Coronavirus: Lessons

At this point in the experience with coronavirus, we probably have enough information to begin sketching the outlines of some lessons to be learned from the pandemic. Of course, it is always possible to learn the wrong lessons from experience, but nonetheless it is important to at least examine where we have been and to try and sort out what we know, what we think we know, what we don't know. and what we think we know but don't. In this spirit, taking each of the posts in this series as a hypothesis based on the information available when the post was made, this seems to be the state of lessons learned, based on subsequent information:

1. There is confusion about how easily the virus spreads. This is easily explained by the notion that the virus spreads easily and does not spread easily. In other words, it does not spread easily in the most common environments, but its ability to spread is greatly enhanced in other environments. This seems obvious by looking at the differential experiences in discrete settings associated with outbreaks, specifically nursing homes and long term care facilities. This is easily understood with reference to the post discussing the probability of virus transmission varying with the type of exposure. Most exposures are very low likelihood of transmitting the virus, but the number of higher risk exposures increases dramatically in favorable environments. This accounts for the apparent anomaly in case rates, and why the rates are in general lower than expected in community settings, and also why there is such a discrepancy between various locations.

2. The models that have formed the basis of decision making are based on assumptions that are overly simplistic. The idea that infection is a process of a susceptible person encountering a number of virus particles and thereby getting infected skips a lot of necessary detail. For one thing, different people will have different susceptibilities. For another, the risk of transmission varies continuously with multiple factors. For example, in the discussion of masks, there is a lot of theorizing about the virus being contained in droplets of body fluids; i.e. saliva, phlegm, mucus, tears, etc. The notion that these droplets are passive conveyances for genetic material is probably too simple. Those droplets likely contain enzymes, antibodies, chemokines, and other factors that may enhance or retard infection of another person with the virus. When the same material is coughed or breathed onto a surface and the accompanying droplet evaporates or otherwise metabolizes, the combination of the virus and the environment in which it is encountered likely changes the risk of infection. Whether this is enhancement or diminution depends on still more factors. Masks probably do limit the number of virions that an infected person distributes to the environment, but there is not enough information to know if this is significant; e.g. does it depend on whether the person in symptomatic, does it vary with time of day or hydration status, etc.

3. Whether or not lockdowns work, lockdown orders do not. There is simply no practical way to affect the course of a contagion with all of the exceptions, non-compliance, and necessary exposures which are unavoidable. If you seal 85 %  of the leaks in a ship, it is still eventually going to sink.

4. The most obvious lesson to be had from looking at different case rates, case fatality rates and hospitalization rates between various places, and trying to correlate them with "responses" is a fruitless endeavor. The underlying assumption, that government response has a significant affect on common transmission of the virus, is false. This is the lesson of Arapahoe and Douglas Counties, which had the exact same responses and significantly different results. It is foolish then to try and determine whether the Swedish response is better or worse than the German one, or the South Korean to the Singaporean, etc. Viral biology gets a vote, as do a myriad of other factors.

The term "common transmission" in the preceding paragraph was used intentionally. It is unlikely that lockdowns, and social distancing, and other measures beyond those common sense precautions that people are apt to observe anyway, affect the risk of infection of the average person. This is not however the case with those situations involving high probability exposures, such as nursing homes. The government can make things better with wise policies and significantly worse with poor ones. For every life saved by government intervention, there  some lost to the same apparatus.

5. Data driven decision were made considerably more difficult because of competing considerations for use of such data. Some considerations required inclusive data, and biased counting methods in favor of diagnosis, and others required more certainty, biasing against it. This reflected competing scientific priorities, but once economic and political factors were allowed to infiltrate the process, the state of the collected data became a mess.

6. Some politicians do not seem to understand that respect for the rule of law and public authority is not unconditional, and that it requires an infrastructure of trust, respect and common sense. "Because I said so, and I get to make that decision" is incompetent, leads to reluctance by law enforcement to effect such orders, and loss of authority for both law enforcement and elected officials when they are seen to be arbitrary, excessive and foolish. Tone-deaf appeals to "science" do not rectify the damage, since it is becoming obvious that the science is not nearly well-enough understood to be convincing. The loss of respect for authority, the flouting of government orders and ridicule of law enforcement will have long-lasting effects that will persist long after the coronavirus has faded.

7. Yes, the severity of coronavirus cases decreases over time. There is no good explanation for why it does, but it does. Some suggestions from various places include genetic mutation of the virus, different symptom profiles related to changes in weather, partial immunity, etc.

8. The notion of relative susceptibility limiting the number of community transmitted cases, as discussed in the first few posts in this series appears to be holding up. It is consistent with otherwise seemingly inconsistent observations regarding disease prevalence, antibody testing, R0, etc. Also, the notion that spread of the virus occurs around points of equilibrium that are largely determined by environment seems to have held up reasonably well.

9. COVID-19, while caused by a single virus is actually a family of diseases.

10. There is a lot we don't know: how long has the virus been in the United States, is the virus that infects people on the West Coast significantly different than that on the East Coast, does hydroxychloroquine work, does zinc, what is the incubation period, do infected people develop immunity, does smoking help or hurt, how infectious are children, is there cross-immunity with other coronaviruses, is there a post-COVID syndrome, how many years of life life lost are attributable to the virus, is there a mechanism by which mechanical ventilators increase lung damage that would not occur otherwise, will there be a second wave, will the virus fade in the summer, why aren't homeless people dying in droves, etc., etc.

11. The most important lesson, for anyone thinking of ways to use the pandemic to their advantage; political, economic, career, etc.: Don't play games with things that you don't understand. You may not like the consequences that flow from what you don't know.

Coronavirus:Clues

These posts contain frequent reference to the idea that there is no one single factor that accounts for the wide disparity in coronavirus impacts between various places. This is not to say however, that there may not be dominant factors. and it natural to ponder what these factors might be.

Arapahoe and Douglas counties are adjacent political subdivisions in Colorado. Arapahoe County has a population of about 650,000 and Douglas County has about 350,000 residents. Douglas County has a higher average household income. Being adjacent areas in the Denver suburbs, the two counties have very similar appearances; one is usually unaware of passing over the county line from one to the other. The City of Aurora has portions in both counties. The counties share the same board of health. Each county has three hospitals, one from each of the same three large hospital systems. The same physicians take care of patients in both counties.

As of 4/30/20, Arapahoe County had 2,472 COVID cases and 141 deaths, and Douglas County had 478 cases with 22 deaths. What might be the dominant factor accounting for this discrepancy? Why is the per capita case rate in Arapahoe County 2.7 times higher than in the adjacent county, and the per capita death rate 3.45 times higher?

The answer may be contained in an observation from the Kaiser Family Foundation: "27 percent of the deaths in the 23 states that report fatalities publicly have occurred in nursing homes and long term care facilities. In six of those states - Delaware, Massachusetts, Oregon, Pennsylvania, Colorado and Utah- the percentage of coronavirus deaths in nursing homes was over 50 percent of the total deaths..."

The Colorado department of Health provides outbreak data, listing individual outbreaks, the affected county and the number of cases. There were 38 discrete outbreaks in Arapahoe County as of 4/30/20. Over the same period there were 5 in Douglas County. This suggests that the cases in Arapahoe County are occurring among populations more likely to die from it, and this would at least in part account for the discrepancy in death rates. But it also suggests that having a nidus of outbreak increases the rate of infection in the vicinity. Nursing Homes and long term care facilities cannot be completely isolated from the surrounding community. Workers must go in and out, trash must be collected, supplies must be delivered, residents are admitted and discharged, etc. A nursing home may act like a corona virus factory that makes containment challenging in the immediate vicinity.

It is quite possible that the most effective coronavirus mitigation strategy would have been more effective isolation of nursing homes and long term care facilities, not simply because the residents were most vulnerable, but because they created the most efficient reservoirs for infecting teh broader community.