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Home / India News / Covid-19: What you need to know today

Covid-19: What you need to know today

The last time India had fewer than 40,000 infected cases was in the first fortnight of May, when it was seeing between 3,000 and 4,000 cases a day.

india Updated: Oct 20, 2020, 04:41 IST
R Sukumar
R Sukumar
Hindustan Times, New Delhi
OPD open at GMSH sector 16 on Monday after long gap with strict Covid norms for Hospitals in Chandigarh.
OPD open at GMSH sector 16 on Monday after long gap with strict Covid norms for Hospitals in Chandigarh.(HT photo)

Could India indeed have fewer than 40,000 active cases of the coronavirus disease (Covid-19) by February as a government-appointed panel believes? Sure, the number, reported in an article in HT on Monday, is, according to the panel, contingent on the wearing of masks, tracing, and social distancing, but a drop from the current level of around 770,000 active cases (according to the HT dashboard) to 40,000 in the next three-and-half months does seem difficult.

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The last time India had fewer than 40,000 infected cases was in the first fortnight of May, when it was seeing between 3,000 and 4,000 cases a day. The panel’s projection comes against the backdrop of a consistent fall in daily case numbers, from a weekly average of around 93,000 in mid-September to around 61,000 in the third week of October, and would appear to assume that India will not see a second wave of infections. That seems unlikely for five reasons: the onset of winter, which many experts expect to set off a rash of new cases; the reopening of almost everything; the ongoing festive season, which will likely witness some amount of fervent socialising; the trend seen in almost every large country in the world (much of Europe is in the midst of a raging second wave currently, and the US is in its third); and corona fatigue (something I have written about and warned against repeatedly). Still, as the cliché goes, I will hope for the best and prepare for the worst.

No country has been able to predict the trajectory of the disease, and the only correlation that has been established thus far is between the extent of testing and the stringency of measures such as lockdowns on one side, and the number of daily cases on the other. Every other link – temporal or related to the infection rate – is hypothetical. But what if this can be done?

A paper on the pre-print server medRxiv claims it can be – and without much trouble, leveraging the prevalent reverse transcription polymerase chain reaction or RT-PCR tests that most countries (including India) use. James A Hay, Lee Kennedy-Shaffer, both at the Harvard TH Chan School of Public Health, Boston, and others, have built a model that, they say, can measure where the epidemic’s trajectory is, based on the viral loads in a random sample of the population. The RT-PCR test, considered the gold standard of Covid-19 tests, is widely used, the authors say, as a Yes-No (Positive-Negative) test, but it also measures viral loads. The hypothesis behind the model is that in the early stages of the pandemic’s run in a region, viral loads in a random sample will be high because the infections are still recent – and that in later stages of the epidemic, these loads reduce because the infections are no longer recent. Thus, the authors say, the viral load can be used to actually understand whether the epidemic is waxing or waning in a region. “The distribution of viral loads, in the form of Cycle thresholds (Ct), from positive surveillance samples at a single point in time can provide accurate estimation of an epidemic’s trajectory,” they write. They also add that “the distributional properties of the measured viral loads (median and skewness) vary with the growth rate of new cases”.

Clearly, more work is needed to understand the model used by the authors and stress test it under various conditions, but if it holds, this approach could actually help health administrators figure out when and whether the number of active cases in a region is declining or rising. As the authors point out, this could assist “real-time resource allocation” and shape “outbreak mitigation strategies”.

Science and data, as this columnist has repeated ad nauseam, are the only things that can point us in the right direction. Everything else is just a guess.

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