Use of statics, mathematical models and simulation for different
types of analysis dates back to 1950s. Today, technology advancements in the
area of data analytics & artificial intelligence has broadened the applications
by multi fold.
The beauty of statistics is that it allows you to create any
type of narrative, positive or negative. It's easy to tweak the numbers. Just
by changing one assumption you can turn around the results and hence the story.
Since the outbreak of COVID19 I have been going through
so many predictions on the spreading, impact, recovery from COVID19 using
mathematical modelling, statistical analysis combined with artificial intelligence
algorithms!
COVID19 is not just challenging doctors & healthcare
professionals but also data scientists. If one carefully studies the
predictions made since beginning of March and compare them with the real
numbers today most of them are far apart.
Why predictions are going wrong? We have a saying in
modelling: ‘Garbage in garbage out’!
The input data that is used for prediction has to be precise.
Also, it is essential to consider all the parameters that impact and study the
variation of each parameter in the complete range.
In simple terms even if you don’t consider one cause in your
study or you haven’t captured one cause with sufficient accuracy the
predictions can completely go wrong.
In the case of COVID19, most of the studies I have read have
excluded ‘asymptomatic carriers’ or have taken an assumed value. Another thing
which is very difficult to model is human behaviour.
We don't have data of asymptotic carriers; it won't be
available unless extensive tests are done for a huge population. Also, it's
difficult to predict primary & secondary contacts because human behaviour
is different from person to person. It depends on several aspects. The
mathematical models representing human behaviour will have lot of assumptions
& approximation. Hence predictions will not be accurate.
These methodologies work very well in a controlled set-up
where one can gather accurate & precise information, feed it to the
scientific tools and then analyse and predict the response.
Linear & discrete mathematical equations can't predict
the non-linear and continuous ‘nature’! Even the non-linear methods and
continuous time models are limited by the availability of accurate real-world
data.
Only nature can say when is the end to this pandemic!