Here we present a model for the transmission of SARS-CoV-2 in all states of the United States of America. The model builds on a previous model developed for the state of Georgia.

Our model takes into account the effect of human mobility on transmission (i.e., social distancing), as well as hard to quantify human behaviors and environmental factors, and is calibrated to the history of incident case and death reports.

For each state, we use our model to forecast reported cases, deaths, and total number of infections (including unreported infections) six weeks into the future, under three scenarios:

1. Increasing social distancing. Increasing social distancing reduces human movements from the current level to 30% of normal, which is the reduction observed in New York City that enabled transmission to decline there.
2. Maintaining social distancing. Maintaining social distancing holds human mobility at the level last observed in mobility data.
3. Return to normal. Ending social distancing increases human mobility from the current level to 100% of normal.

Changing human mobility (as results from practicing social distancing) has the effect of changing transmission rates. Transmission tends to decrease as mobility decreases. Many other factors (environmental and behavioral) also affect transmission rate, but as it is difficult to collect data on these factors, we do not attempt to model them directly. Instead, we capture the trend in transmission rate with human mobility subtracted (i.e. the “latent trend”), and use the latent trend in combination with mobility-based scenarios to forecast outcomes. We also make assumptions about testing and case reporting improving over time and build those into our model.

Top states by peak cases per 100k per day

The plot below shows the median forecasted daily case count per 100,000 people under each of three scenarios for several states. The states shown are those with the highest forecasted peak number of daily cases per 100,000 people under the status quo scenario (i.e. “Maintaining social distancing,” green lines).

States ommited due to poor model fits to data: Arizona, California, Connecticut, District of Columbia, Florida, Illinois, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, New York, Ohio, Tennessee, Texas, Washington, Puerto Rico, Guam, American Samoa, Mariana Islands, Virgin Islands.

In all cases, a return to normal mobility would worsen the epidemic (red lines), whereas increasing social distancing (blue lines) would reduce the number of cases.The dotted grey line indicates a threshold for designation as a “hot zone” for new cases, defined here as 15 cases per 100,000 people per day. Model updated July 13, 2021.