Reimagining our pandemic issues with the mindset of an engineer


Good science is humble and able to refining itself within the face of uncertainty.

Marc Lipsitch

Susan Holmes, a statistician at Stanford who was not concerned on this analysis, additionally sees parallels with the engineering mindset. “An engineer is at all times updating their image,” she says—revising as new knowledge and instruments grow to be accessible. In tackling an issue, an engineer affords a first-order approximation (blurry), then a second-order approximation (extra targeted), and so forth.

Gelman, nevertheless, has beforehand warned that statistical science might be deployed as a machine for “laundering uncertainty”—intentionally or not, crappy (unsure) knowledge are rolled collectively and made to appear convincing (sure). Statistics wielded in opposition to uncertainties “are all too usually offered as a form of alchemy that can remodel these uncertainties into certainty.”

We witnessed this throughout the pandemic. Drowning in upheaval and unknowns, epidemiologists and statisticians—newbie and professional alike—grasped for one thing stable as they tried to remain afloat. However as Gelman factors out, wanting certainty throughout a pandemic is inappropriate and unrealistic. “Untimely certainty has been a part of the problem of choices within the pandemic,” he says. “This leaping round between uncertainty and certainty has precipitated a whole lot of issues.”

Letting go of the need for certainty might be liberating, he says. And this, partially, is the place the engineering perspective is available in.

A tinkering mindset

For Seth Guikema, co-director of the Middle for Threat Evaluation and Knowledgeable Choice Engineering on the College of Michigan (and a collaborator of Zelner’s on different initiatives), a key facet of the engineering method is diving into the uncertainty, analyzing the mess, after which taking a step again, with the attitude “We’ve to make sensible selections, so how a lot does the uncertainty actually matter?” As a result of if there’s a whole lot of uncertainty—and if the uncertainty adjustments what the optimum selections are, and even what the great selections are—then that’s essential to know, says Guikema. “But when it doesn’t actually have an effect on what my finest selections are, then it’s much less crucial.”

As an illustration, growing SARS-CoV-2 vaccination protection throughout the inhabitants is one state of affairs during which even when there may be some uncertainty concerning precisely what number of instances or deaths vaccination will stop, the truth that it’s extremely more likely to lower each, with few opposed results, is motivation sufficient to resolve {that a} large-scale vaccination program is a good suggestion.

An engineer is at all times updating their image.

Susan Holmes

Engineers, Holmes factors out, are additionally superb at breaking issues down into crucial items, making use of rigorously chosen instruments, and optimizing for options underneath constraints. With a crew of engineers constructing a bridge, there’s a specialist in cement and a specialist in metal, a wind engineer and a structural engineer. “All of the totally different specialties work collectively,” she says.

For Zelner, the notion of epidemiology as an engineering self-discipline is one thing he  picked up from his father, a mechanical engineer who began his personal firm designing health-care services. Drawing on a childhood stuffed with constructing and fixing issues, his engineering mindset entails tinkering—refining a transmission mannequin, as an illustration, in response to a transferring goal.



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