Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates, nonpharmaceutical interventions adherence, and new variants scenarios

The COVID-19 Scenario Modeling Hub convened several modeling teams to provide long-term, 6-month projections in the US. The Hub has produced so far 14 rounds of projections based on scenarios aimed at enveloping the future drivers of the COVID-19 trajectory in the US (Vaccine delivery/administration, SARS-CoV-2 variants prevalence, relaxation of non-pharmaceuticals interventions (NPIs), etc.). The Hub aims at providing results based on ensembling the results of the different modeling teams.

Here we report the specific results of our specific modeling approach. The projections in this study are intended to bound plausible outbreak trajectories and should not be considered as forecasts of the most likely outcome. Considerable uncertainty is inherent when modeling the trajectory of COVID-19 over long timeframes because of deviations that may or may not be captured by the different scenarios (e.g., vaccine hesitancy, change in the pace of NPIs relaxation, etc.). The results for Round 4 appear in the MMWR report according to scenarios and data defined in late March 2021.

Update 7/29/21: Scenarios 4 through 6 do not include explicitly the modeling of the Delta variant, according to the scenario hub definitions, and we have discontinued their update.

Update 11/24/21: Scenarios 7 through 9 do not include explicitly the modeling of the Omicron variant, according to the scenario hub definitions, and we have discontinued their update.

Update 6/13/22: Scenarios 13 and 13.1 do not explicitly include the modeling of the Omicron sub-variants: BA.2, BA.2.12.1, BA.4, and BA.5.

Update 6/30/22: Scenario 14 does not explicitly include the modeling of the Omicron sub-variants: BA.4 and BA.5

Scenario Definitions
Extended Scenario Definitions*
Round 14.1
(includes modeling of Omicron sub- variants BA.4/BA.5)
Round 13.1
(Different waning time distribution)
Round 11.1
(Updated calibration timeline)
Round 9.1
(Updated calibration timeline)
Round 7.1
(Updated calibration timeline)
Round 6.1
(Complete Fall school reopening with updated school calendars)

*Note: extended scenarios provide updates and extensions to existing scenario hub scenarios (e.g. extended calibration timelines, updated NPIs calibrations, etc..). Differences are listed within the scenario definition of each extension.

Scenarios defined as of May 25, 2021  |  Model projecting from Epiweek 2021-21 to Epiweek 2021-47
scenario
definitions
round 6.1

United states Scenario PROJECTIONS

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

SCENARIO projections by state

Select a state:

ALABAMA

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Alaska

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

wisconsin

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

wyoming

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

ARIZONA

scenario a
High vaccination
Moderate NPI

Scenario B
High vaccination
Low NPI

Scenario C
Low vaccination
Moderate NPI

Scenario D
Low vaccination
Low NPI

arkansas

scenario a
High vaccination
Moderate NPI

Scenario B
High vaccination
Low NPI

Scenario C
Low vaccination
Moderate NPI

Scenario D
Low vaccination
Low NPI

california

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

colorado

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

connecticut

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

delaware

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

district of columbia

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

florida

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

georgia

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

hawaii

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

idaho

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

illinois

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

indiana

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

iowa

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

kansas

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

kentucky

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

louisiana

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

maine

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

maryland

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

massachusetts

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Figures show the median, the IQR and the 90%RR

michigan

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

minnesota

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

mississippi

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

missouri

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

montana

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

nebraska

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

nevada

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

new hampshire

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

New Jersey

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

New mexico

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

New york

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

North carolina

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

north dakota

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

ohio

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

oklahoma

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Oregon

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Pennsylvania

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

rhode island

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

South Carolina

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

south Dakota

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Tennessee

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

texas

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Utah

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Vermont

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

Virginia

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

washington

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

west virginia

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

ARIZONA

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

ARKANSAS

scenario a
Low vaccine hesitancy
Variant with low transmissibility increase

Scenario B
Low vaccine hesitancy
Variant with high transmissibility increase

Scenario C
High vaccine hesitancy
Variant with low transmissibility increase

Scenario D
High vaccine hesitancy
Variant with high transmissibility increase

About

To study the spatiotemporal COVID-19 spread, we use the Global Epidemic and Mobility Model (GLEAM), an individual-based, stochastic, and spatial epidemic model [1, 2, 3, 4, 5, 6]. GLEAM uses real-world data to perform in-silico simulations of the spatial spread of infectious diseases at the global level.  We use the model to analyze the spatiotemporal spread and magnitude of the COVID-19 epidemic in the USA at the county level. The data are aggregated to provide the estimates at the State level. The model generates an ensemble of possible epidemic projections described by the number of newly generated infections, hospitalizations, and deaths. The model is calibrated on weekly deaths data from the Johns Hopkins Centers for Civic Impact by using an information theoretical approach.

For each state and scenario, we report the weekly median number of projected cases, hospitalizations, and deaths with the interquartile range and 90% CI.

Disclaimer: There are large uncertainties around the transmission of COVID-19, the effectiveness of different policies and the extent to which the population is compliant to social distancing measures. The presented material is based on modeling scenario assumptions informed by current knowledge of the disease and subject to change as more data become available.

Acknowledgements: We acknowledge support from grant HHS/CDC 6U01IP001137 & HHS/CDC 5U01IP0001137. The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the funding agencies, the National Institutes of Health, or the U.S. Department of Health and Human Services.

Team

Northeastern University/MOBS Lab
• Matteo Chinazzi
• Jessica T. Davis
• Kunpeng Mu
• Ana Pastore y Piontti
• Xinyue Xiong
• Alessandro Vespignani

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