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\begin{document}

\title{Don't panic, it is only an emergency}



\author[1]{Mathew Mercuri  }%
\affil[1]{Mcmaster University}%


\vspace{-1em}



  
  \date{May 07, 2024}


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\begin{abstract}
Since news of COVID-19 outbreak hit the mainstream media, I have
received several calls from acquaintances about if and how they should
be worried. I suspect many readers of the~\emph{Journal of Evaluation in
Clinical Practice}~have experienced the same. What makes communicating
the risk difficult can be illustrated through a recent assignment I gave
to my undergraduate class focused on how we use science in public
policy. I asked the students to identify claims in the media regarding
the virus and then search the literature to assess the level of support
for such claims. Suffice it to say, they found several claims
unsupported, and several others to be inconclusive. Not very good
grounding for providing definitive (or even satisfying) advice.%
\end{abstract}%



\sloppy




\textbf{Don't panic, it is only an emergency}

Mathew Mercuri PhD\textsuperscript{1,2,3}

\textsuperscript{1}Editor-in-Chief, Journal of Evaluation in Clinical
Practice

\textsuperscript{2}Department of Medicine, McMaster University,
Hamilton, Canada

\textsuperscript{3}Institute of Health Policy, Management and
Evaluation, Dalla Lana School of Public Health, University of Toronto,
Toronto, Canada

Correspondence to:

Mathew Mercuri

Hamilton General Hospital, McMaster Wing, Rm 242

237 Barton Street East, Hamilton, Ontario, Canada, L8L 2X2

Email: matmercuri@hotmail.com

``It's a dangerous business, Frodo, going out your door. You step onto
the road, and if you keep your feet, there's no knowing in where you
might be swept off to''. -- J.R.R. Tolkien, The Lord of the Rings.

Since news of COVID-19 outbreak hit the mainstream media, I have
received several calls from acquaintances about if and how they should
be worried. I suspect many readers of the \emph{Journal of Evaluation in
Clinical Practice} have experienced the same. What makes communicating
the risk difficult can be illustrated through a recent assignment I gave
to my undergraduate class focused on how we use science in public
policy. I asked the students to identify claims in the media regarding
the virus and then search the literature to assess the level of support
for such claims. Suffice it to say, they found several claims
unsupported, and several others to be inconclusive. Not very good
grounding for providing definitive (or even satisfying) advice.

Granted, my students are not professional health scientists. However, I
suspect that even those of us trained in epidemiology would have trouble
in coming up with something much better, or at least good enough to put
one's mind at ease. Adding to the challenge is the language used by our
health officials. For example, on January 30, 2020 the WHO designated
the virus a ``Public Health Emergency of International Concern''. To the
lay public, terms such as ``emergency'' and ``international concern''
are troubling. How troubled should one be? Let us look at that
terminology a bit deeper. By the International Health Regulations (IHR)
definition, a public health emergency of International concern is:

\begin{quote}
an extraordinary event which is determined, as provided in these
Regulations: i. to constitute a public health risk to other States
through the international spread of disease; and ii. to potentially
require a coordinated international response. This definition implies a
situation that: is serious, unusual or unexpected; carries implications
to public health beyond the affected State's national border; and may
require immediate international
action.11https://www.who.int/ihr/procedures/pheic/en/
\end{quote}

The definition states that one necessary criteria is the disease be a
public health risk to other States through international spread. That
part of the definition does not stipulate what is the threshold of risk,
nor does it indicate how many States must be at such risk. Influenza
would meet that criteria, and yet, it typically does not merit the
designation (the 2009 H1N1 outbreak is one exception). The reason for
the general exclusion of influenza is found in the latter part of the
definition -- i.e. ``serious, unusual, or unexpected''. Certainly, the
common flu is serious, as it causes significant morbidity and mortality
around the world each year. However, it is not ``unusual'' or
``unexpected''. That distinction raises another issue in how to
interpret the designation. ``Serious'', ``usual'', and ``unexpected''
are not synonymous. The use of an ``or'' conjunct suggests that these
are alternatives (i.e. they are not all required). Something can be
``unexpected'' but not be ``serious''. The question is can something
warrant risk to other States through international spread and not be
``serious''? I suppose that depends on how one defines serious --
something that I suspect differs between individuals and between lay
people and experts. A second necessary criteria is that the disease
(potentially) requires a coordinated action from the international
community. Presumably, that could range from simply sharing data, to
sharing and redistributing resources, to closing borders and instituting
quarantine strategies for people crossing borders. Certainly, the
definition can be interpreted in several different ways of differing
degrees. I do not doubt that members of the WHO and epidemiologists who
study infectious disease have an intuitive and somewhat consistent
understanding of when the definition is met. However, one can see how
members of the public trying to make sense of the meaning may have
difficulty.

Another issue is the communication of risk. For example, at the time of
writing this editorial, the Public Health Agency of Canada had:

\begin{quote}
assessed the public health risk associated with COVID-19 as
\textbf{low}{[}their emphasis{]} for the general population in Canada
but this could change rapidly. There is increased risk of more severe
outcomes for Canadians: aged 65 and over, with compromised immune
systems, with underlying medical
conditions.22https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html
\end{quote}

A similar statement was issued by the American Centers for Disease
Control and Prevention (CDC): ``The immediate risk of being exposed to
this virus is still low for most Americans, but as the outbreak expands,
that risk will
increase.''33https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/summary.html?CDC\_AA\_refVal=https\%3A\%2F\%2Fwww.cdc.gov\%2Fcoronavirus\%2F2019-ncov\%2Fsummary.html
What does ``low'' risk mean? Lichtenstein and Newman {[}1{]} showed
there is incredible variability in how people interpret verbal phrases
associated with numerical probabilities. For example, the range of
probabilities assigned by participants to terms that might be associated
with ``low'', such as ``somewhat unlikely'', ``very unlikely'', and
``seldom'', include estimates as low as 0.01 and as high as 0.8. It has
also been shown that experts can have a very different impression of
risks than do lay people {[}2{]}. Classic research on risk perception
shows that there is a tendency to overestimate risk when outcomes are
dreadful or impact a lot of people in a short period of time (e.g.
catastrophic events) or when we feel a lack of control {[}3{]}. I
suspect that a pandemic certainly fits that criteria in the eyes of
many. Thus, it is not surprising that some would overreact, nor is it
surprising that some would not take the issue seriously.

The difficulty in communicating risk is not new to health care. Consider
the example of exposure to ionizing radiation from diagnostic imaging or
fluoroscopy guided interventional radiology/cardiology procedures. Such
risks (if they are known) can be presented as absolute risk (e.g.
probability of cancer induction following exposure) or as relative risk
(e.g. risk as a fraction of a naturally occurring risk). The former
approach is often confusing for patients -- what does 1 in 1000 mean to
the individual, especially in a world with poor numeracy? The latter
might come across as abstract or will simply scare patients -- a dose
equivalent to a year's worth of natural background radiation is
meaningless to someone who does not know what is the health impact of a
year's worth of natural background radiation, and describing a CT scan
as the equivalent of 100 chest radiographs sounds dreadful, even if the
dose from a chest radiograph translates to a negligible risk to the
individual. Of course, all that assumes you have a good understanding of
the risk to the individual. People navigating a pandemic are worried
about the chance they will get sick, and a population estimate is often
not helpful in informing that.44See Mercuri and Gafni {[}4{]} for a
discussion on the potential danger of extrapolating information from
populations when assessing what will happen for the individual.

Estimating the risk associated with this particular virus is difficult.
As I write this editorial, we have 153,503 confirmed cases, with 5789
deaths.55https://www.arcgis.com/apps/opsdashboard/index.html\#/bda7594740fd40299423467b48e9ecf6,
accessed on March 14, 2020. That works out to a case fatality rate of
3.8\% or 1 in 26.5 cases. That is a very high fatality rate from the
perspective of an epidemiologist. However, we do not know the true
denominator, as there is a higher probability of being tested if your
symptoms are severe. Thus, it is likely the case fatality rate is lower,
but how low is anyone's guess (it depends on the validity of the
assumptions in your model). The infection rate is also difficult to
understand. China has a population of 1.4 billion people and has
recorded approximately 80 thousand confirmed cases. That would put the
risk of infection at 1 in 17,500. We know that is certainly incorrect,
given that 1) again, we do not know how many people were actually
infected -- many have mild symptoms and/or do not gets tested, and 2)
the excellent response in China to reducing the spread of infection
through the implementation of testing, tracing, and quarantine and other
social distancing measures. We also need to consider contextual
differences, such as population density, demographics, health care
resources, cultural practices, etc. that complicate the extrapolation of
experience from setting to another.

Given the speed at which such infections can move through the
population, we may not have time to wait until we have definitive
answers on risk of infection and case fatality rates before we implement
measures to mitigate both transmission and potentially overwhelming
scarce healthcare resources. That means we may need to rely on the
judgment of experts, such as those with knowledge of infectious disease
and public health. On the other hand, we must be very careful in how we
formulate messages to the public so as to avoid inducing an
over-reaction or complacency. So what are we to tell people when they
ask about their risk and are seeking advice on if they should go to
work, be with friends, etc.? To tell them that there is nothing to worry
about is not only incorrect, but it damages trust in science, especially
if things turn out differently than what the experts are predicting
(which will likely be the case, as their models are not perfect, but
hopefully any error ends up in our favour). Nor is it correct to tell
them that the situation is dire, as it is not clear how many people in
their community will ultimately suffer. My personal belief is that we
must be realistic in regards to what we know and that it is always best
to be honest about that. What is wrong with simply saying that we do not
know what is going to happen, but we know that there are certain
activities that will mitigate risk, and it is best to err on the side of
caution? That might not be a satisfying answer, but it is better than
telling people to stock up on water and toilet paper, which seems to be
what people are telling each other.

\textbf{Acknowledgements}

I would like to thank Benjamin Djulbegovic for comments on an earlier
draft of this editorial.

\textbf{References}

\begin{enumerate}
\tightlist
\item
  Kraus N, Malmfors T, Slovic. Intuitive Toxicology: Expert and Lay
  Judgments of Chemical Risks. Risk Analysis, 1992;12(2):215-232.
\item
  Lichtenstein S, Newman JR. Empirical scaling of common verbal phrases
  associated with numerical probabilities. Psychonomic Science,
  1967;9(10);563-564.
\item
  Fischhoff B, Slavic P, Lichtenstein S, Read S, Combs B. How Safe Is
  Safe Enough: A Psychometric Study of Attitudes Toward Technological
  Risks and Benefits. Policy Sciences 1978;9:127-152.
\item
  Mercuri M, Gafni A. Reflecting on Evidence Based Medicine, Person
  Centered medicine and Small Area Variations: how contemporary
  frameworks for medicine address (or not) the needs of the individual
  patient. European Journal of Person Centered Healthcare
  2018;6(3):454-461.
\end{enumerate}

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