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Opinion | Lessons for the world from the coronaviral pandemic

The pandemic has brought to the fore a range of issues, from the vulnerability of our economic structures to the role of technology in the spread of misinformation

Any counter strategy, therefore, must view it as more than just a public health issue. We need to also acknowledge our individual roles that collectively contribute to such crises.Premium
Any counter strategy, therefore, must view it as more than just a public health issue. We need to also acknowledge our individual roles that collectively contribute to such crises.

As of the time of writing, there were 115,000 Covid-19 cases globally and climbing. These are very likely the tip of the iceberg, given limited testing and an incentive to hide cases to avoid wage and job losses. The Organization for Economic Cooperation and Development predicted that a half-percentage-point of global gross domestic product growth could be lost as an economic fallout of cancelled travel, closed factories, disrupted supply chains, and people staying home. Bloomberg Economics suggested that we could see zero growth this year if the virus isn’t contained soon. Hand-washing and social distancing appear to be slowing the spread, though the “infodemic of fake news", to borrow the phrase from World Health Organization (WHO) chief Tedros Ghebreyesus, offers a number of other perspectives and “solutions".

How did we become this fragile? What do we do about it, given the 21st century reality of complex, interconnected, and deeply influential changes that we’ll have to tackle, in some cases without even having the equivalent of the WHO and its infrastructure for global collaboration? All eyes are on public health right now, but we have climate change, water security, conflict, artificial intelligence, and more “wicked" problems waiting in the wings.

We highlight some of the critical research and strategy agendas that the present pandemic brings to the fore. Each is an example of the kind of interdisciplinary, interwoven, and action-oriented societal learning that we will need beyond public health policy.

How did we get to an economic structure in which Covid-19 could not only spook global stock markets, but also topple the real economy of supply chains, and goods and services production? Some of the fragility is local. The rise in corporate debt, for example, has made the US economy especially vulnerable to a temporary slowdown. However, there are also global roots in a market system that encourages lean, efficient, and distributed—disruptable—supply chains and a financial system that has not yet addressed the lessons of the 2008 economic contagion.

We will need to develop an ability to quantify and reward safety, not just efficiency. This is in part a behavioural question. How do we make “the dog that didn’t bark" real enough to pay for, in public procurement, consumer goods and services? It’s also a question of the relationship between markets and states. Competition creates pressure to cut costs and sometimes corners. How can we adjust incentives? And it’s a data question as well. Even if we want to reward safety, how do we know it when we see it?

Second, how did our digital superpowers, which ought to have had the ability to accurately track the disease, coordinate responses and spread warnings farther, wider and faster, collapse so quickly under pressure? Early news of the virus got out of the gate fast on social media, only to be shut down by censorship. A loose network of researchers, sharing findings on Twitter along with more dedicated platforms such as the Global Initiative on Sharing All Influenza Data, or GISAID, is tracking the spread of the virus, using slight genetic variations to deduce transmission patterns, only to be drowned out by conspiracy theories and pangolin memes. We have greater technical ability to trace contacts and interactions than ever before, but we’re using those skills awkwardly, not at all in some places, or perhaps too enthusiastically in others (e.g. South Korea’s SMS broadcasts of some patients’ detailed travel histories).

We will have to accelerate emerging efforts to filter fact from fiction and manage viral misinformation. Massive editing is a technology challenge; building greater immunity to clickbait is a social and cultural question. We will also have to grapple with ethical questions about the use of technologies and emergency powers that will have demonstrated their practical utility but are ripe for abuse. Government investment in—and tacit permissions for—digital surveillance rose in the wake of the 9/11, 26/11, and other terrorist attacks. Do we want to see the same kind of leaps post-Covid-19?

Third, how did we let a predictable risk become an inevitability? It’s not because we didn’t know that we should prepare for it or attempt to prevent it. We have history, fiction, expert reports and ongoing surveillance. We know, in detail, the factors that increase the possibility of novel (to humans) viruses. When we crowd out wildlife and pack livestock together in confined spaces, the potential for emerging infectious diseases rises. We’ve had dress rehearsals: SARS, MERS and H1N1. Why did we keep doing it?

We’ll have to somehow fix our blindness to externalities and become more accustomed to recognizing the individually small but collectively large role we have played in creating most of the 21st century risks. This is a science and data agenda, in the sense that stronger attribution—demonstrated connection of outcomes to contributors—could help. It is a communication problem: how can we make abstract considerations more personal and salient? It is also an institutional design challenge: what metrics and indicators might guide policy, market and social systems toward better outcomes?

It’s easier to write this down than make it happen. However, acknowledgement is the first step towards action.

Kapil Viswanathan & Jessica Seddon are, respectively, vice-chairman of Krea University and research fellow at Princeton University

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Updated: 12 Mar 2020, 10:52 PM IST
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