Dissecting the Indian pandemic bubble that is taking away thousands of lives today

India fights the most serious crisis since Independence, and there is a strong division between opinion as to who is responsible for the scenes of desperation and helplessness which in the previous century we felt we had left behind. Sadly, the responses to this issue are perfectly predictable on account of the respondent’s political affiliation. The reality is perhaps obscure in the face of the dynasty and the cacophony of political slogan making.
Fortunately, an analytical concatenation of information within a system of risk assessment may provide a constructive perspective into the events and how to ensure that these results are achieved in the future. Although the meaning may be different, the behavior of the second bubble wave resembles the financial bubble. Therefore, in the light of this pandemic, lessons from financial risk management are relevant.
People had more restraint in the first wave, and the government was more cautious. This was most certainly due to a mix of Knightian confusion and the ‘vividness effect.’ There was very little information about the outbreak, and all parties (government and citizens) were confronted with an “unknown unknown.” As a result, they became more vigilant, cautious, and disciplined. Second, the ‘vividness’ of the photographs coming out of Milan and New York influenced our views, and fear of the epidemic was widespread, with vigilance being the rule.
Our surprisingly quick escape from the first surge, on the other hand, resulted in the formation of perceptions and circumstances that are common in the development of financial bubbles. Many people succumbed to the so-called “recency bias,” because, like investors who extrapolate past returns into the future, stakeholders extrapolated the virus’s latest benevolent behavior well into the future. Overconfidence bias, in which an individual begins to overestimate his or her ability to handle danger, was rampant.
Many people faced infection for relatively low “returns” such as dinners, social parties, worship activities, and holidays, similar to overconfident consumers picking pennies in front of a bulldozer. Bayesian upgrading was also responsible for dangerous conduct. This applies to the process of changing previous assumptions about a phenomenon in light of new knowledge.
As the first wave sputtered to an end, those who had been cautious updated their views about the virus’s “mild” existence and threw caution to the wind. Vaccine apprehension grew as ‘rational investors’ balanced the uncertainties surrounding vaccine safety and effectiveness against the virus’s established but ‘manageable’ threats. This was exacerbated by a flurry of information about the protection and effectiveness of covid jabs. The virus had been hiding underneath the surface, poised to retaliate with a vengeance, like instability.
When financial bubbles collapse, a flight to safety arises, resulting in a lack of liquidity, bank runs, and a vicious negative feedback loop that threatens to destabilize an economy. Similarly, as the number of diseases increased, the precautionary motive began to dominate our behavior. Governments (both state and federal) were defensive, many people rushed to get oxygen tanks, concentrators, Remdesivir, and hospital beds even though they didn’t need them, shortages were self-fulfilling, and the poor were devastated.
The fact that we don’t understand the true essence of the mechanism that regulates virus mutation and propagation is at the root of the issue. Cases in India increased by nearly tenfold in a month, a phenomenon never seen before in a big country during the pandemic. In America, however, cases increased almost seven fold in less than four months. As a result, neither the pandemic nor its containment can be anticipated or managed using reactive techniques. It can only be hedged against using the same risk management principles as risk analysts use to shield themselves from unknown market return distributions.
Redundancy is the first concept of efficient risk control. This is accomplished in financial markets by capital and cash buffers. Even in the midst of the second wave, state and federal policymakers can do this by expanding healthcare capability beyond what is actually expected. And after the second wave subsides, this potential should not be unwound, but rather added to. This will protect us from potential covid shocks that could be much more serious than the one we are already experiencing.

India’s government must also develop some “real options” to protect against covid insecurity so that vaccines can be scaled up quickly. Paying vaccine producers for their fixed costs of capacity growth would be a simple way to do this. Which ensures that vaccine manufacturers don’t lose money if capacity isn’t used in the future due to a lack of demand. On the other hand, the government may have provided a mechanism for quickly increasing vaccine coverage in the event of a third wave, without having to commit to purchasing doses in advance.
To summarize, the probability, timing, and magnitude of a third wave are unknown, and the cost of creating insurance to protect against it is high, but one thing is certain: if we do not expend resources to protect ourselves against this erratic pathogen, we will be subjected to even higher human and economic costs.