Hi everyone. I'm Ryan Calder,
Assistant Professor in
the Department of Population Health Sciences
at Virginia Tech here to report on
the work by my colleagues and myself investigating
the interactions between COVID-19 and the food-
energy-water nexus.
Both to share findings so far and
our opinions on priority areas for future work.
Very quickly in the pandemic,
it became clear that COVID was going
to be experienced not only as
an infectious disease but was
going to be felt in many aspects of society,
including at the food-energy-water nexus .
In the first weeks and months,
we saw headlines like these.
People whose incomes had been disrupted,
unable to pay for energy and water bills,
and facing utility disconnections,
wildly forecasted blackouts due to higher
than usual residential occupancy in the summer months.
To our knowledge, this didn't really
come to pass because there were, in most cases,
other factors that led to net decreases in demand
and so transmission systems were able
to weather that stress.
Early in the pandemic when there was a lot of uncertainty
around principal transmission pathways,
hand washing was very heavily promoted as
a health intervention and it
became clear that in
very water-stressed parts of the world,
there was a real trade off between
vastly increasing the frequency
of hand-washing and water availability
for other purposes, including agricultural purposes.
This is in addition, of course,
to the widely publicized outbreaks
in meat processing plants
and other industrial food facilities.
This has had really bad impacts for food workers,
of course, and their health, to some extent,
is everyone's health because
food workers are responsible for maintaining
the integrity of the food system and for
ensuring nutritional sufficiency
in the general population.
When COVID hit, we had recently begun
a SESYNC pursued under the leadership of
Rebecca Muenich from Arizona State and Rebecca Hale from
Idaho State with the goal of
developing a typology of food,
energy, water stresses across
the United States in order
to more systematically identify
social and other drivers of
those stresses and to identify opportunities for
policy transfer based on
commonalities in physical systems at
play and other factors.
So when COVID struck,
we decided to devote a fraction of our effort to
understanding the impacts on
the food-energy-water system.
Understandably, the vast majority of
public health attention has focused
on the spread of COVID-19
and the impact of COVID-19 infection on people's health,
so fatalities, hospital admissions, and so on.
Conversely, we wanted to understand
how COVID-19 disrupted food,
energy, water processes,
and how food, energy,
and water insecurities affected
health outcomes as an indirect impact of
COVID-19 or at least
inventory what research was ongoing in that direction.
Finally, we wanted to understand how the food, energy,
water nexus was in turn
accelerating or attenuating the spread of COVID-19.
For instance, we already saw that example
of outbreaks in meat processing plants.
Graphical models are being used in
more and more fields to justify decision-making by being
explicit about assumptions about
the natural or social variables
that drive some system of interest,
and they go by different names,
such as theory of change,
pathways of change, logic models, etc.
They're very useful tools,
in my opinion, for organizing,
thinking about what are sometimes
very complex systems around key causal dependencies.
We set out to make a graphical model for
COVID-19 and the interaction with the food, energy,
water nexus by scraping journal articles and
news and media articles that
had come out in roughly the first year
of the pandemic by coding
the causal relationships asserted
or studied by other authors
and then by identifying
system dynamics that were either observed in
COVID-19 or could emerge in
a future pandemic if certain variables changed,
for instance, if a future pandemic
had much worse impacts on working-age people,
for instance, than COVID-19 did.
This actually applied methods that we developed
previously to make unified graphical models out
of disparate research by
authors working at different levels of detail in
different settings and so on.
One of the big challenges of making
comprehensive graphical models that integrates research
carried out at different levels of
spatial and temporal detail is
that as the relationships you
represent become more mechanistically explicit,
that's what we're representing here with network depth,
the number of concepts,
the number of individual relationships
represented increases exponentially,
which starts to pose a real barrier to
interpretability for decision-making or
usability of the model.
So there's a trade-off between
mechanistic detail and usability in some sense.
We describe that in more detail in this paper
with the full citation details on the previous slide.
Pretty early on in our work,
we figured out that there were
only so many lessons to be drawn from previous pandemics.
Even though the 20th century had
at least three major respiratory virus pandemics with
direct death tolls comparable
to COVID-19 effects on other parts of society,
including effects on what today we would call the food-
energy-water nexus, were very different.
For starters, the most recent
major respiratory virus pandemic
prior to COVID-19,
the H3N2 outbreak of 1968-69 occurred at
a time when many of
the interventions that we've taken during COVID-19,
such as widespread work from home and social distancing,
were not as feasible.
A lot of the worst-case outcomes that we
as a society had been working so
diligently to avoid in COVID-19,
such as hospitals running out of capacity,
did indeed occur in the context of H3N2,
and they seem to have been viewed
with a greater amount of inevitability or
maybe fatalism than we
would seem to find
acceptable today in the context of COVID-19.
Newspaper articles from this era are very interesting
and illustrative of difference
in attitude around those outcomes.
Second, the food-energy-water-space
and the food system in particular today,
are much more susceptible to disruptions
from outbreaks than they were
even in the '60s because of
the really substantial centralization and
consolidation of food production
into a smaller number of physical locations.
That has really reduced
the redundancy and the resiliency of the food system,
in particular, the viral pandemics.
I would argue that that has
both increased the indirect impacts of
viral pandemics on human health
by creating the supply side risks for food security,
and has also made interventions like
social distancing and lock downs
of non-essential workers.
More important now than maybe they were in
the '60s because food-energy-water infrastructure
seems to be more vulnerable
to breakdown from viral outbreaks.
These differences are really
important because as we'll see
several of the major impacts of
COVID-19 on the food-energy-water
space are not due to morbidity and mortality per se,
but rather due to economic disruptions,
especially in the early months of the pandemic,
when certain sectors of the economy were suddenly
closed without much of
a follow-up plan and
how to support workers in the immediate aftermath.
This work culminated in a paper that came out in E,
S, and T letters in July.
This schematic shows how we represent it at a high level,
the system dynamics that we haven't covered.
First, of course, COVID-19 directly affects human health
via viral infection and spread,
but it also affects labor inputs
to the food-energy-water system.
For example, when workers get sick or when
consumers whose incomes have been
disrupted can't make utility payments which
have affected energy and water sectors particularly hard.
Meanwhile, risks to the food-energy-water system
from supply-side breakdowns
and demand-side barriers.
Also heavy human health impact, unfortunately,
particularly among the very people who are
also most at risk from COVID-19,
and those interactions are not very well understood.
Finally, like we saw
earlier large centralized industrial
food operations have played
a major role in
spreading COVID-19 and keeping the whole thing going.
This is a more granular representation
of causal relations with
the solid lines reflecting relationships that we
did identify in the peer-reviewed literature,
and dashed lines representing
relationships that we hypothesized,
but didn't identify where that we've found
alluded to in news and media articles,
but didn't find investigated
in peer-reviewed articles so far.
The pluses represent positive associations
and the minuses represent negative associations.
Our overarching interest in constructing
this framework was in understanding how
the net impacts of burden of disease of all of
these interacting processes and
whether the system dynamics and the
food-energy-water spaces
tend to attenuate or amplify these impacts.
We use this framework to identify
feedbacks and trade-offs and potential gaps and research
needs that we go into in greater detail in the article.
Then I'll have time to do in this talk.
I guess also the advantage of
this pre-recorded video is
that people who are really curious
and the nuts and bolts of this can
pause and zoom in before moving on.
One of our biggest observations.
This is probably no surprise is that
COVID-19 has presented us with
many trade-offs for which there is
actually very little quantitative modeling capacity.
For example, water use optimization
between hand-washing and other things.
For COVID-19, hand-to-hand transmission
turned out not to be a very important pathway,
but a future disease might make
that optimization exercise more urgent,
or a more widely discussed trade-off around
mental health impacts of extended physical distancing,
particularly among populations with
lower case fatality rates.
This is not a food-energy-water thing,
but it's probably the most urgent.
To our knowledge, there is no quantitative analysis
of the net impacts on different populations.
This is partially due to
a lack of data so far, but hopefully,
as more data are reported,
more quantitatively, explicit comparisons can be drawn.
In COVID-19,
to a large extent,
I would argue that we have been lucky
that case fatality rates among
younger people have been quite
low because
probably averted major supply-side breakdowns.
That was not at all guaranteed to be the case.
If you compare COVID-19, for example,
to the 1918 H1N1 pandemic,
the relative case fatality rate
between younger people and
older people was almost exactly opposite.
In the United States,
case fatality rate among 18-29 year-olds was about 130
times lower than those among 65-74 year-olds.
This is, of course, prior to vaccination.
In the H1N1 pandemic of 1918,
it was the opposite with
case fatality rates among 15-44 year-olds,
120 times higher than among over 65 year-olds.
It is alarmingly easy to
imagine a much worse outcome on the supply side.
This led us to ask,
what would the effects on the food-energy-water nexus
be if COVID-19 had looked more
like the 1918 H1N1 pandemic,
at least in terms of age effects?
The food system in particular,
is much more vulnerable than it was
to viral outbreaks given
the consolidation of activities in
a smaller number of physical locations like we saw.
However, existing food-energy-water models
have very little ability
to evaluate the effect of labor shortfalls.
That seems like a major gap that needs to be bridged in
order to build resiliency against future pandemics.
With that, I would like to thank
my co-authors and collaborators.
The maroon box is the co-authors on the
E, S, and T letters paper.
The orange box is
the broader SESYNC team
that I've been working with since 2019.
Rebecca Hale and Becca Meunich, like I say,
are the PIs on the SESYNC team without whose leadership,
this work would not have occurred.
This is where in normal life I would take questions,
but instead here I'll invite you to
email me or track me down
at AGU in New Orleans. Thank you.