Not all 10% increases are created equal. And by that we mean, assumption effects are often more impactful in one direction than in the other. Especially when it comes to truncation models or those which use a CTE measure (conditional tail expectation).
Principles-based reserves, for example, use a CTE70 measure. [Take the average of the (100% – 70% = 30%) of the scenarios.] If your model increases expense 3% across the board, sure, on average, your asset funding need might increase by exactly that amount. However, because your final measurement isn’t the average across all the scenarios, but only the worst ones, it’s likely that your reserve amounts are going to increase by significantly more than the average. You might need to run a few different tests, at various magnitudes of change, to determine how your various outputs change as a function of the volatility of your inputs.
It is a wonder that nobody choked on their morning toast and tea, for if Imperial modelling has stood for anything in this crisis, it is relentless pessimism. Plummeting figures were certainly not predicted by its researchers. The difference this time is that the Government has pressed ahead with reopening despite the doom-mongering, and so has proven the models wrong.
Here is what they said would happen and what we know now: Hospital admissions When the Government published its roadmap out of the pandemic on Feb 22, it was largely based on modelling assumptions from Imperial, the London School of Hygiene & Tropical Medicine and Warwick University.
Imperial modelled four unlocking scenarios, ranging from “very fast” to “gradual”. Under the fastest, full lifting would occur at the end of April, while under the slowest, Britain would not see restrictions eased until Aug 2.
In the end, the Government chose a path somewhere between “fast” and “medium”, yet the Imperial model predicted that would still lead to Covid hospital bed occupancy of about 15,000 to 25,000 in the summer and early autumn – which was higher than the first peak in April 2020.
“There’s only one model that we look at that has the number of projected deaths which is the IHME model which is funded by the Gates Foundation,” Cuomo said on April 2, adding, “and we thank the Gates Foundation for the national service that they’ve done.”
In an April 9 briefing, Michigan Governor Gretchen Whitmer referred to the IHME model in order to project deaths and the PPE resources needed for the supposed surge.
It was the same story with the government of Pennsylvania. The PA Health Department exclusively uses IHME models to forecast coronavirus outcomes.
Governor Phil Murphy, another nursing home death warrant participant, used IHME models to navigate the state’s policy response.
For a few months last year, Nigel Goldenfeld and Sergei Maslov, a pair of physicists at the University of Illinois, Urbana-Champaign, were unlikely celebrities in their state’s COVID-19 pandemic response — that is, until everything went wrong.
Following the model’s guidance, the University of Illinois formulated a plan. It would test all its students for the coronavirus twice a week, require the use of masks, and implement other logistical considerations and controls, including an effective contact-tracing system and an exposure-notification phone app. The math suggested that this combination of policies would be sufficient to allow in-person instruction to resume without touching off exponential spread of the virus.
But on September 3, just one week into its fall semester, the university faced a bleak reality. Nearly 800 of its students had tested positive for the coronavirus — more than the model had projected by Thanksgiving. Administrators had to issue an immediate campus-wide suspension of nonessential activities.