Prophetic Models : Why are Governments Telling Us to Stay Home?

In this blog, I explore the prophetic role of models in advising governments how to respond to the Covid-19 virus.

In a recent blog, I talked about the surprising upside of this crisis. In this blog, I explore the prophetic role of models in advising governments how to respond to the Covid-19 virus. While predictive modeling is already a vital part of decision making in both the private and public sector, this crisis revealed how impactful they can be. They are no longer just predictive but also prophetic models that can alter the future of a nation.

Don’t believe it? A few weeks ago, the British government was considering an alternative approach to lead the nation through this pandemic. The idea was to allow for the spread of the virus, instructing only the 70+ population and those with symptoms to isolate themselves. In this scenario, there would be no school closures, no working from home or even cancellation of mass gatherings.

The rationale was that by allowing the virus to spread, enough people would recover from it to develop herd immunity. That is, when enough people have either been vaccinated or contracted and recovered from the virus, they would protect those who had not, breaking the chain of transmission.

Yet, in March 16th, in a stunning reversal, Boris Johnson had a change of heart. He quickly joined other world leaders in calling for a suppression strategy instructing all citizens to practice social distancing. Why? In short, the government learned that as much as 24% of the population would need hospitalization which would quickly overwhelm the the nation’s healthcare system. It came from a revealing report by the Imperial College London. This report would later find its way across the ocean to inform American policy on the virus response as well.

Prophetic Models that Changed it All

Intrigued by this news and having built predictive models myself for the last 6 years, I decided to go to the source for further investigation. I was interested not only in the findings but also examining the researchers’ methodology and other insights overlooked by articles reporting on it. In the next few paragraphs, I summarize my investigation paying particular attention to the forecasting model that the report was based on.

The model analyzed the predicted outcomes of two strategies: suppression and mitigation. The first one is the more aggressive strategy adopted by places like China and many European countries in suppressing virus transmission through rigorous social distancing in order to reverse epidemic growth. The second, aims only to slow growth, mitigating its worse effects by quarantining only at risk populations and those presenting symptoms.

The model went on to analyze the impact of a combination of NPIs (non-pharmaceutical interventions) by the governments. Mitigation focused on applying case isolation, home quarantine and social distancing only for those who are 70+. This strategy would cut fatalities in half but still result in over 1 million deaths in the US and overwhelm ICU beds 8 times over at highest peak demand! Therefore this option was deemed unacceptable.

Estimating the Impact of Suppression

Image by Pete Linforth from Pixabay

While saving lives continues to be at forefront, the focus turned to a scenario in which the country’s health care system could withstand the increase in cases during the virus peak infection phase. The model simulations found that a combination of 1) general population social distancing; 2) schools and university closures; 3) home quarantine; and 4) case isolation of those infected was the best alternative to achieve this goal. These measures would have to be in place for a sustained period of time.

How long? The scientists ran a few scenarios but the most feasible one was where social distancing and school and university closures were triggered by threshold. That is, when the number of ICU cases must be at 60, 100 or 200 per week before the policies go into effect. This scenario assumes this triggering would be in place for a period of two years or until a vaccine is developed. The numbers below for the suppression scenario assume a trigger of 400 ICU cases per week.

Strategy Estimated Deaths GBEstimated Deaths US
Do Nothing510K2.2M
Mitigation255K1.1M
Suppression39K168K
Estimated fatalities based on the Report Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand.

As shown in the table above, the model predicts significant decreases in fatalities. In doing so, it makes a clear case as to why these governments should apply these drastic measures.

Certainly, the model’s scope is limited. It does not look into the economic impact these shut downs or the indirect fatalities of those that cannot use an overwhelmed health care system. It also does not take into account every mitigating factor that could accelerate or hinder the virus spread. With that said, it is robust enough to make a compelling case for action. That is all we can expect from a good prophetic model.

Models as Modern Prophets

The Hebrew scriptures tells us of prophets who warned their communities of impending doom. One good example of that is the short book of Jonah. In the story, God summons Jonah to speak to the city Nineveh. After a few detours, one which involved spending some time in a fish’s belly, the prophet arrives at the city. There he delivers a simple message: “Change your ways or face destruction.”

Just like a modern forecasting model, the prophet was showing the people of Nineveh a picture of the future if they remained in their ways. He was giving them the “do nothing” or “keep status quo” scenario. He also offered an alternative scenario, where they changed their minds and opted for righteous living. In this scenario, the city would save lives and retain their prosperity.

To the prophet’s own chagrin, the city actually listened. They changed their ways and therefore altered their future. They weighed the consequence of doing nothing versus changing and decided to opt for the latter. Hence, the story tells us that God spared the city who heeded the prophets’ forecast of impending doom.

The model described above played a similar role of warning about the cost of doing nothing. Yet, instead of fiery sermons, it used the mighty power of number. As modern prophets, the scientists from the Imperial College warned leaders in Britain and the US of a collapsed healthcare system and mounting casualties. Prophetic models vividly described the cost of doing nothing and also paint a picture of their altered future. In the model’s assessment, action was imperative and thankfully, these political leaders, like those of Nineveh, listened.

What if the Model is wrong?

Just like in the case of Nineveh, the risk of listening is that the initial prediction could be wrong all along. In fact, the good prophet does their job best when they challenge decision makers to prove their numbers wrong. The point is not to forecast outcomes accurately, even though that is an important part of a rigorous model. The main point is to paint a believable picture of an undesirable future enough to move people to action.

Successful prophetic models are not the one that predict accurately but the ones that lead the community towards a better future. Furthermore, the mounting casualties of the last weeks give proof that this pandemic is not just your average cold. I can’t even imagine how worse they would have been without the concerted global effort of social distancing. Yet, when this crisis is over, many will look at the diminished numbers and wonder if it was all worth it.

This is where I can point to this imperfect but rigorous model to say that the policies put in place will likely save 2 million lives in the US and 500 thousand in Britain!

If that is not a good outcome, I don’t know what is.