the peak of the epidemic was likely reached in mid- to late October rather than mid-September as the number of cases suggests.

Figure 2: Weekly cases and CFR in Pune city

The CFR has remained flat and fairly low since December 2020, again underscoring the fact that Pune’s health system has performed much better this time around, which is remarkable. However, the slight increase in CFR beginning in late April 2021 reminds us to be vigilant to ensure that the CFR does not start rising again.

The above analysis also highlights the necessity of transparent data sharing by the administration. The drop in the number of cases in October lulled us into a sense of safety that was not really supported by other measures such as test positivity and CFR. Crises demand collective action by the citizenry, and we must ensure that all relevant information is available so that we can make the best possible decision in these uncertain times.