Predictive methodology of the dynamics of the number of COVID-19 cases: application to China, Belgium, and South Korea

Resumen

Objectives: Multiple methodologies based on probability theory have been developed to establish predictions of dengue, malaria, HIV, obesity epidemics, among others. This research aimed to develop a new method for predicting the dynamics of the number of COVID-19 cases for China, Belgium, and South Korea based on the probability theory that allows the evaluation and comparison of their increment.

Material and methods: Probability ranges of the number of COVID-19 cases were established, which were assigned to each of the daily number of COVID-19 cases reported by China, Belgium, and South Korea that were evaluated during 74, 50, and 50 days respectively. The frequency and probability of each daily range for each country was calculated. Their total probability and the probability of the dynamics in intervals of 8 consecutive days were calculated, and the values between countries were compared to evaluate their differences.

Results: Probability values of 1.21E-30, 2.03E-22, and 3.15E-12 were established for China, Belgium, and South Korea, which allows the quantitative differentiation of the characteristics of their dynamics. The probability differences of the 8-day subspaces ranged from 0.003 to 1, allowing the temporal changes in the dynamics to be evaluated.

Conclusion: The ranges established for the evaluation of the number of COVID-19 cases allow to differentiate the behavior of epidemics between countries and to stratify the severity of expansion. Highlighting an underlying mathematical order for this phenomenon permitted quantitatively predict its spatiotemporal dynamic and indirectly, the efficacy of public health politics implemented for each country.