At the beginning of this year, policymakers in many countries, including the US and the EU, decided to lock down the entire country in order to save lives and to push back Covid-19. Their calculations were strongly influenced by work done by a few researchers at the Imperial College, London and the University of Chicago. Increasingly, the models and the numbers used to validate the conclusions regarding the wholesale lockdown recommended by these studies are being questioned. The pushback is quite universal.

The title of an oped in the Wall Street Journal on June 16 was very clear, "The Data Are In: It's Time for Major Reopening". Even in our neighbouring country, Dr Giridhar R Babu, Professor and Head Lifecourse Epidemiology, Public Health Foundation of India, wrote, "Revised CDC guidelines should prompt India to re-evaluate lockdown, which was more political than epidemiological". He strongly advocates that the new norm for mitigation ought to be a focus on "cluster spread". It is abundantly clear that clusters are a critical point of transmission. Many epidemiologists and economists are now suggesting that instead of promulgating a blanket lockdown, countries must switch to selective measures to identify and mitigate pockets of Covid-19 outbreak as they emerge.

The argument leading to the now-discredited heavy handed lockdown policy was simple and pretty straightforward. It went as follows. If we can save human lives by closing all economic activities, curtailing the movement of humans, and isolating individuals through "social distancing", the benefit measured by the value of each life (know as the value of statistical life or VSL) is in the millions of dollars. Most studies blindly used VSL estimates circulated by the Environmental Protection Agency (EPA) of the US government, which adjusting for inflation, gives a value of USD 9.5 million today. If the cost to the economy of saving this life is less than USD 9.5 million, then benefits outweigh the cost. How do we know what the cost is? In two research papers that were not peer-reviewed, or more commonly known as "working papers", both published in March 2020 in the midst of the pandemic, it was shown that the cost of saving a life, in terms of lost jobs, income, as well as avoiding hospital and medical costs that accompany morbidity and mortality is a fraction of USD 9.5 million. In other words, the cost-benefit ratio of a lockdown policy is overwhelmingly positive.

The working paper from Michael Greenstone and Vishan Nigam of the University of Chicago's Becker Friedman Institute for Economics purported to show that even moderate social distancing has the potential to save well over a million lives. Their estimates relied heavily on epidemiological models and values of key parameters used by Neil M Ferguson and his team at Imperial College, London.

Greenstone and Nigam estimated that in the USA, an estimated USD 8 trillion in mortality benefits accrue from lockdown and strict social distancing protocols. Their model relies directly on parameter values borrowed from the Imperial College model. "We project that 3-4 months of moderate social distancing beginning in late March 2020 would save 1.7 million lives by October 1. "

It is obvious that many of the strict "worst case" scenario policy prescriptions have failed to generate the benefits but has resulted in damages to economies. Lockdown was imposed without preparations, leading to unbelievable misery for large numbers of people who found themselves without jobs, income, food, or shelter—a situation that many governments seem unwilling to acknowledge. "Further, lockdown should have been used to identify, test and isolate, and treat the most vulnerable—the elderly, those with co-morbid conditions, etc. and this happened only a few countries." Dr Scott Gottlieb, a former US Commissioner of Food and Drugs, was critical of the US lockdown policy, which he said was based on public fears.

US Federal Reserve Chairman Powell has been candid, so far as mistaken policies adopted in the USA are concerned. "We are not experts on epidemiology, the spread of pandemics or anything like that," Powell said in an online event in late May. "We talk to experts, and the main answer they give you is things are highly uncertain." He said that the Fed did not try to establish its own central system for monitoring or recreating health data, but pulled extensively from the publicly available information, consultations with outside experts, and a massive amount of background reading.

A paper published in the journal Nature based on a study done by Global Policy Lab at the University of California, Berkeley shows that the shelter-in-place orders came at an extreme economic cost. In the same issue of Nature, researchers from the Imperial College also caution that even as lockdowns start to ease around the world, public health officials still have very limited tools to combat the coronavirus. It is now acknowledged, that the death toll would have been lower if residents of nursing homes had been shielded from infection, something that didn't happen effectively enough.

Other flaws in the Chicago and London models have now been detailed. Ironically, some models in recent weeks are still predicting that by October, there will be more than 200,000 deaths in the USA alone.

A study by Yale economists Barnett-Howell and Mobarak note that "in poor countries, the benefits of lockdowns may be lower (flattening the curve may not help in countries where health systems cannot cope with status quo demand, and the younger demographics in developing countries implies lower mortality rates), while the costs of lockdowns may be higher (interrupting all economic activities while livelihoods depend on day-to-day wages presents a large public health threat of its own)."

In a report on March 31, 2020, in Science, a publication of the American Association for the Advancement of Science (AAAS), the modellers' lack of data has come under severe criticism by James Stock of Harvard University. Stock, who served on the federal Council of Economic Advisers under former President Barack Obama, has recommended that researchers focus on the accuracy of parameters, the most critical of which is a better estimate of how deadly the disease is.

 "If it turns out a lot of people get infected and have few symptoms, the economically sensible approach might be to let the infection spread and accept that there will be some death toll," Stock says. "The policies are extremely different depending upon these parameters that we don't know."

Finally, some economists have questioned the benefits of strict lockdown and are advocating "smart containment" (SC).  The SC policy is based on the infection status of tested individuals. Those tested positive would be subject to stricter isolation than those who have recovered. According to Prof. Alexis Akira Toda, an economist at the University of California, San Diego, the benefits of social distancing could be achieved with less damage to the economy by publicising the level of infection in a given area. All of the economists agree that some policies are more effective if they are calibrated at the local level, with each city or region setting a policy based on the level of infection in that area. Toda, nonetheless, concedes that to avoid needless damage to the economy, the more stringent lockdown could be used when the epidemic is nearing a peak.

Dr Abdullah Shibli is an economist and works in information technology. He is Senior Research Fellow, International Sustainable Development Institute (ISDI), a think-tank in Boston, USA.