COVID-19

Scenario Modeling Hub

A Note on Scenario Modeling Hub Round 14 (July 19, 2022)

In a new round of projections, the Scenario Modeling Hub evaluated the trajectory of COVID-19 in the coming year under different assumptions about the scale of the fall 2022 booster campaign and the emergence of a hypothetical new variant in fall 2022

Our main findings include:

  • Absent a new variant, COVID levels may continue to rise nationally and stay elevated through early fall. 50% projection intervals suggest that hospitalizations are unlikely to exceed 60% of the Omicron peak. However, this national pattern masks significant variation in projected trajectories between states
  • Not all models project a significant peak to result from the introduction of a new variant, however those that do project peaks in late fall or winter.
  • Regardless of the presence of a new variant, over the first fifty weeks of the projection period an extended booster campaign is projected to lead to a greater than 15% reduction in hospitalizations and 10% reduction in deaths relative to the restricted booster scenario. This represents reductions of 348,000 (95% PI: -64,000-759,000) hospitalizations and 43,000 (95% PI: -23,000-108,000) deaths in the no variant scenario at the national level.
  • Absent a new variant or change in vaccination policy, over the next fifty weeks 1.7 million (95% PI: 503,000-4.5 million) hospitalizations and 230,000 (95% PI: 29,000-873,000) deaths are projected, with very broad uncertainty.
  • We are still in a period of substantial uncertainty about the future and there are significant qualitative differences between individual models, particularly in the long-term. The ensembling methodology may blunt the magnitude of the projected peaks when individual models differ in peak timing.
  • As of the release of this report, hospitalization have tracked well with the ensemble projections while deaths have tended to be on the lower end of the projection interval.
  • These key takeaways are subject to several limitations/caveats:
    • Not all models include BA4/5, and those that do are fit to limited observed data on their circulation.
    • Radical changes in case ascertainment and reporting are making models increasingly hard to fit and clouding the comparison between model projections and observed outcomes.
    • The efficacy of reformulated vaccines is unknown.
    • The new variant introduced in these scenarios is purely hypothetical, and any new variant that does emerge may have very different characteristics.

Table 1. COVID-19 Scenario Modeling Hub round 14 scenarios. More detailed scenario definitions and model characteristics can be found at https://github.com/midas-network/covid19-scenario-modeling-hub.


Rationale

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.