Omicron variants are widespread and infect many people, including those who have been vaccinated or previously infected. The surge in cases has been commonplace for the past two years, but it clearly shows that this wave is very different from the previous one. The record number of cases in the United States and around the world is primarily due to Omicron being more contagious than other variants and having a greater ability to evade immunity to infection. At the same time, early indications suggest that it is less common for people infected with Omicron to develop a serious illness and be hospitalized. This has important implications for assessing how devastating Omicron is in terms of death, hospitalization, work and school breaks. 

Epidemiologists often look at mathematical modeling and projection to estimate the future burden of variants like Omicron. The idea is to use a computerized representation of the spread of the virus  to simulate potential future consequences. It's important for the model builder to explore the unknown about Covid. For example, there is evidence  that Omicron is more portable than the Delta variant, but  how much? By incorporating uncertainty into the model, they don't just predict a single outcome. Instead, it creates a distribution of results, similar to the uncertainty cones used to predict hurricane landings. 

Recent models assume that the United States is likely to record more Covid 19 cases in January than in the previous month of the pandemic, but a lower percentage of these cases require hospitalization. Whether the hospital is more or less exposed than in January 2021 depends on the number of cases and their severity. For example, if twice as many people are infected, but those people are hospitalized half as often, the demand for beds will be the same. This calculation also applies to the estimated number of deaths from the virus and the expected adverse effects on the workforce.