UPDATED May 28, 2021, at 10:08 AM

Where The Latest COVID-19 Models Think We're Headed — And Why They Disagree

As of May 28, 2021, we are no longer updating this project with new COVID-19 forecasts.

Models predicting the potential spread of the COVID-19 pandemic have become a fixture of American life. Yet each model tells a different story about the loss of life to come, making it hard to know which one is “right.” But COVID-19 models aren’t made to be unquestioned oracles. They’re not trying to tell us one precise future, but rather the range of possibilities given the facts on the ground.

One of their more sober tasks is predicting the number of Americans who will die due to COVID-19. FiveThirtyEight — with the help of data compiled by the COVID-19 Forecast Hub — has assembled 10 models published by scientists to illustrate possible trajectories of the pandemic’s death toll. In doing so, we hope to make them more accessible, as well as highlight how the assumptions underlying the models can lead to vastly different estimates. Here are the models’ U.S. fatality projections for the coming weeks.

April 1, 2020July 1Oct. 1Jan. 1, 2021April 1July 1200k400k600kRecorded deathsRecorded deathsForecastsForecasts95% of modeled outcomesfall within shaded regions95% of modeled outcomesfall within shaded regionsEach dotted lineEach dotted lineis a different model:is a different model:

Forecasts like these are useful because they help us understand the most likely outcomes as well as best- and worst-case possibilities — and they can help policymakers make decisions that can lead us closer to those best-case outcomes.

And looking at multiple models is better than looking at just one because it's difficult to know which model will match reality the closest. Even when models disagree, understanding why they are different can give us valuable insight.

Coronavirus is hard to understand. FiveThirtyEight can help.

How do the models differ?

Each model makes different assumptions about properties of the novel coronavirus, such as how infectious it is and the rate at which people die once infected. They also use different types of math behind the scenes to make their projections. And perhaps most importantly, they make different assumptions about the amount of contact we should expect between people in the near future.

Understanding the underlying assumptions that each model is currently using can help us understand why some forecasts are more optimistic or pessimistic than others.

Johns Hopkins Univ.

 589K

587K594K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k95% of modeled outcomesfall within shaded regions95% of modeled outcomesfall within shaded regions

This model incorporates information about stay-at-home orders and assumes that the effectiveness of social distancing measures in a given state decreases by roughly 25 percent after those orders are lifted.

Iowa State

 594K

586K605K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model does not make specific assumptions about the interventions in effect.

Columbia Univ.

 598K

595K603K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

Columbia releases several models with varying assumptions. The one we currently track assumes that contact between people will increase by 5 percent each week for the next two weeks. Before May 13, we tracked models that did not account for states reopening.

Univ. of Mass.

 599K

597K601K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model assumes that factors affecting transmission will remain similar over the forecast horizon.

Northeastern Univ.

 600K

594K607K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model assumes each state’s current social distancing policies will continue indefinitely.

Univ. of Arizona

 600K

596K615K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model assumes that current interventions will remain in effect for at least four weeks after the forecasts were made.

Los Alamos

 600K

596K603K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model assumes that there will continue to be interventions, such as stay-at-home orders, but it does not specifically assume what those interventions will be. Instead, it considers various possible interventions to arrive at its forecast, which typically results in wider prediction intervals than a model with stricter assumptions.

Georgia Tech

 601K

600K602K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model assumes that the effects of interventions are reflected in the observed data and will continue.

MIT

 601K

599K604K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model accounts for state reopenings, and assumes that interventions would be reenacted if cases continue to increase. The model was changed significantly on July 4.

UCLA

 608K

604K612K  by June 19

4/1/207/110/11/1/214/17/1200k400k600k

This model incorporates state reopenings and assumes contact rates will increase after states are reopened.

    State-by-state breakdown

    Below are individual forecasts for all 50 states and the District of Columbia.

    Alabama

    11,140 deaths as of May 27

    4/1/207/110/11/1/214/17/110k20k

    Alaska

    369 deaths

    4/1/207/110/11/1/214/17/11k2k

    Arizona

    17,594 deaths

    4/1/207/110/11/1/214/17/110k20k

    Arkansas

    5,829 deaths

    4/1/207/110/11/1/214/17/15k10k

    California

    63,168 deaths

    4/1/207/110/11/1/214/17/150k100k

    Colorado

    6,545 deaths

    4/1/207/110/11/1/214/17/15k10k

    Connecticut

    8,230 deaths

    4/1/207/110/11/1/214/17/15k10k

    Delaware

    1,660 deaths

    4/1/207/110/11/1/214/17/11k2k

    District of Columbia

    1,132 deaths

    4/1/207/110/11/1/214/17/11k2k

    Florida

    36,733 deaths

    4/1/207/110/11/1/214/17/120k40k

    Georgia

    20,774 deaths

    4/1/207/110/11/1/214/17/120k40k

    Hawaii

    498 deaths

    4/1/207/110/11/1/214/17/15001k

    Idaho

    2,090 deaths

    4/1/207/110/11/1/214/17/12k4k

    Illinois

    25,101 deaths

    4/1/207/110/11/1/214/17/120k40k

    Indiana

    13,583 deaths

    4/1/207/110/11/1/214/17/110k20k

    Iowa

    6,047 deaths

    4/1/207/110/11/1/214/17/15k10k

    Kansas

    5,068 deaths

    4/1/207/110/11/1/214/17/15k10k

    Kentucky

    6,748 deaths

    4/1/207/110/11/1/214/17/15k10k

    Louisiana

    10,570 deaths

    4/1/207/110/11/1/214/17/110k20k

    Maine

    825 deaths

    4/1/207/110/11/1/214/17/11k2k

    Maryland

    9,581 deaths

    4/1/207/110/11/1/214/17/15k10k

    Massachusetts

    17,850 deaths

    4/1/207/110/11/1/214/17/110k20k

    Michigan

    20,301 deaths

    4/1/207/110/11/1/214/17/120k40k

    Minnesota

    7,496 deaths

    4/1/207/110/11/1/214/17/15k10k

    Mississippi

    7,304 deaths

    4/1/207/110/11/1/214/17/15k10k

    Missouri

    9,490 deaths

    4/1/207/110/11/1/214/17/110k20k

    Montana

    1,610 deaths

    4/1/207/110/11/1/214/17/12k4k

    Nebraska

    2,236 deaths

    4/1/207/110/11/1/214/17/12k4k

    Nevada

    5,578 deaths

    4/1/207/110/11/1/214/17/15k10k

    New Hampshire

    1,349 deaths

    4/1/207/110/11/1/214/17/11k2k

    New Jersey

    26,173 deaths

    4/1/207/110/11/1/214/17/120k40k

    New Mexico

    4,259 deaths

    4/1/207/110/11/1/214/17/15k10k

    New York

    53,229 deaths

    4/1/207/110/11/1/214/17/150k100k

    North Carolina

    13,055 deaths

    4/1/207/110/11/1/214/17/110k20k

    North Dakota

    1,541 deaths

    4/1/207/110/11/1/214/17/11k2k

    Ohio

    19,753 deaths

    4/1/207/110/11/1/214/17/120k40k

    Oklahoma

    7,291 deaths

    4/1/207/110/11/1/214/17/15k10k

    Oregon

    2,660 deaths

    4/1/207/110/11/1/214/17/12k4k

    Pennsylvania

    27,130 deaths

    4/1/207/110/11/1/214/17/120k40k

    Rhode Island

    2,708 deaths

    4/1/207/110/11/1/214/17/12k4k

    South Carolina

    9,711 deaths

    4/1/207/110/11/1/214/17/110k20k

    South Dakota

    2,004 deaths

    4/1/207/110/11/1/214/17/12k4k

    Tennessee

    12,428 deaths

    4/1/207/110/11/1/214/17/110k20k

    Texas

    51,401 deaths

    4/1/207/110/11/1/214/17/150k100k

    Utah

    2,294 deaths

    4/1/207/110/11/1/214/17/12k4k

    Vermont

    255 deaths

    4/1/207/110/11/1/214/17/1200400

    Virginia

    11,152 deaths

    4/1/207/110/11/1/214/17/110k20k

    Washington

    5,754 deaths

    4/1/207/110/11/1/214/17/15k10k

    West Virginia

    2,792 deaths

    4/1/207/110/11/1/214/17/12k4k

    Wisconsin

    7,814 deaths

    4/1/207/110/11/1/214/17/15k10k

    Wyoming

    719 deaths

    4/1/207/110/11/1/214/17/15001k

    Comments