Killing the Curve in Pakistan: How Models Failed & Why Targeted Interventions Worked

An inherent weakness of statistical models is the representative agent, where a diverse population of a country with a multitude of differentiating factors is clubbed as one monolithic entity. Epidemiological models like the SRI Model, which provided earlier doomsday predictions for Pakistan assumed the population to be one monolithic entity, which was never the case. Such are the pitfalls of models, and hence they should only be used for guidance, rather than undeniable truth. A considerably younger population with a median age of 22 years, compared to greater than 35 years for other jurisdictions also provided a hedge against the disease, as fatalities are largely skewed towards a more senior segment of the population (> 65 years). The positive testing ratio for Pakistan, which went as high as 20%, is now less than 5% and continues to decline.

Early non-pharmaceutical intervention through the closure of schools, a full-fledged lockdown to ramp up healthcare capacity, closure of shopping malls, restricted working hours for markets, etc. also contributed to reducing the network effect. Constant communication about the dangers of the disease, as well as the importance of masks, ensured that the network effect was dampened. Even if a small minority continues to wears mask, the chain breaks, and the probability of infection declines significantly. Novel coronavirus spreads through networks, with greater connectivity resulting in the higher spread. The epidemiological models assumed uniform connectivity across the board, whether someone was a frequent international traveler or someone who had never stepped foot outside his village – they both were assumed to have similar connectedness. R0 which is often touted as a metric for how quickly a disease is spreading, went as high as 2.12x following Eid-ul-Fitr, only to reduce considerably to less than 0.7x. As a thumb rule, an R0 of greater than 1 signifies a pandemic, while less than 1 signifies that the spread is under control.

As the disease spread through more prosperous, and urban areas of Pakistan – the rest of the country could not really figure what the hoopla was all about. A review of testing and death data per 100k population exhibits that Islamabad, Karachi South, Karachi Central, Karachi East, and Lahore had the highest number of cases and deaths. The ramp-up in a number of cases after Eid-ul-Fitr clearly demonstrated that the spread was largely restricted to a few urban hotspots, which could be further filtered down to the district level, and could be tackled through direct interventions.

The government through its targeted interventions, and by avoiding cookie-cutter models imported from more prosperous (and aged) jurisdictions, not only flattened the proverbial curve but also killed it. In the case of Pakistan, novel coronavirus is largely a rich man’s disease, and hence created more noise than many other diseases stemming from lack of nutrition, or availability of clean water. Many are calling flattening (or killing) a miracle. This is not a miracle. This is the result of targeted interventions by the State, which understood the properties of the problem at hand and designed policies accordingly.

It may be too early to declare victory over an invisible micro enemy, as schools still need to open up, markets still need to resume normal working hours, and so on. This may lead to a second wave – but there is a sense of comfort that the State has been successful in taming the curve, and would be able to control the R0 as the economy slowly progresses towards a new normal.