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Coronavirus pandemic
OpinionComment
Sun Sun Lim
Roland Bouffanais
Sun Sun LimandRoland Bouffanais

Opinion | How cities can avoid costly lockdowns with smart use of big data

  • Instead of locking down an entire city, officials can shut down or reconfigure specific locations with a high potential to trigger outbreaks by tapping big data
  • As lockdowns can be devastating for businesses, a robust, data-grounded approach can help governments justify tough decisions

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Commuters alight at Admiralty MTR station on August 19. Tracking human mobility and combining that data with epidemiological evidence can help cities pinpoint areas at risk of super-spreading events without having to shut down the entire city and its economy. Photo: Nora Tam
Sun Sun LimandRoland Bouffanais

You impose a lockdown. With people confined indoors, shops close and the economy grinds to a halt. Your Covid-19 infections fall to pleasing numbers, and soon it appears safe to end the lockdown and reopen your economy. Businesses open, people come out in droves and some sense of normalcy returns.

Before you know it, new virus outbreaks emerge and clusters expand and spread, threatening to overwhelm your health care services. You impose a lockdown, rinse and repeat.

Cities around the world have entered seemingly endless cycles of lockdowns and viral resurgence.

Although there is encouraging progress towards viable vaccines, lockdowns of varying extents are the main tactic to contain Covid-19 when exponential growth in community cases occurs. Yet lockdowns are blunt tools that exact heavy costs such as severe economic malaise and the declining well-being of entire populations sequestered at home. Some experts have cautioned that this disruptive lockdown cure is worse than the disease, claiming lives through job losses, social isolation and domestic strife.
Cities in particular can attempt to break free from the lockdown trap by identifying super-spreader locales. Instead of locking down the entire city, a more sustainable approach is shutting down or reconfiguring specific locations with high potential to trigger outbreaks by tapping insights from big data.

Like people, certain places can be spatial super-spreaders, and big data is the key to identifying these weak links. Cities are constantly throbbing with human activity as people transit, converge, mingle and disperse. Currently available human mobility data must therefore be mined to zero-in on vulnerable locations beset by the dangerous confluence of high human traffic, intense social interaction and conditions favourable to disease spread.

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