UPDATED IHME COVID-19 PROJECTIONS: PREDICTING THE NEXT PHASE OF THE EPIDEMIC: https://covid19.healthdata.org/united-states-of-america
Since our first release of COVID-19 projections on March 26, we have sought to update and advance our modeling strategies alongside the world’s rapidly evolving understanding of the pandemic. Processing new types and more routinely collected data, and then revising modeling approaches as the evidence base expands, is foundational to any scientific endeavor. Its importance becomes dramatically higher when a new disease is affecting millions throughout the world.
Our initial COVID-19 modeling strategy drew from the evidence on death reporting earlier in the global pandemic to inform predicted trajectories of deaths and hospital resource needs in the US, Puerto Rico, Canada, and European Economic Area (EEA) countries. Initially, our goal was to predict the peak of the epidemic, both in terms of when the number of deaths would peak, and also when health systems would experience the greatest surge in demand. These projections were informed by early response to the COVID-19 epidemic: the adoption of various social distancing policies to slow and ultimately contain the virus’s rapid spread. Some locations enacted such measures swiftly – Australia and New Zealand, among others – and appear to have been successful in curbing their epidemics. Other locations were slower to implement distancing mandates but instituted strict policies like curfews, while some primarily issued behavioral change recommendations to reduce infection risk. It is increasingly clear that COVID-19 epidemic trajectories – and corresponding responses – are highly variable throughout the world.
Globally, data on COVID-19 and key epidemic drivers have markedly improved since the end of March. In addition to an expanded data universe on reported COVID-19 deaths, cases, and hospital resources, we have much more information on COVID-19 hospitalizations and testing. Much more data on human mobility patterns have become available, a critical contributor to heightened exposure and potential transmission of the novel coronavirus. Our team has actively sought to incorporate both new and updated data into our models as soon as they become available, enabling regular updates of COVID-19 predictions for an increasing number of locations.
We, collectively, are now entering a new phase of the COVID-19 pandemic. More locations are easing previously implemented social distancing policies, and human mobility patterns are trending upward – even in places where distancing measures remain in place. Testing has scaled up in many parts of the world, but such progress has been uneven and is not keeping pace with the growing demand for lifting business and gathering restrictions. Carefully tracking what is happening today as locations move to “re-open” will provide vital information for potential COVID-19 trajectories in the coming weeks and months.
Today we launch a major update to our COVID-19 estimation framework: a multi-stage hybrid model. This modeling approach involves estimating COVID-19 deaths and infections, as well as viral transmission, in multiple stages. It leverages a hybrid modeling approach through its statistical component (deaths model), a new component quantifying the rates at which individuals move from being susceptible to exposed, then infected, and then recovered (known as SEIR), and the existing microsimulation component that estimates hospitalizations. We have built this modeling platform to allow for regular data updates and to be flexible enough to incorporate new types of covariates as they become available. Last, by relating transmission parameters to predictions of key drivers of COVID-19 epidemic trends – temperature, the percentage of populations living in dense areas, testing per capita, and human mobility – this new modeling approach will allow for a more comprehensive examination of how COVID-19’s toll could unfold in the coming months, taking into account these underlying drivers. This is particularly important as many locations ease or end prior distancing policies without having a clear sense of how these actions could potentially affect COVID-19 trajectories given current trends in testing and mobility, among others. With our new modeling framework, we aim to provide a venue through which different COVID-19 epidemic scenarios and responses can be explored by location.
We summarize this new modeling strategy below, as well as the data which have made these modeling innovations possible. The results can be explored online: https://covid19.healthdata.org/projections . We would like to highlight that the SEIR model has been incorporated for the US to date; more countries and locations will be added soon..
At IHME, our guiding principle is to produce the best possible predictions given what we know today – and to continually improve these estimates to support further gains against COVID-19 tomorrow. We will be updating our projections in the coming days and weeks to incorporate the world’s evolving evidence base on COVID-19.
[Read the rest of the webpage regarding original modeling and the updates to May 4, 2020.
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