How Long Will the Pandemic Last? Rate of Growth of Active Cases Holds Key.
Based on the current trend line of active cases, the growth may be slowing but India will hit its peak only when daily recoveries outpace new cases. There are signs this may be happening in Delhi, which is why other metros need to pay attention to its strategy.
A woman watches as healthcare workers wearing personal protective equipment (PPE) check the temperature of residents of a slum during a check-up camp for the coronavirus disease (COVID-19) in Mumbai, India June 17, 2020. Photo: Reuters/Francis Mascarenhas
Just over a week ago, Prime Minister Modi asked his ministers to prepare “emergency plans” to deal with the spike in COVID cases in the five most severely affected states of the country. If one is looking for an admission from the government that its lockdown had failed, then this is it: instead of taking 21 days, Modi’s Mahabharata has lasted over 100 days. And the battle is only growing more intense by the day.
So how long will it last? How long before the case count reaches its peak and starts to decline? After how many deaths? If anyone in the government has an idea, she or he has kept it a deep secret. Mercifully, we have enough data now to make a reasonable estimate by ourselves. The news is not all that good, but the data on the rate of growth of active cases (i.e. total cases minus those who have recovered) is sufficiently reassuring to make panic unnecessary. While across India, daily new cases are outpacing daily recoveries, the picture in Delhi is somewhat reassuring and could serve as a guide for what needs to be done if the duration of the pandemic is to be shortened.
The following table gives data, from May 15 till July 6, for the total number of cases, the number of patients who have recovered, and the number of patients under active care.
May 15 has been chosen as the starting date because phase 3 of the lockdown had ended and normal life was just being resumed. It therefore gave the data a fairly uniform base, free of policy change-induced shocks. A comparison of the rates of change in these parameters makes it possible to discern the slowing down of the diseases and, barring, a surge in news cases, broadly map the trajectory of cases.
Of course, a caveat is needed. Two big confounding factors remain testing rates and the government’s denial of community transmission. Recovery rates do increase because that’s the natural course during a pandemic and we won’t discover more new cases unless we test more, which is why leading epidemiologists like Dr Jayaprakash Muliyil think most cases are going under the radar. For this exercise, however, we will take the government’s data at face value.
