Science - Technology

Demographers tackle Covid-19

Eryn Brown, Knowable Magazine

The research seemed straightforward: Analyze 2020 death records in Minnesota and, among other things, quantify which deaths were attributable to Covid-19 in various slices of the population — young and old, black and white, people living in advantaged versus disadvantaged neighborhoods.

But when University of Minnesota demographer Elizabeth Wrigley-Field began to dig in, the numbers revealed complex trends.

The records showed that last year more Minnesotans — especially non-whites — died at home than in a typical year, having avoided hospitals because of the pandemic. Such deaths were almost never reported as Covid-related, even though many probably were. The analysis suggested that Covid deaths in minority groups were going underreported.

It’s the sort of intriguing finding that is likely to percolate to the surface more frequently as researchers study Covid-19 from a population — or demographic — perspective.

Soon after the pandemic hit, demographers leaped into action. Today, there are studies afoot to examine a broad swath of inquiry: from questions about life expectancy to whether school closures really averted infections to how a single Covid death affects surviving family members’ physical and mental health. Even the relationship between exercise habits and social-distancing trends in US counties is under scrutiny.

● Historical demographer Steven Ruggles, a university colleague of Wrigley-Field, says researchers at the Institute for Social Research and Data Innovation are conducting at least a dozen Covid-related research projects. They’re mining sources ranging from spatial data from satellite imagery and remote sensing to time-use surveys in which people fill out diaries reporting their activities.

Demographers already have been studying state mortality records from the 1918 influenza pandemic to understand how different public health measures affected outcomes; Ruggles thinks that the patchwork US approach to Covid-19 measures such as masking will provide a similar opportunity for number-crunchers to analyze what worked and what didn’t in the fight against Covid.

● Demographer Alison Gemmill of the Johns Hopkins Bloomberg School of Public Health studies how acute stressors such as terror attacks and political shocks affect fertility and fetal health, in a population sense. Examining Covid’s effects was an obvious pivot. Fertility rates have been falling steadily in the US and other high-income countries around the world since the Great Recession of 2008, and Gemmill and others have found that in most high-income locations they fell even more in 2020, despite early speculation that bored couples being stuck at home might trigger a Covid baby boom.

“Demographers knew better, based on history — births fall in pandemics and recessions,” Gemmill says. “The big question is: Is this temporary, or does this have a permanent effect on childbearing? I think we’ll spend the next decades unpacking the consequences of this shock.”

● At UC Berkeley, Ayesha Mahmud is involved in a slew of new projects — from a description of “contact patterns” across the US during Covid (men have more contacts than women, young people have more contacts than older people) to analyses of vaccine strategies (demographic data already helped US public health officials figure out who should get a jab first in order to save the most lives; a future aim may be to reduce barriers to vaccine access and ensure equity across racial, ethnic and socioeconomic groups). Mahmud’s other work, in developing countries such as Bangladesh,  pairs viral genome data with anonymized cell phone records to help epidemiologists predict local upticks in Covid outbreaks. She hopes the method could someday be applied to all kinds of diseases: “We see a lot of other uses for these data beyond Covid,” she says.

These demographers don’t expect to study Covid indefinitely. But for now, the pace is frenetic, Wrigley-Field says. She’s already had five Covid-related studies published or under review, and several more are on the way. She adds that the volume of work being produced by the field as a whole is “overwhelming.” That’s not always good, she says: Some hasty studies she’s seen fail to shed light on the forces affecting pandemic outcomes.

Wrigley-Field says she would like to get back to studying the 1918 influenza pandemic, a major focus of her work before Covid-19. But in some ways, she already has — familiar themes are emerging anew.

In 2019, she coauthored an analysis of US deaths from infectious diseases from 1900 to 1948 that revealed a stark racial disparity: As terrible as the 1918 flu was, white mortality during that pandemic still remained lower than Black mortality had been for every other year in the study period.

She began to wonder if the pattern would repeat itself during Covid. To try to get at that, she embarked on a study to calculate how many excess deaths among white Americans in 2020 it would take to raise total white mortality in Covid times to levels higher than the Black mortality levels seen in non-Covid years. The number she arrived at: 400,000.

Final counts aren’t available yet, but Wrigley-Field’s calculations suggest that the excess deaths among whites probably won’t reach that number — suggesting that the early-20th century disparities she studied remain to this day.

“These results have radically reoriented what matters to me and what analyses I want to do,” she says. “I think I’ll be working on that problem for a long time.”

This article is part of  Reset: The Science of Crisis & Recovery , an ongoing  Knowable Magazine  series exploring how the world is navigating the coronavirus pandemic, its consequences and the way forward. Reset is supported by a grant from the Alfred P. Sloan Foundation.

10.1146/knowable-071421-2

This article originally appeared in Knowable Magazine, an independent journalistic endeavor from Annual Reviews. Sign up for the newsletter.


Knowable Magazine is an independent journalistic endeavor from Annual Reviews.

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