COVID-19 has overshadowed all events throughout the world over the past two years, with the first reported case in Wuhan, China in December 2019, COVID-19 was declared a pandemic by the WHO in March 2020. From early on in the outbreak, several mathematical models have been proposed to study the transmission dynamics of COVID-19 and evaluate control strategies to reduce the disease burden.

The aim of such models has been two-fold:
(1) to understand the severity of the outbreak and the effects of various control measures and,
(2) to make projections regarding disease burden.

In this talk we will discuss some of the modeling techniques used in epidemiology, we will then look at COIVD-19 models and argue that while many of the models were successful in the first aim outlined above, many of the models were off the mark in their projections. We discuss possible reasons for this and suggest some ways forward.