Scenario Modeling Hub

A Note on Scenario Modeling Hub Round 15 (August 16, 2022)

In a new round of projections, the Scenario Modeling Hub evaluated the trajectory of COVID-19 during Aug 2022-May 2023, under different assumptions about the timing of the fall 2022 booster campaign and the emergence of a hypothetical new variant in fall 2022.

Our main findings include:

  • In the absence of a new variant, and with a late vaccination campaign, hospitalizations are projected to remain stable and gradually decline until the end of the year.
  • Early distribution of reformulated boosters starting in mid-September is expected to decrease hospitalizations in early fall. Over the entire projection period, absent a new variant, early boosters are projected to prevent 2.4M (95% CI 0.8-4.8) cases, 137,000 (95% CI 21,000-251,000) hospitalizations and 9,700 (95% CI 500-19,000) deaths.
  • Not all models project a rebound with the arrival of a hypothetical new variant in the fall, so that there is large uncertainty in ensemble projections. If it occurs, a rebound would most likely peak near the end of the year.
  • In the most pessimistic scenario evaluated in this round, with a new variant and late boosters, we project 1.3M cumulative hospitalizations (95% PI 0.4-2.7M) and 181,000 cumulative deaths (95% PI 23,000-346,000) to occur over the 9 month projection period. In the most optimistic scenario, in the absence of a new variant and with early boosters, we project 0.7M hospitalizations (95% PI 0.2-1.70M) and 111,000 cumulative deaths (95% PI 11,000-212,000).
  • Overall, we estimate that early boosters would avert 6-12% of cases, 10-16% of hospitalizations and 12-15% of deaths, depending on the variant scenario.
  • A few caveats are worth noting:
    • The vaccine coverage assumed in these projections is indexed on the adult influenza vaccine coverage and is deemed optimistic. This assumes both a fast ramp up of vaccination in the month after boosters become available, and a high saturation coverage, above the levels observed for the first COVID-19 booster uptake in late 2021.
    • We assumed that boosters would be reformulated in the fall, with a VE of 80% against symptomatic disease immediately after vaccination. The efficacy of reformulated boosters against existing and new variants remains unclear, and so does the pace of waning after multiple booster shots and repeat infections.
    • We considered a single booster campaign in the fall-winter 2022-23.
    • The new variant introduced in these scenarios is purely hypothetical, and any new variant that does emerge will have different characteristics and timing of arrival.
    • Issues with case ascertainment and delays in death reporting make model calibration difficult for these outcomes. Hospitalizations continue to be a reliable outcome.
    • We cannot fully project changes in behavior and testing practices as we exit the emergency phase of the pandemic.

Table 1. COVID-19 Scenario Modeling Hub round 15 scenarios. More detailed scenario definitions and model characteristics can be found at


Even the best models of emerging infections struggle to give accurate forecasts at time scales greater than 3-4 weeks due to unpredictable drivers such as a changing policy environment, behavior change, the development of new control measures, and stochastic events. However, policy decisions around the course of emerging infections often require projections in the time frame of months. The goal of long-term projections is to compare outbreak trajectories under different scenarios, as opposed to offering a specific, unconditional estimate of what “will” happen.

As such, long-term projections can guide longer-term decision-making while short-term forecasts are more useful for situational awareness and guiding immediate response. The need for long-term epidemic projections is particularly acute in a severe pandemic, such as COVID-19, that has a large impact on the economy; for instance, economic and budget projections require estimates of outbreak trajectories in the 3-6 month time scale.