  The construction of mathematical models that allow comprehensive approach of
decision-making in situations of absence of robust evidence is important. While
it is interesting to use models that are easy to understand, using values of
direct interpretation, we analized a published index (COVID-19 Burden Index)
and found it seems to be oversimplified. It is possible that the proposed
index, with current data, could be useful in geographically and
administratively narrowed places. But it is inaccurate to be applied throughout
the process and in places as broad as American countries. It would be ideal to
correct and refine the referred model, bearing in mind clinical concepts
described, to take advantage of the proposal and generate a more accurate
response, which can serve as an input both in the implementation of measures
and in the prediction of the behavior of a pandemic like the current one.
However, what we propose is to improve the accuracy of the model in terms of
quantities and applicability, agreeing with the concept of "stay at home". The
approach between complementary areas of knowledge should be the door that we
must open to generate the new evidence we need. Mathematics should not dispense
clinical sciences.
