What armchair COVID ‘experts’ are getting wrong

Now everyone’s a statistician, it’s way too easy to be taken in by misinformation.

What armchair COVID ‘experts’ are getting wrong

Now everyone's a statistician. Here's what armchair COVID experts are getting wrong

If we don’t analyse statistics for a living, it’s easy to be taken in by misinformation about COVID-19 statistics on social media, especially if we don’t have the right context.

For instance, we may cherry pick statistics supporting our viewpoint and ignore statistics showing we are wrong. We also still need to correctly interpret these statistics.

It’s easy for us to share this misinformation. Many of these statistics are also interrelated, so misunderstandings can quickly multiply.

Here’s how we can avoid five common errors, and impress friends and family by getting the statistics right.

1. It’s the infection rate that’s scary, not the death rate

Social media posts comparing COVID-19 to other causes of death, such as the flu, imply COVID-19 isn’t really that deadly.

But these posts miss COVID-19’s infectiousness. For that, we need to look at the infection fatality rate (IFR) – the number of COVID-19 deaths divided by all those infected (a number we can only estimate at this stage, see also point 3 below).

While the jury is still out, COVID-19 has a higher IFR than the flu. Posts implying a low IFR for COVID-19 most certainly underestimate it. They also miss two other points.

First, if we compare the typical flu IFR of 0.1 per cent with the most optimistic COVID-19 estimate of 0.25 per cent, then COVID-19 remains more than twice as deadly as the flu.

Second, and more importantly, we need to look at the basic reproduction number (Ro) for each virus. This is the number of extra people one infected person is estimated to infect.

Flu’s Ro is about 1.3. Although COVID-19 estimates vary, its Ro sits around a median of 2.8. Because of the way infections grow exponentially (see below), the jump from 1.3 to 2.8 means COVID-19 is vastly more infectious than flu.

When you combine all these statistics, you can see the motivation behind our public health measures to ‘limit the spread’. It’s not only that COVID-19 is so deadly, it’s deadly and highly infectious.

Read more: How deadly is the coronavirus? The true fatality rate is tricky to find, but researchers are getting closer

2. Exponential growth and misleading graphs

A simple graph might plot the number of new COVID cases over time. But as new cases might be reported erratically, statisticians are more interested in the rate of growth of total cases over time. The steeper the upwards slope on the graph, the more we should be worried.

Read more: Coronavirus is growing exponentially – here’s what that really means

For COVID-19, statisticians look to track exponential growth in cases. Put simply, unrestrained COVID cases can lead to a continuously growing number of more cases. This gives us a graph that tracks slowly at the start, but then sharply curves upwards with time. This is the curve we want to flatten, as shown below.

“Flattening the curve” is another way of saying “slowing the spread”. The epidemic is lengthened, but we reduce the number of severe cases, causing less burden on public health systems. The Conversation/CC BY ND

However, social media posts routinely compare COVID-19 figures with those of other causes of death that show:

Even when researchers talk of exponential growth, they can still mislead.

An Israeli professor’s widely shared analysis claimed COVID-19’s exponential growth “fades after eight weeks”. Well, he was clearly wrong. But why?


His model assumed COVID-19 cases grow exponentially over a number of days, instead of over a succession of transmissions, each of which may take several days. This led him to plot only the erratic growth of the outbreak’s early phase.

Better visualisations truncate those erratic first cases, for instance by starting from the 100th case. Or they use estimates of the number of days it takes for the number of cases to double (about six to seven days).

Read more: The bar necessities: 5 ways to understand coronavirus graphs

3. Not all infections are cases

Then there’s the confusion about COVID-19 infections versus cases. In epidemiological terms, a ‘case’ is a person who is diagnosed with COVID-19, mostly by a positive test result.

But there are many more infections than cases. Some infections don’t show symptoms, some symptoms are so minor people think it’s just a cold, testing is not always available to everyone who needs it, and testing does not pick up all infections.

Infections ‘cause’ cases, testing discovers cases. US President Donald Trump was close to the truth when he said the number of cases in the US was high because of the high rate of testing. But he and others still got it totally wrong.

More testing does not result in more cases, it allows for a more accurate estimate of the true number of cases.

The best strategy, epidemiologically, is not to test less, but to test as widely as possible, minimising the discrepancy between cases and overall infections.

4. We can’t compare deaths with cases from the same date

Estimates vary, but the time between infection and death could be as much as a month. And the variation in time to recovery is even greater. Some people get really ill and take a long time to recover, some show no symptoms.

So deaths recorded on a given date reflect deaths from cases recorded several weeks prior, when the case count may have been less than half the number of current cases.

The rapid case-doubling time and protracted recovery time also create a large discrepancy between counts of active and recovered cases. We’ll only know the true numbers in retrospect.


5. Yes, the data are messy, incomplete and may change

Some social media users get angry when the statistics are adjusted, fuelling conspiracy theories.

But few realise how mammoth, chaotic and complex the task is of tracking statistics on a disease like this.

Countries and even states may count cases and deaths differently. It also takes time to gather the data, meaning retrospective adjustments are made.

We’ll only know the true figures for this pandemic in retrospect. Equally so, early models were not necessarily wrong because the modellers were deceitful, but because they had insufficient data to work from.

Welcome to the world of data management, data cleaning and data modelling, which many armchair statisticians don’t always appreciate. Until now.

Read more: When a virus goes viral: pros and cons to the coronavirus spread on social media The Conversation

Jacques Raubenheimer, Senior Research Fellow, Biostatistics, University of Sydney

This article is republished from The Conversation under a Creative Commons licence. Read the original article.

With so much misinformation on social media, what sources do you trust? Do you believe the media is promoting the truth or spreading fear about the coronavirus?

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    To make a comment, please register or login
    15th Sep 2020
    The media thrives on deceitful headlines promoting sensationalism, because it attracts readers not just to its emotionally charged stories but to its advertisers.

    So, the real question should be, " When will the media stupidity curve flatten"?
    15th Sep 2020
    15th Sep 2020
    Until I read this article I was a little confused regarding Covid 19, now I am totally confused, the entire article seems to be based on guess work and maybes, the statistics comparisons are not comparing known data, but are comparing on assumptions that may prove to be inaccurate.
    15th Sep 2020
    what is the distinction between a little confused and totally confused?
    15th Sep 2020
    A lot
    15th Sep 2020
    But why aren't we told how many of those infected recover? The ignored statistic....
    15th Sep 2020
    The data you desire:
    NSW is very helpful in identifying clusters and tracing and Gladys and Dr Chant give a run down every morning.
    Victoria on the other hand has been in damage control since the quarantine breach and BLM protest so the truth is rather vague.
    15th Sep 2020
    the data is there if you care to look but you can also work it out easily enough ... cases subtract deaths equal recovered
    15th Sep 2020
    More Vic data (including the recovered total) at https://www.dhhs.vic.gov.au/victorian-coronavirus-covid-19-data
    15th Sep 2020
    Try this BillW41- https://www.worldometers.info/coronavirus/country/australia/
    Coronavirus Cases: Australia wide
    816...Majority in Victoria-Melbourne
    15th Sep 2020
    Of all the maths I learned at Uni, including Laplace transformations, calculus, reverse polar notation, quadratic equations etc etc, the one maths subject that bewildered me, and still does, is statistics. To quote Mark Twain (I think), there are three types of untruths- lies, dam lies and statistics.
    16th Sep 2020
    What was that quote about 'lies, damned lies and statistics'? Looks like the perfect example here. Is this meant to be justification for sitting around, doing nothing, and hoping for a vaccine? If State and Federal governments were even half way serious about preventing infection and deaths from Covid-19, they would be doing everything they can to raise resistance and immunity. Is it any wonder that the conspiracy theorists think that they are using this crisis to increase power and control, as well as kill off as many elderly people as possible? Funny how none of the 'leaders' (Peter Dutton excepted) have become infected or died. Seems the virus only attacks the elderly and the lower economic classes.
    16th Sep 2020
    BillF2 since you are clearly an infectious diseases expert, perhaps you would enlighten the rest of us with how, in the absence of a vaccine, Governments could "raise resistance and immunity".

    This is a new virus and a new disease which means there is NO resistance or immunity anywhere in the world. Even within communities where there were far more cases than in Australia (with its consequent higher death tolls) there is still no evidence that any immunity gained through infection (by testing for antibodies) is long lasting. Antibodies drop sharply after a relatively short period of time even to undetectable levels. However, what is not known is whether T cells retain viral memory and can reactivate to fight subsequent infection.

    There are already cases where someone who was diagnosed with COVID-19, hospitalised as a result but later recovered and testing negative for the virus then released from hospital. Only to be readmitted several weeks (and in one case months) later with the same infection. Does this mean resitance and immunity is short lived or even does not exist? Does it mean they never cleared the infection and away from medical care it underwent a resurgance? Or is it a effectively a new infection from a mutated virus?

    As for your assertion that the virus only affects the elderly and low socio-economic populations you really need to do more research. That point of view is one that is driving the spread of the virus among the 25-35 age group. What is already known is that even a mild dose of COVID-19 ( even asymptomatic) affects most body organs not just the lungs - heart, liver, kidneys, brain. What is not yet known is whether this damage is permanent or whether over time the organs will recover. Potentially there will be a huge demand on health care down the track as the damage becomes more apparent.

    This is not an infection you want to run riot. The fact that Australia has had relatively low numbers of cases is because of the public health interventions. The problem with public health interventions is that if they are successful, nothing happens. That is the position Australia is in.
    16th Sep 2020
    An excellent article, thank you.
    For those who are saying, "I'm more confused after reading it" please do read it again. Slowly. Think it through. Don't skim it looking for an easy answer.
    Regarding changes to the underlying assumptions that the statistical models are based on, yes the assumptions will keep changing as more information is gathered. Think about the old story of blind people, each touching part of an elephant. One held the tail and said, "An elephant is a skinny thing like a rope." Another held the trunk and said, "No, it's quite fat". Another grasped a foot and said, "You're both wrong. It's really really fat and heavy."
    Statisticians world wide are still gathering the facts on the elephant that is Covid-19, and as they pool their information the picture about the virus keeps changing. They don't yet have the big picture.
    Also, it could be years before the long term effects of even a mild infection become known. Will young people who are infected develop heart problems in later years? Lung problems?
    Compare it to rheumatic fever. People can get that from a simple strep throat if it isn't treated properly. And that can affect the heart, joints, and brain. So, at present, we just don't know what we don't know. All we can do is wait and watch as the picture becomes clearer.
    16th Sep 2020
    Seriously , statistics and how to read them. What rot, statistic are just numbers , what goes on around them is what counts . The fact that influenza does cause more deaths in the elderly is not a statistic count its a fact. Statistics is as full of bulldust like statistics on AFL footballer possessions, these days they get lots of possessions but they are sometimes all by them selves and kick back and forward to each other. The stat is misleading.
    Fact is how serious you want to take things is fine, the facts that you witness like in France and Italy and Spain where second wave is high in numbers very low in deaths, how do you read that mr statistic expert. Stats, only sometimes reflect fact, they are just numbers. When people die they are more than numbers. YLC you are apoligists and excuse makers!
    For who?
    16th Sep 2020
    John, I'm pretty sure the second waves in France, Italy and Spain are high because they let all their citizens mix freely with each other (and thus allowed the virus to spread amongst them) and it was mostly younger people who took advantage of the opportunity to mingle.
    So the high number of cases was because a lot of younger people caught the virus.
    The low number of deaths was because younger people are less likely to die from it.
    17th Sep 2020
    Thanks, KSS. You are right. I am not an infectious diseases expert, but if as we are continually told, we are in a war, I would expect those who claim to be leading the fight to use all the weapons at their disposal. Vaccines are not yet part of their arsenal, and in spite of the press reports, they might not be available for another year. In the meantime, how are we fighting the virus? Apart from social distancing, washing your hands and wearing a mask, nobody is being pro-active or offering advice on how to be physically less susceptible to the virus. Defence is not the best form of attack. After all, the goal of any war is to win, and the way to defeat the virus is to reduce or destroy its ability to infect. If the best we can do is sit around and wait for a vaccine, then, not only are we in a bad way, but we are not very serious about defeating the virus. Do you wonder why there are so many conspiracy theorists?
    17th Sep 2020
    Bill, our leaders can't "use all the weapons at their disposal" to kill the virus because we have no weapons in the arsenal that will kill the virus.
    The only 'weapon' that will do that will be a vaccine.

    Until then all we can do is keep dodging the 'bullets' that are sprayed by infected people in the form of droplets and aerosols.

    The good news is that after many months of frantic research the doctors have found some existing medicines that reduce the impact of the illness in some people.

    Also, a pattern has not yet emerged to show what it is that those who survive have in common with each other - aside from most survivors being below 60 years old.
    That means the doctors have no idea what it is that makes some people "physically less susceptible" and how we could improve that.

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