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.
Clinical concepts might be included in health-related mathematic models