PREPARE: PREdicting PAndemic's REcurring Waves Amidst Mutations, Vaccination, and Lockdowns

TL;DR

This paper introduces an adaptable framework for predicting recurring pandemic waves considering mutations, vaccinations, and lockdowns, aiding policymakers in forecasting infection trends amidst uncertainty.

Contribution

It presents a novel predictive model that accounts for dynamic factors like mutations and interventions, validated on COVID-19 data from Germany.

Findings

Accurately predicts medium-term pandemic waves.

Incorporates mutation, vaccination, and lockdown effects.

Validated on real-world COVID-19 data.

Abstract

This study releases an adaptable framework that can provide insights to policymakers to predict the complex recurring waves of the pandemic in the medium postemergence of the virus spread, a phase marked by rapidly changing factors like virus mutations, lockdowns, and vaccinations, offering a way to forecast infection trends and stay ahead of future outbreaks even amidst uncertainty. The proposed model is validated on data from COVID-19 spread in Germany.