My previous post outlines the ideas I have about a fantasy government of data and urgency as it relates to the COVID19 situation. Here, I want to contrast different approaches to governing.
Govern by models
This is the approach we took, at least in the USA. This is only my impression based on keeping up with the news. At the foundation of this approach is the reliance on a computer model for how the epidemic will progress.
Based on my prior experience with models, I imagine a statistical discrete-event type simulation although I’m guessing they actually used a discrete time (day-by-day) model.
Such a model would start off with a population, say 100 million people. Using statistical distributions, the populations would be assigned different attributes such as sex, age-cohort, home neighborhood (such as zip code), home type (such as apartment vs detached houses), household size and mix, occupation, work location (territorial if involves travel), etc.
Using data from the epidemic, we would assign different rates of transmission within location and activity categories and between those categories. We would also assign probabilities that vary by sex and age cohorts for whether the epidemic would deteriorate to needing medical attention from basic hospital observation to full intensive care with intrusive ventilation.
These joint probabilities may be composites of the epidemic’s broad properties combined with standard weights that vary by the category.
The simulation would start tracking a single infection and then add in additional infections as they are computed to occur. Eventually, the encounters will be from people who previously recovered so that they would not propagate the epidemic further.
A discrete event simulation of each individual would probably not be practical unless the population was scaled down dramatically, but it would be interesting to run with multiple iterations with different starting seeds to see the distribution of results. I would expect such a model to predict that there would be substantial portions of each sub population to escape without ever being infected just due the virus running out of opportunities to reach them: the infected never had the opportunity to come in close proximity to the remaining uninfected.
The actual simulation probably was more discrete time step where each calculation dealt with the sub-populations collectively. Each time step would change the populations metrics such as percentages for infected, recovered, dead, etc. This also could be run multiple times to gather statistical distributions of possible results.
I expect that the actual models used to inform decision makers looked something like these.
Such simulations would be run periodically with updated information about the infection properties. I doubt the models of the population characteristics would change because those are harder (with current techniques) to update with new information. As information about the infection rates and mortality rates would change, the computed results would change.
Although the models are the result of rational designs with science-tested theories, they are still models. As we see with the current gated-phased reopening, the government is using the simulation results to guide their decisions. Although the simulations have parameters from the real world, government is about getting the simulation to produce favorable results and this will lead to favorable results in the real world. This is government by playing computer games.
A consequence of this approach is that the actual population has a passive role. As mentioned above, there is no time to update the behavioral models of the sub-population. People may in fact make substantial changes such as rearranging their lives but this would not change the simulation results. Only changes in the infection’s properties will change the simulation results, and thus will change the minds of the governing groups.
It is possible that modern data analysis approaches could update the behavioral models of the sub-populations as quickly as we can update the virus’s properties. I doubt this will work politically, though. Allowing the population parameters to change during the management of the epidemic would likely result in having to change direction in the governing guidance. Democratic governments expect steadfast guidance that involves a certain stubbornness to stick to the original decisions.
A decision-maker that makes a change would be admitting the previous direction was a mistake and that would likely end that leader’s career. If the people are going to have to change course, they might as well change the leader too.
Govern by charts
Another dark data approach to government is to study the technical patterns in the charts. The science of epidemics predicts a particular shape of the curve representing new cases and cumulative cases. The shape starts low and briefly rises rapidly but then begins to slow and eventually flattening out at some peak before declining toward zero again. The shape appears bell shape where the initial rise resembles a positive exponential curve at first but the exponent value gradually decreases to below one and eventually negative to gradually taper away.
The government’s decisions may be based purely on observing the plots and looking for the point when the upward curve begins to bends toward flat. Once it become clear that the bending has started, the government can conclude that the crisis is ending even if the new cases continues to rise.
The epidemic model based on numerous past epidemics predict that once the curve begins to bend toward flattening, the future peak is near and that will be followed by a decline. Once the curve starts flattening this way, the government can begin to plan on relaxing its policies.
I think this approach is more compatible with democratic government because everyone is aware of the technical tracking of a standard epidemiological curve. The latter easing of restrictions despite continued increase in new cases would be accepted because everyone understands that the end of the epidemic is near as soon as it is clear that the curve is flattening.
Other than the science behind characterizing the curve itself, there is no underlying assumptions about why the curve happens. There is no need to count the remaining number of uninfected, or how they are living, because the epidemic is following an assumed inevitable curve. The only question was when the bending of the curve will begin.
I am not aware of any government following this kind of strategy.
Govern by observations
Although very different from each other, both of the above approaches involve dark data, presumed truths from historically tested science. One is a model of how the infection propagates from person to person, or from group to group and it requires an accurate description of those groups. The other is a model of a predictable pattern of growth, flattening, and decline so that all that is needed is the moving average of daily new cases to see where in the curve the current situation is at.
My fantasy government prioritizes bright observational data over dark data of past discoveries. In the extreme it would dismiss dark data entirely.
As noted in last post, this government takes a passive role just gathering data until the majority of the population affirms a sense of urgency. Once properly triggered, the government would run an algorithm to select a particular authoritative ruling that will be enforced for a short well-defined period. After the rule expires the government returns to passive data collection unless or until the population’s sense of urgency triggers a new rule, and that one can be completely independent of the previous one, allowing for complete U-Turns.
In the past, I described this as a punctuated liberty type government. The default condition is complete liberty, but when the population complains loudly enough the government will act with strict authority, but just long enough to get people quiet again. Although this appears close to a libertarian type government, the justification is not based on moral principals such as the non-aggression principle. The justification is that the government needs to impose the fewest constraints on people in order collect the least biased data about how people behave and how the world operates.
From a moral perspective, my fantasy government is actually cold and fatalistic. It accepts that things will turn out the way they will, that people will do what people do, and that nature just needs to take its course. Even when triggered to take action, the goals of the new policy is more likely to maximize the benefits and minimize the burdens on the survivors when things are over, rather than to minimize the harm on the current population.
This form of government anticipates that there will be a future when this crisis will be over. At that time, only the survivor’s concerns matter. Those lost have no further political power, and they have nothing more to offer or to demand from the world.
When such a government is presented with the current situation, it would immediately accept the initial evidence that many people will get infected and many of them will die. Instead of trying to immediately stop this result, this government would calculate what will happen when the dire predictions come true.
I conceded in the past that the initial decision might be very similar to what we actually experienced, a near universal lock-down with narrowly defined essential activities. However, the purpose would be completely different. For this fantasy data-only government, the goal would be to inform and to convince the population that a true hazard exists that can affect anyone’s lives. After this message is received, the government would relax all rules and trust that the population will act in full knowledge of what is at stake. The population may act in a way that reduces the spread, or the population may act in a way that make it worse. Either is acceptable for the government that is primarily concerned about collecting data about how this current generation of humans behave.
While this may seem harsh and cruel, there remains the safeguard of the ability for the government to be triggered to make a new rule that will take into account the nature of the new urgency plus all the newly collected data about how people actually act after being under strict lockdown. I won’t predict what would happen next except that anything could happen next. The government may decide that the best thing to do next is to schedule a holiday and have everyone celebrate and feast in close proximity — the exact opposite of the prior ruling.
Each ruling is allowed to be completely independent of earlier rulings. This allows the government to take maximum advantage of the most recent information and the most recent expression of urgency that will inevitably be different from the prior expressions.
This independence of successive rulings is also a consequence and even assertion of rejecting dark data. The previous rulings are dark data relative to the newly collected observations about the situation and the human behavior. Also, because the rulings are grounded very minimally on dark data of scientific knowledge, that dark data continues to have little influence on future rulings.
If the population is chronically panicked, the government will continue to issue haphazard rulings that will appear like coming from a drunkard’s mind. It is unlikely that the panic will be chronic. People will begin to relax, at least to the extent that the panicked will not muster the necessary votes to trigger a new ruling. Evidence of human history shows that people will work together (at least in sufficient numbers) to assure the survival into the future. This survival is likely to be of the entire culture and way of life. If it falls short of that, it won’t fall too short.
Just as our current governments places faith in being guided by dark data from science and consistency, the fantasy government by data and urgency places faith in the current living generation of humans. The contrast is that the current governments prioritize preservation of the past while the fantasy government prioritizes the optimization of the future.