Discerning between truth, fake news, speculation, and poor information becomes exhausting as the content overload around COVID-19 shows no signs of abating. Margaret Blackie provides guidelines to help readers assess the information they see and to establish whether it is reliable and trustworthy.
As the COVID-19 pandemic progresses, it become more and more evident that we need to understand the difference between established, reliable information and speculation. We know that we live in an era where many get their news via social media and many are not particularly discerning in terms of what they choose to pass on. As a result, ‘fake news’ can take hold quickly and conspiracy theories abound.
So how do we discern that which is reliable from that which is speculation?
The delivery system
Firstly, look at the delivery system – There are two points here. The credibility of the delivery system and whether the same information is being reported by multiple sites. Is this being reported by an established news agency, scientific body governmental agency or a person who has built a track record of credibility? If so, it may be credible. If the delivery system is not credible do not pass it on, at best it is likely to be speculation, at worst it is a deliberate attempt to mislead.
Secondly, even if the delivery system is reliable, what are they saying about the source of their information? The controversy over the use of hydroxychloroquine as a treatment is one excellent example. President Trump has widely and repeatedly stated that hydroxychloroquine is good cure for COVID-19. There are indeed a few scientific studies which suggest that it might be.
Unfortunately, there are also a few scientific studies which suggest that it causes more problems. So, what is the ‘truth’? Right now, we don’t know! We don’t have enough data. We need more people with COVID-19 to be treated with hydroxychloroquine to see if it works – there is a technical name for that process – it is called a clinical trial. Clinical trials require stringent treatment protocols and control groups of patients who are not given the drug. Mostly gathering this data takes time, and in the midst of a pandemic the slow pace of the process is frustrating.
The quantity of data
Another example is the speculation over whether the BCG vaccine — traditionally used to prevent tuberculosis — somehow imparts some benefit. The reason for this idea is, in part, the relatively slow growth of infection rate in South Africa (there are other countries where this has been observed as well).
But there are many factors in play. Not least of which is that the poorer countries, where the BCG vaccine is still in widespread use, shut down much more quickly than the Europe and North America simply because it reached us later. Another factor is that poorer countries tend to have a younger population. The point is, again, we don’t have enough data yet.
The source of the data
The BCG vaccine speculation was published in various reliable newspapers. So here, the delivery system was supposedly reliable. However, as a discerning reader it is important that you ask yourself where they are getting the information from. If it is a genuine scientific study, they should name the person and institution at which they work and give a link to the full study.
However, if we go back to the hydroxychloroquine example you will note that there are several studies that have been published that offer conflicting information. In this case you can safely presume that we are still in the mire of the speculation zone.
Looking for patterns
For a simple example of how science develops from speculation into reliable information.
It begins with an idea that y might have some relationship x.
Graph A – a scientist does an experiment relating one factor to another. In graph A it looks like y has a high value when x is low. Thus far this means very little.
Graph B – the scientist repeats the experiment keeping as many conditions constant as they can. Now there are two conflicting results. Again no conclusion may be drawn.
Graph C – the scientist keeps repeating the experiment and still there is no clear pattern.
D, E and F represent different scenarios where enough data has been gathered. Graph D – now it is clear that as x increases so does y. There is a direct relationship between the two factors. The two original results are outliers.
Graph E – now it is clear that that there is an inverse relationship between the two. As y increases x decreases; and as x increases y decreases.
Graph F – there is no correlation between the value x and the value y. They are unrelated.
Establishing sufficient evidence of correlation
Notice though that even at this point all we have is data to support a correlation between x and y in scenarios D and E. We still do not know if the value of x causes a particular value of y.
The process of doing all of these experiments is all science, but it is only when we get to D, E and F that we have enough information to make any kind of claim.
In both the BCG case and in the hydroxychloroquine case do we have enough information yet to claim correlation?
Is there any good news?
In South Africa, we are in the very fortunate position of having a President who is listening to his health minister. In turn, the health minister has assembled an excellent team of advisors lead by Prof Salim Abdool Karim. I think we can trust that they are making the best choices given the data in their possession. And, yes, if a credible theory has made it to your Facebook feed they do know about it! If information is published on sacoronavirus.co.za you can trust it.
What we do know for certain is the social distancing is a reliable way of slowing the spread. Hand washing also lowers your personal risk. Wearing a mask protects those around you and supports the gains of social distancing.
There is an English saying ‘One swallow does not a summer make’. In these uncertain and desperate times people will be looking for ‘swallows’. Just make sure there are enough independent claims before you spread the ‘good news’.