Could India 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 on HT on Monday, is, according to the panel, contingent on wearing masks, tracking and social distancing, but a drop from the current level of around 770,000 active cases (according to HT) to 40,000. in the next three and a half months it seems difficult.
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The last time India had fewer than 40,000 infected cases was in the first half of May, when it saw between 3,000 and 4,000 cases a day. The panel’s projection comes against the backdrop of a steady drop in the number of daily cases, from a weekly average of around 93,000 in mid-September to around 61,000 in the third week of October, and seems 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 hope will trigger a series of new cases; the reopening of almost everything; the current holiday season, which is likely to witness fervent socializing; the trend seen in almost every large country in the world (much of Europe is currently in the middle of a raging second wave and the United States is in the third) and crown fatigue (something I’ve repeatedly written and warned about). 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 so far is between the scope of the tests and the rigorousness of the measures, such as blockages on the one hand, and the number of daily cases due to it. other. . Any other link, temporary or related to infection rate, is hypothetical. But what if this can be done?
An article on the medRxiv prepress server states that it can be, and without much trouble, taking advantage of the reverse transcription polymerase chain reaction or RT-PCR tests that are used by most countries (including India). James A Hay, Lee Kennedy-Shaffer, both from Harvard’s 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 viral loads of randomly. population sample. The RT-PCR test, considered the gold standard of Covid-19 testing, 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 spread of the pandemic in a region, viral loads in a random sample will be high because infections are still recent, and that in later stages of the epidemic, these loads are reduced. because the infections are no longer recent. Thus, the authors say, viral load can be used to really understand whether the epidemic is increasing or decreasing in a region. “The distribution of viral loads, in the form of cycle thresholds (Ct), from positive surveillance samples at a single time point can provide an accurate estimate of the trajectory of an epidemic,” they write. They also add that “the distribution properties of the measured viral loads (median and skew) vary with the growth rate of new cases.”
Clearly, more work is needed to understand the model used by the authors and to test it under various conditions, but if sustained, this approach could help health administrators determine when and if the number of active cases in a region is decreasing or decreasing. growing. As the authors point out, this could aid ‘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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