3 min readNew DelhiJul 30, 2020 08:05 AM IST
First published on: Jul 30, 2020 at 08:05 AM IST
People line up to consult doctors at a Covid-19 screening facility inside a government hospital in Jammu on July 21, 2020. (AP Photo: Channi Anand)
It’s been four months since the world’s most stringent lockdown was imposed with four hours’ notice on over a billion unprepared people with the promise, buttressed by scientific jargon and graphs of curves. But even after this extreme action — which was supposed to flatten the curve of infection down to zero by mid-May — India continues to struggle with the epidemic across different cities and towns.
What went wrong?
“The history of this pandemic is littered with premature, and often inaccurate, scientific predictions ranging from the estimates of the numbers of people who will die unless nations impose a lockdown to the effectiveness of drug treatments,” writes Vikram Patel, the Pershing Square Professor of Global Health at Harvard Medical School, in The Indian Express.
“Crowning these scientific disciplines is the field of modelling, for it was its estimates of mountains of dead bodies which fuelled the panic and led to the unprecedented restrictions on public life around the world,” he writes.
None of these early models, however, explicitly acknowledged the huge assumptions that were made, for example, that mortality was distributed evenly across the population (incorrect, because it is heavily concentrated in the elderly) or that everyone who is not infected is vulnerable (likely to be incorrect as evidence of innate immunity mounts).
Patel writes that “this kind of tunnel vision has characterised scientific proclamations from the outset of the pandemic, with little attention to their societal implications”. The fact that many lives will be lost as a result of the lockdowns is now emerging across the world.
Patel writes that scientists have “failed in our obligation to acknowledge the uncertainties in our observations, the limitations of our methods and the importance of other traditions of knowledge”.
“While science-informed policies are an aspiration, we also need to appreciate their limitations and assumptions to ensure that such policies do not lead to avoidable harms and promise unrealistic results,” he concludes.
People line up to consult doctors at a Covid-19 screening facility inside a government hospital in Jammu on July 21, 2020. (AP Photo: Channi Anand)
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