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We proposed the SIkJalpha model at the beginning of the COVID-19 pandemic(early 2020). Since then, as the pandemic evolved, more complexities were addedto capture crucial factors and variables that can assist with projectingdesired future scenarios. Throughout the pandemic, multi-model collaborativeefforts have been organized to predict short-term outcomes (cases, deaths, andhospitalizations) of COVID-19 and long-term scenario projections. We have beenparticipating in five such efforts. This paper presents the evolution of theSIkJalpha model and its many versions that have been used to submit to thesecollaborative efforts since the beginning of the pandemic. Specifically, weshow that the SIkJalpha model is an approximation of a class of epidemiologicalmodels. We demonstrate how the model can be used to incorporate variouscomplexities, including under-reporting, multiple variants, waning of immunity,and contact rates, and to generate probabilistic outputs.

The Variations of SIkJalpha Model for COVID-19 Forecasting and Scenario Projections