A government by data and urgency could make innovative choices because it is not bound by tradition or precedence. In the case of the current epidemic, the data shows that the epidemic is very hard to contain through quarantines. In addition, the expansion of quarantines to suspected contacts or entire geographic regions inevitably removes a large number of people from the economy for a period of time.
Given the trajectory of quarantine expansion, it appears inevitable that there will be a point where entire nations or continents may be in quarantine. As seen with people held in cruise ships, such quarantines make more likely that the uninfected will become infected.
A possible approach to make quarantines more effective would be to have readily available testing kits so that we could test the entire population for infection even before exhibiting symptoms and then quarantining them based on the test. Even if that would be feasible, the testing would have to be repeated every few days because they could become infected in that amount of time. The test would have to be very effective with high sensitivity and low false-alarm rates. But more importantly it would have to be applied extensively and regularly for the duration of the pandemic, a period that may a year or more.
At some point quarantines based on infection status or suspicion will be counter productive: we would be better off without quarantines at all.
Meanwhile, we are getting good data about the outcomes of those who are infected. Based on extensive testing that is occurring in South Korea, it appears that the majority of people becoming infected will recover without medical care and that proportion may be above 80%.
The remaining population will likely need intensive medical attention and many of those are at risk of dying.
We are getting good data now that is identifying the populations most at risk of needing intensive medical care when they get infected. The at risk population has some condition that is readily known in advance without any need for new testing. This population has some pre-existing condition, particularly chronic respiratory ailments, diabetes, hypertension, or just being over the age of 50 or so.
From source on 3/11/2020:
COVID-19 Fatality Rate by COMORBIDITY:
*Death Rate = (number of deaths / number of cases) = probability of dying if infected by the virus (%). This probability differs depending on pre-existing condition. The percentage shown below does NOT represent in any way the share of deaths by pre-existing condition. Rather, it represents, for a patient with a given pre-existing condition, the risk of dying if infected by COVID-19.
PRE-EXISTING CONDITION DEATH RATE
Cardiovascular disease 13.2% 10.5% Diabetes 9.2% 7.3% Chronic respiratory disease 8.0% 6.3% Hypertension 8.4% 6.0% Cancer 7.6% 5.6% no pre-existing conditions 0.9%
COVID-19 Fatality Rate by AGE:
*Death Rate = (number of deaths / number of cases) = probability of dying if infected by the virus (%). This probability differs depending on the age group. The percentages shown below do not have to add up to 100%, as they do NOT represent share of deaths by age group. Rather, it represents, for a person in a given age group, the risk of dying if infected with COVID-19.
AGE DEATH RATE
80+ years old 21.9% 14.8% 70-79 years old 8.0% 60-69 years old 3.6% 50-59 years old 1.3% 40-49 years old 0.4% 30-39 years old 0.2% 20-29 years old 0.2% 10-19 years old 0.2% 0-9 years old no fatalities
The currently available data suggests a very different strategy for dealing with a pandemic. This strategy is to change the focus of quarantines. Instead of sealing off the potentially infectious people from the health population, we could be sealing off the population of currently healthy people whose readily apparent preexisting conditions put them at the highest risks of needing intensive medical care if they were to get infected.
We are seeing this now where the infection spreads in old-age assisted-care centers where there are abundant people who will get very ill if they contract the disease. We need to focus on sealing off such populations from any risk of infection as long as they remain uninfected.
This proposal would apply the sealing off (quarantine) conditions only to healthy people but those who have the preexisting conditions most at risk of having complications that will require hospital care and that can likely result in death. This population is easy to identify. On an individual basis, the logistics of isolating them from the rest of the population is similar to quarantining the infected. The population having the relevant preexisting is large in number but at some point this population will be smaller than the 80% of the population who will be able to recover on their own when they get infected.
In contrast to the quarantine of infected people as they get infected, this approach starts off isolating a large population at first based on preexisting conditions. As those people become infected despite the isolation measures, they are removed from this isolation because at that point it is clear that the isolation is no longer useful. In contrast, the removal-criteria for quarantining the potentially infectious is less obvious.
By analogy, the data we are collecting about the pandemic is similar to data modeling of some approaching hurricane projected to make landfall. We have the advanced notice to prepare for something we cannot stop. In the case of storm preparation, we secure the items most at risk of damage and leave the more robust items to weather the storm. A similar approach may be most effective when preparing given the advanced notice of the spread of a pandemic. We should focus on securing the most vulnerable and let the more durable weather it out. If something does get impacted early in the storm, we can rearrange the remaining unaffected items to improve their security.
Another dimension of the data received so far is that the fear of the disease is about the severity of the worst cases. One fear is that one would find themselves in that condition. A broader fear is that the number of those in that condition can overwhelm the healthcare system and also cause major disruptions on communities. This data also supports the idea of refocusing efforts away from quarantining the infectious and instead isolate the most vulnerable.
The goal should be to minimize the severe cases and deaths instead of minimizing the number infected. If we did have the data to recognize the preexisting conditions that increases the risks of complications and death, then our only option would be to minimize the infected in order to minimize the need for hospitalization or the risk of death. We do have data now that recognizes these conditions.
Clearly this option is politically impossible. The government would have to impose isolation on a population that is healthy enough to enjoy free movement and often be productive in the economy or active in the government itself. This is particularly true if the isolation was based on age, a large fraction of the population over 60 is active and often occupy senior roles in various areas, especially in the government. Isolating them for their own protection would result in vacancies that will need to be filled by the less vulnerable. Once filled, many (if not most) of the new holders of those positions would hold them permanently.
When the disease finally becomes less urgent due to the introduction of effective vaccines or effective treatments, the quarantined healthy people with preexisting conditions will be disappointed in not being to return to the positions they previously left under healthy conditions. Their jobs will be taken over by others, and at least for the older portion of this population, they will have a hard time finding a comparable position somewhere else.
As a result, this is not politically possible in a democratic type of government. Such a government is doomed to the constant news of new hospitalizations and grieving of newly deceased among families, communities, and work places. Unstated in this approach is that we prefer this outcome to an alternative of fewer hospitalizations and deaths where a large number of people who were kept healthy would be removed from the economy through isolation initially and through loss of standing or employment in the long haul.
A government driven by algorithms and data instead of human rule or overruling abilities would choose the best option given the data available. That option may be to stop quarantining the infectious and instead isolate the most vulnerable as long as they remain uninfected.
*Amended 3/11/2020 to insert statistics for age and comorbidity, and lowered the at-risk threshold to 50 years old.
Addendum 3/12/2020 (source referring to Austria):
Schools will be closed, over 1 million students will stay at home until at least April 12. Chancellor Sebastian Kurz appealed that grandparents should not take care of the children, so that the elderly be protected against the coronavirus. Children are “much less at risk when it comes to illnesses, but at the same time we know that children are strong multipliers,” said Health Minister Anschober [source]