Caracterización de la tendencia del COVID-19 en Colombia con regresiones polinomiales

Objective. To develop a series of polynomial models to track the growth and trend of infection and death curve for COVID-19 in Colombia. Methods. The infected and daily deaths from COVID-19 between March 6 to April 10, 2021, were used. For its prediction analysis, we use polynomial functions in Excel. Results. Of the six polynomial functions evaluated, the polynomial with the highest level of determination is that of degree 6 according to the adjusted R.. Predictions were made taking into account the accumulated polynomial functions of confirmed infected and deceased. Conclusions. Easy-to-build Excel models such as polynomial functions are effective for monitoring public health events, facilitating timely decision-making.