The Geometrical Bayes Theorem and Probabilistic Prediction of Next Global Pandemic

Abstract

The recent Corona virus 2019 and Monkeypox 2022 diseases, have manifested the fully unpredictable character of global pandemics as to time and geography where the outbreak begins. Despite of that, the statistics that have leave these pandemics can be taken as a pattern by which exists a probability of continuation of more global pandemics in future. This paper presents an approach based at a fully geometrical concept in conjunction to conditional probabilities. In concrete the Bayes theorem is considered. In this manner, number of infections versus time of a global pandemic can be seen as sides of a trapezoid. The sides of involved geometry can be condition for each other. From this, the peaks can be estimated and the total number of infection can be approximately predicted. Based at data of Corona virus 2019, the next peak of a possible next global pandemic has been predicted. Errors are basically attached on the time estimation of each wave in a finite sequence. Considering the highest peak of 4M infections seen in January 2022, the highest peak for next pandemic might to be ranking between 3M and 7M of infections.