The endgame falls into roughly 3 scenarios, the first 2 of which are shown in the following charts:

1. The CDC study estimate of 8x undercounting is more accurate, meaning we are clearly due for a dive in infections as herd immunity is rapidly realized,
2. The IHME assumption of a 3-4x understatement means half the country has been exposed to the virus and transmission is not only getting harder for the virus at the same time immunizations are underway, or
3. The actual cases reflect the reported numbers. In this case, the immunizations will pull us out of the pandemic ... not likely before the shots are given to well over half the population.

All scenarios assume that the 1,000,000 2nd vaccinations per day is already in progress.

1/22/2021 note: changes in infection growth may be due to arriving herd immunity (see "Endgame" tab) rather than to changes in human behavior.

These forecasts are based solely on reported JHU-CSSE data as of the date of the model, using the latest growth rates and derivatives -- starting with an 7-day averaging of new cases -- to project into the future. No epidemiological, political, or behavioral assumptions or models are incorporated, other than that the current observations as represented in the data are valid into the future with the exception that acceleration/decelerations in daily rates are capped at 2%. Thus, the forecasts do not attempt to account for possible changes in human behavior such as tightening or relaxing discipline, improved testing, or more accurate reporting. Those changes might be inferred in deviations of the actuals over time from the models.

For counties with low numbers of new cases (generally, below 5 per day), the projections are highly suspect as small changes in cases have an oversized impact on the growth rates. As well, counties with suddenly higher numbers of new cases will have accelerations over-estimated.

The method is as follows:

• Total confirmed cases data is collected from JHU-CSSE daily.
• New cases are computed as today's confirmed cases less yesterday's confirmed cases.
• For each country, U.S. state, and U.S. county, the backward-looking 7-day average for new cases is computed.
• The change in new cases (our first derivative) is computed as today's averaged new cases less yesterday's averaged new cases.
• The change in the first derivative (our second derivative) provides the acceleration (or deceleration) of the change in new cases, and is computed as today's change in average new cases less yesterday's change in averaged new cases.
• The model is built by taking the JHU-CSSE data on the date of the model. Then, for each day after the date of the model, multiply the total cases of the previous day by the first derivative and multiply that by the second derivative.
• The first derivative for subsequent days is the first derivative of the previous day multiplied by the second derivative. The second derivative is not changed.

For additional details see the Methodology tab.