If you are interested in learning more about mathematical models of COVID-19, you might find this JAMA perspective useful:
Predictive Mathematical Models of the COVID-19 Pandemic: Underlying Principles and Value of Projections
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However, the primary and most effective use of epidemiological models is to estimate the relative effect of various interventions in reducing disease burden rather than to produce precise quantitative predictions about extent or duration of disease burdens. For predictions, “models are not crystal balls,” as Ferguson noted in a recent overview of the role of modeling.
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Don't expect the model to exactly match the death count. It's a bit like trying to guess the outcome of a football game -- very rarely will the guesstimate be accurate. These mathematical models produce statistical ranges of possible outcomes, and the expected total deaths can fall anywhere within that range, or even outside, with a certain percentage likelihood. They aren't built to cater to your political beliefs.
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