The link between transit use and early COVID cases

Date:
April 14, 2022
Source:
Georgia Institute of Technology
Summary:
A new study looks at the association between America's mass
transportation usage and case counts in opening months of the
pandemic.



FULL STORY ========================================================================== Researchers from Georgia Tech's Colleges of Engineering and Computing
have completed the first published study on the link between America's
mass transit use and Covid-19 cases at the beginning of the pandemic.


========================================================================== Using data from the Federal Highway Administration's National Household
Travel Survey, the team looked at the nation's 52 largest metropolitan
areas and each community's likelihood of riding buses and trains. They
then compared the numbers with the 838,000 confirmed Covid cases on the
Johns Hopkins Center for Systems Science and Engineering's dashboard
from Jan. 22 -- May 1, 2020.

The timeframe covers the initial days, weeks, and months of the
pandemic, before mask mandates were in place and prior to widespread
social distancing.

Ventilation on public transit had yet to be addressed, along with other
public health measures that have since become the norm.

The study found that cities with high-usage public transportation systems displayed higher per capita Covid incidence. This was true when other
factors, such as education, poverty levels, and household crowding,
were accounted for.

The association continued to be statistically significant even when the
model was run without data from transit-friendly New York City.

The paper, "Investigating the association between mass transit adoption
and COVID-19 infections in US metropolitan areas," is published in the
journal Science of the Total Environment. While the researchers don't
suggest that transit is the sole cause of the high incidence rates,
they say it could have been an important factor early in the pandemic.

"This is what we expected, but we wanted to run the models to know
for sure.

Policymakers shouldn't make decisions based on what they assume to
be true," said Michael Thomas, one of the study's co-authors and a
Ph.D. student in Georgia Tech's School of Computational Science and Engineering. "This study is similar to dusting off a dinosaur dig site
and finding a leg bone. This isn't the entire dinosaur. There are many
ways of making the argument about Covid spread, and transit is just
part of it." The team got the idea of tracking transit and Covid cases
after watching early reports from Wuhan, China, and reflecting on how differences in public transportation systems may factor into pandemic
spread patterns. As assumptions were being made about how American cities should react based on ridership patterns on the other side of the globe, Professor John Taylor thought the pandemic shouldn't be treated as a
"one size fits all" situation.



==========================================================================
"In the initial months of the pandemic, models were being developed
here at home based on incidence rates in Wuhan. But, in terms of mass
transit ridership behavior, China's may be far different than what we
see in American cities," said Taylor, Frederick Law Olmsted Professor
and associate chair for graduate programs and research innovation in the
School of Civil and Environmental Engineering. "For instance, people in
Chinese urban areas often stand in long, single file lines as they wait
for trains and buses. We don't. Different spread patterns can develop
because of differences in mass transit behaviors." Taylor's primary
research focuses on the dynamics that can occur at the intersection of
human and engineered networks, such as how people change electricity consumption behaviors and changing mobility patterns in natural
disasters. Pandemics were on his research radar before Covid became a
household name, as Taylor wanted to create better models to forecast
the spread of illnesses. His first research effort in this direction
was tracking the Ebola virus that reached Texas in 2014.

In the fall of 2019, Thomas was working as a biostatistician at the
Georgia Department of Public Health when he spoke with Taylor about
pursuing his Ph.D.

Thomas submitted his application to Georgia Tech that November -- just
four months before Covid shut down America.

The two, along with study co-author and senior research engineer Neda Mohammadi, are now creating models to predict the spread of future
illnesses among populations. They're also looking to demonstrate how researchers can modify those models for better accuracy.

"If engineers and scientists can better understand the factors
of community spread, policymakers can make faster, more accurate
decisions to protect public health," said Thomas. "In transportation,
for example, it could lead to quicker decisions to restrict the number
of people on buses. Or policies to stagger vehicle departure times more consistently. Studies like ours provide a basis for those decisions."
Having more accurate models also takes varying human behavior into
account, according to the researchers. Just as people in Wuhan wait for
public transportation differently than those here in America, cities
can differ from each other.

"Your pandemic is different than your neighbor's," said
Mohammadi. "Pandemic spread isn't the same from city to city, nor
is ridership. Decision makers often look to other communities to
see how they're responding to shape their actions. That's not always
accurate. Models need to be customizable because populations don't react uniformly. It's our goal to improve decision making to be easier, faster,
and more accurate for the next pandemic."

========================================================================== Story Source: Materials provided by
Georgia_Institute_of_Technology. Original written by Jason Maderer. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Michael M. Thomas, Neda Mohammadi, John E. Taylor. Investigating the
association between mass transit adoption and COVID-19 infections
in US metropolitan areas. Science of The Total Environment, 2022;
811: 152284 DOI: 10.1016/j.scitotenv.2021.152284 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/04/220414110903.htm

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