Statistics

[Consideration of Immunity Loss in the Epidemic Model of Respiratory Viruses]

Authors: Johnny J. Mafra Jr.
Comments: 16 Pages.

A previous work on Covid-19 forecast miserably failed to preview the epidemic evolution with the massive vaccination done during 2021. This paper aims to workaround its weak point, which was to not consider immunity loss in its model. The set of SIR equations was reviewed including immunity loss, Beta profile was recalculated and the model was tuned using real data of 2021. This way was achieved a good conformance between the simulation and data, roughly within the calculated uncertainty of 25%. The simulation for 2022 presented Omicron peak but switched in time. The probable explanation for that is an unbalance in Beta profile in the beginning of 2022, resulting in a bigger peak in January and in consequence a smaller one latter, due to more immune people. It was explored the hypothesis of different immunity losses for natural and vaccine immunities. This case showed a theoretical profile similar to the real data observed. As a limit case theoretical study, was verified that the epidemic evolution in several years more similar to real data was the case in that the vaccination didn’t avoid transmission or avoid as little as 20%. Simulation showed, as expected, that if Beta is below some limit the epidemic vanishes. Data showed that Covid-19 seems to be naturally vanishing by itself, meaning that no measures so far were effective. New approaches are speculated to provide a better performance on epidemic combat based on ventilation and air sterilization using GUV. Suggestions on how to test those approaches are presented.
Category: Statistics