A methodology to generate epidemic scenarios for emerging infectious diseases based on the use of key calendar events

Abstract

This work presents a methodology to recreate the observed dynamics of emerging infectious diseases and to generate short-term forecasts for their evolution based on superspreading events occurring on key calendar dates. The method is illustrated by the COVID-19 pandemic dynamics in Mexico and Peru up to January 31, 2022. We also produce scenarios obtained through the estimation of a time-dependent contact rate, with the main assumption that the dynamic of the disease is determined by the mobility and social activity of the population during holidays and other important calendar dates. First, historical changes in the effective contact rate on predetermined dates are estimated. Then, this information is used to forecast scenarios under the assumption that the trends of the effective contact rate observed in the past will be similar on the same but future key calendar dates. All other conditions are assumed to remain constant in the time scale of the projections. One of the main features of the methodology is that it avoids the necessity of fixing values of the dynamic parameters for the whole prediction period. Results show that considering the key dates as reference information is useful to recreate the different outbreaks, slow or fast-growing, that an epidemic can present and, in most cases, make good short-term predictions.