Scenario Modeling Hub

In a new round of projections, the Scenario Modeling Hub evaluated the trajectory of COVID-19 during April 28, 2024 to April 26, 2025 (52-week horizon), under 6 scenarios about the extent of immune escape of circulating variants (50% vs 20% annually) and the annual uptake of reformulated boosters (i) minimal uptake, ii) high-risk group uptake, where vaccination is recommended for individuals under 65 yrs with high-risk conditions and those over 65 yrs, with vaccination coverage mirroring reported levels in these groups in 2023-24, or iii) universal uptake corresponding to 2023-24 coverage levels in the entire US population). Nine teams contributed both national and state-specific projections.

GENERAL DYNAMICS

• COVID-19 Hospitalizations and deaths will begin to rise nationally in late summer 2024 and peak in mid-December 2024 throughand mid-January 2025. Peak hospitalizations will be similar to the 2023-24 season assuming the same vaccination recommendation (all eligible individuals) and high immune escape.

• Over the course of the projection period (April 28, 2024-April 26, 2025) we project 814,000 hospitalizations (95% PI 0.4-1.2 million) and 54,000 deaths (95% PI 17,000-98,000). This presumes high immune escape and vaccination recommended to all eligible individuals (conditions similar to the 2023-24 season). Our worst case (no vaccination, high immune escape) projects 931,000 hospitalizations and 62,000 deaths, while the best case (universal vaccination, low immune escape) projects 550,000 hospitalizations and 42,000 deaths.
• Without vaccination, 52% of hospitalizations and 87% of deaths are projected to be in those 65+. This is presuming high immune escape. It is expected most deaths and hospitalizations in younger age groups would be in high-risk individuals, however these numbers were not explicitly modeled.

VACCINE IMPACT

• Vaccination of high-risk individuals is projected to prevent over 76,000 hospitalizations and 7,000 deaths. Assuming high immune escape, hospitalizations are reduced by 76,000 [8%] (95% CI: 34,000-118,000) and deaths by 7,000 [10%] (95% CI: 3,000-11,000), compared to a no vaccine recommendation scenario. The majority of this impact comes from reductions in hospitalizations and deaths in those 65+ (71,000 and 7,000, respectively).

• A recommendation for vaccination on all individuals leads to further reductions in hospitalizations and deaths, including in those 65 and older. Assuming high immune escape, a universal vaccine recommendation reduces hospitalizations by an additional 28,000 [4%] (95% CI 13,000-43,000) and deaths by an additional 2,000 [3%] (95% CI 800-3,000), compared to a high-risk recommendation. This further reduction includes reductions in hospitalizations and deaths in those 65+ from indirect vaccine protection (11,000 and 1,000, respectively).

Table 1. COVID-19 Scenario Modeling Hub round 18 scenarios. More detailed scenario definitions and model characteristics can be found at https://github.com/midas-network/covid19-scenario-modeling-hub.

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.