OSPE - The Voice - June 2020 - 32

ENGINEERING ACADEMY

Aleman acknowledges
the strength of
R0 in showing
epidemiological curves
for quick mapping,
because it requires
limited data. However,
with that speed comes
a lack of workable
information.

THE VOICE Summer 2020

to be around 2.3. One infected individual
turns into two infected individuals and
that's how we get that exponential spread."
While the simplicity of the R0 number
allows it to be applied broadly, it comes
with its own set of flaws. "While it might
describe the trajectory of a pandemic in
a city or worldwide pretty well, it doesn't
necessarily help to understand what is the
impact of individual polices like telling
people to socially distance themselves,
closing schools and universities, closing
down workplaces, because all of these
different ways that people have contact with each other."
Rather than broad based data collection, Aleman and her team are interested in
how specific demographic data sets interact with each other. Not only the number of
citizens in a city, but who lives in what neighborhood? Which transit systems do they
take? Which routes of that transit system are they taking? By collecting as much data as
possible, and making it intersect in their pandemic modelling system, Aleman can retrieve
precise information on how a virus might spread. "The reproduction number in each of
those situations should be different. Just thinking of kids: they're germy and have no
sense of hygiene or personal space, so germs spread like wildfire amongst children. One
would think that the R0 for any disease would be much higher within a school than say a
restaurant or an office. People have very different types of contact between each other."
Aleman acknowledges the strength of R0 in showing epidemiological curves for
quick mapping, because it requires limited data. However, with that speed comes a lack
of workable information. "We wanted to know if we had something that really looked at
person to person contact and possibility of person to person transmission where any two
people might have a different rate of transmitting or receiving the disease."
This optimization strategy is at the heart of industrial engineering and its ability to find
efficient solutions that are applicable to policy. Because their data is specific and could
pinpoint crucial factors, it can lead to government policy decisions that target the right
groups. As Aleman says, "Rather than just saying elderly people are much more impacted...
maybe it's people of a particular age group, who live in a particular neighborhood who
take a particular transit route."
Unfortunately, by applying industrial engineering to medical decision making, Aleman
experiences difficulties within these medical community. As with any innovation, there
can sometimes be resistance to change. While COVID-19 sheds a glaring light on the
importance of this kind of cross-pollinated thinking, Aleman reports that not everyone
understands the interdisciplinary process, "Ultimately it is difficult to get research funding
for this type of work because the techniques that are involved are not necessarily novel
from an engineering perspective. From a medical side, it's sort of a vast departure from

OSPE - The Voice - June 2020

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