The ‘Advance Warning’ and ‘Pandemic Building’ metrics to prepare for Covid’s third wave

In the early days of March 2020, governments were worried that industrial slowdown will be a big problem due to covid, in view of the ‘shutdowns’ and ‘lockdowns’ to ensue. Lockdown is but a more serious version of a shutdown, in that, lockdown applies to all, while a shutdown affects select activities. For example, in a shutdown, shops will be closed. But, in a lockdown, all factories will be closed. Thus, a lockdown can do a lot more damage to industrial life than a shutdown.

These two aspects are ‘outcomes’ of a deeper malaise – a spreading covid infection. The ‘enablers’ leading to the closures at various levels are far more important. And I think this was neither well understood nor adequately addressed before the second wave in India, leading to a very serious situation.

Also read: India fares poorly in healthcare

So, the lead indicators, like, average density of crowds in places like gyms, malls, vegetable and flower markets; average trips made by ambulances, rate of admission of patients in hospitals, status of ICUs bookings, (called the ‘Advance Warning’ cluster) followed by the number of active cases, availability of hospital beds, doctors, oxygen, ICU’s, ambulances are all vital to control the outcomes, like, number of deaths, number of serious cases in the ICU’s, number of recoveries, etc. (called the ‘Pandemic Building’ cluster). The third dimension of this triangle is the ‘feedback’. The covid environment can then be characterised by a ‘Covid Triangle’. (see figure below).

Thus, it can be seen that the enablers fall into two clusters – ‘Advance Warnings’, and ‘Pandemic Building’. India missed out on the ‘Advance Warning’ cluster, because such a concept did not exist at the time. Most agencies did not sense the developing tsunami of cases as there were no metrics available to sound the alarm.

An alarm cannot be sounded based on someone’s instinct or gut feel, it needs to be backed up by some scientific data and analysis. Similarly, it should also be said that experts have not arrived at certain threshold levels of these cluster variables which will indicate the start of a ‘Pandemic Building’ phase. It is hoped that the concerned agencies like the Union Health Ministry should immediately at on this and issue guidelines which state governments can monitor.

We are seeing a lot of statements everyday in the press about the start of the third wave, but these are merely speculative, there is no scientific approach to identify, isolate and provide trigger levels for the ‘Advance Warning’ variables.

Doing this will help us avoid not only the build up of the wave, but also help state governments assess the infection levels (i.e., cases) more accurately, and provide the necessary resources. Especially, oxygen, which proved to be the Achille’s heels for the governments efforts to deal with the second wave. My view is that the oxygen requirements have been overestimated in many places, and, had oxygen reached on time, then the quantity consumed would have been much less than what actually was used up.

The problem with such a state of affairs is that huge capacity build-ups are done based on the shortages, without taking into account that the shortages were but a temporary mismatch between capacity and consumption. In other words, India had enough capacity to produce oxygen, but could not reach it in time to the needed places due to logistics gaps. However, to the credit of the central government, the logistics arrangements were done speedily and largely in a timely manner. Now, the press is reporting the creation of new oxygen capacities by all and sundry, which will result in low-capacity utilisation and consequent waste of capital assets due to future disuse and disrepair.

Also read: Managing the medical oxygen supply chain in India

The ‘Pandemic Building’ metrics are another bunch of lead indicators, the knowledge of which will govern the monitoring and control of the events during the break-out. Big data analytics can be used to build models and simulations which can help establish various ‘trigger’ levels for the cluster variables, so that actions can be goal-directed rather than all encompassing.

Any multi directional actions will invariably lead to waste of resources, non-availability of required medicines and pills, at the right place and time, and consequently a mismatch between effort and results. This wrong ‘pairing’ can and does cause needless harm to suffering patients, and avoidable deaths and long hospital stays, post covid complications arise.

The start of the second wave could not be sensed early enough. Even the models developed by some institutions were reported in the press sometime during the middle of the wave. This, though helpful, can be prevented by early big data analytics, provided our scientists are able to identify the ‘Pandemic Building’ variables.

Already, one is seeing some predictions by an IIT Kanpur model, which shows the possible start and end dates, as also the levels of cases. However, this model will be helpful only if we can know that the third wave has started. This can be found only if we can, between now and September, or sooner, work on the two clusters of lead indicators identified, and provide an ‘Early Warning’ system to the central and state governments. Hope this will be done sooner than later.

(Jayaraman is Head of Capstone Projects at Bhavan's SPJIMR)

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