NedNotes (not blog): 22jan21 COVIData Sweep

In remembrance of five Americans ripped away by the epidemic this week. Three men; two men. Two people of color; one immigrant from Liberia; average age of seventy-four and median of seventy-eight. From New Jersey to California. 

B.L.U.F. (bottom-line, up-front): death rate is levelling off; speed of inoculation has assumed a paramountcy with exponential, existential variations of the virus.

INTRODUCTION
Summary. This week, there is little new to report. Some unusual daily numbers emerged during the week that might be attributable to good news or bad.

The analysis again is limited due to personal constraints (i.e., a professional euphemism for laziness). My review of the video produced by The Los Angeles Times should suffice only for those who really can not take the requisite ninety minutes to watch it. I have watched and listened three times and still am missing much of the substance. The greatness of this vid. lies in its intelligibility. A brief overview of those data presented this week, plus a quick comment on the daily data collected during the week, follow immediately below the disclaimer.

DISCLAIMER: any conclusions I propose are S.W.A.G.s (i.e., scientifically wild-assed guesses 😉). Even that is an over-statement since I only passed high school biology on the solemn oath I made to my teacher stipulating that I never darken another frog’s life . . . ever. 😱 (Notice that the stipulation is for another individual frog; hence I was free to annoy fifty-four million when my family and school packed me off to France for a term. 😊) 

Keep in mind that any conclusions I draw are intended, not to explain something I lack the background to know, but to stimulate the reader into asking questions and thinking for him-or-herself.

OVERVIEW of WEEKLY DATA
Summary. Tough winter indeed. Despite a notable drop in the number of fatalities for the week, deaths remain at levels over twice the number seen two months ago. A deadly ratchet effect may follow the emergence of more contagious strains. Most of the states on the watch-list remain there, with several others knocking on Hell’s door.

This week has recorded a notable decline in deaths of 7%, though the current level of fatalities of 22,003 remains a troubling 108% above that of the week preceding Thanksgiving (i.e., 10,579), the start of the current seasonal surge. Of the ten bellwether states, only Texas has had to assume an acceleration in the growth-rate of confirmed cases (i.e., a 7.8% increase week-over-week versus a 6.9% elevation the week before). The growth rate in deaths in seven states – Arizona, California, Oklahoma, Illinois, Wisconsin, Idaho, and Missouri – has exceeded their respective growths in confirmed cases. 

In reviewing these states, one must keep in mind that the national mortality run-rate for the week was 1.67%. Two points one should keep in mind here. First, five of the seven states have inadequate testing regimens, with testing penetration rates running behind the national average by 14% (Oklahoma) to 43% (Arizona and Wisconsin). Consequently, these states may be reporting fewer cases as they fail to count untested passive carriers.

The second qualification one should consider has to do with lag times. The time lapsed between infection (i.e., prior to the onset of symptoms) to death appears to be two-to-three weeks. So, when a spike occurs, people check into hospitals on a staggered basis since the community transmission of the virus occurs over time, rather than at a specific moment. Consequently, as the surge subsides, the number of new hospitalizations and incoming patients requiring critical care decline.

Sources: The Atlantic and Worldometer.

Nevertheless, with the two-to-three week lag-time, there are still people infected during the spike who are dying when cases dip. Thus, deaths relative to confirmed cases increase during the first days after the transmissions have ebbed, lending the impression that the virus is now more toxic or penetrating elderly care facilities once again. There is some evidence of the latter occurring or about to do so. During the current week, daily deaths have started low and ended high, as they usually do (for reasons I can not fathom).

This week’s increase in fatalities runs against a fall in new cases by 22% or more from the case-loads of the previous week; in hospitalizations by 8%; and, in patients requiring critical care by 5%. The higher level of new cases from the holiday season has ended. A declining number of cases means reduced needs for newly infected patients. Yet others already in the hospital still die during the week, thereby creating an appearance of an increase in fatality rates.

Another darker possibility follows in the feature section on mutations, below. A review of the weekly data from the ‘38+ table’, together with those of the bellwether states, indicates a stable week except in the South plus some scattered states outside that region. Of concern among the larger states (i.e., over ten million people) are California (with the highest growth in fatalities in the nation), Tejas, Pennsylvania and Georgia. Kentucky continues to deteriorate.

The week’s most improved performance award goes to Colorado, followed very closely by Michigan. These states, with Michigan oh-so-slightly behind in each case, have cut mortality growth in half; met or exceeded the national average for vaccinations; and, reduced positivity rates sharply. The Northeast, followed by the Pacific Northwest, have reported much improved numbers though positivity rates remained uncharacteristically high in New York at 6.2%.

Of the ten states on the watchlist for last week – Alabama, Arizona, California, the Carolinas, Georgia, Massachusetts, Oklahoma, Pennsylvania, and Tennessee – only Massachusetts could drop off the list, despite the threat of the virus to her ageing population. The Commonwealth is bringing her fatality rates down, leads the country in testing, and has improved her positivity rate, Nonetheless, the Bay State  lags other New England states in vaccinations. Tejas would take the spot vacated by Massachusetts.

¿CHANGELING or VIRUS?
Summary. Like the 1918 flu, mutations may make this coronavirus more deadly, but not by increasing its toxicity; rather its lethality would manifest through an acceleration of viral transmission, together with far stronger staying power against anti-bodies and B-cells. Specific T-cells, designed to kill infected cells and the viruses inside them, may be the next line of human counter-attack.

Now for the second, darker possibility to explain the rising fatalities in the face of declining cases, hospitalizations, and critical care requirements: not a lag-time but a virus increasing in lethality through mutations. The Los Angeles Times has sponsored a series of documentaries: two in early and mid 2020, which I missed, and this third one released this week.

This installment, however, bears directly on the race against the clock for vaccinations. Mutations evade anti-bodies and undermine B-cells. Depending upon their velocity of change and adaptation to human hosts, mutations are capable even of undoing the salutary effect of vaccines. Since the conclusions drawn during this documentary remain critically important to vaccines, here is where the United States stands in the vaccination race:

• 41.1 million vaccines distributed (enough to give 12.5% of the population the first dose; 1.2 million doses distributed today);
• 20.5 million vaccines administered (enough to give 6.2% of the population the first dose; apparently, some 1.5 million doses administered today);
• of the people vaccinated to date, 17.4% inoculated a second time;
• of vaccines administered, 2.4 million administered in elderly care facilities (or 11.7% of total inoculations; roughly 14.6% of those in long-term care; less than 5% of Americans over sixty five years old); as well as,
• 56% of the vaccines administered produced by Pfizer and 44% by Moderna.

The ninety minute vid., narrated by Dr Patrick Soon-Shiong, the Executive Chairman of the venerable newspaper, clarifies two concepts, at least for me. First, the Earth is only in its second wave of the COVID-19 pandemic since mutations, not seasons, better differentiate the distinct waves infections. Second, potentially similar to the novel H1N1 virus of 1918 (i.e., the Spanish flu), the second wave may well prove to be more deadly than the first due to a lethal mutation.

An increase by multiples of a virus’s contagiousness and the way it interacts with the cells attacked will define the increased lethality of mutations, similar in their adaptations, independently emerging in the U.K., the Amazon Forest, and South Africa. That is to say: the mutation makes the coronavirus more efficient, not necessarily more toxic. The L.A. Times presentation focusses on the new variant emerging rapidly in South Africa. It makes the following points.

1. Mutations in a coronavirus (with its attaching ‘spike’ proteins) are like master keys available to the virus forcibly to enter a cell and suck it lifeless.
2. This coronavirus is mutating and adapting far more rapidly than previous viruses causing pandemics; three, perhaps as many as eight, mutations can occur almost simultaneously.
3. This adaptive property is like the virus having a ring filled with master-keys to enter receptor cells in the nose and lung PLUS a quick-dry plastic mold to make a new master-key on the fly, if necessary.
4. The original virus had spikes with two binders, like docking lines on a sail-boat to tie up to a pier; only one of these binders could attach to the receptor cells.
5. Now both binders on the spike protein attach to the receptor cell, multiplying the strength of the invasive attachment many times over; think Velcro versus a button-clip.
6. This mutation showed up in September. By November it commanded some 40% of the ‘viral share’ in that country; now it is more like 90%. Think viral Social Darwinism.
7. The current vaccines provide preventive measures to lock the virus out of the target cells. Plasma treatments seek to introduce B-cells as one-off blockers of the virus.
8. Genomic surveillance indicates that anti-bodies are losing effectiveness quickly as they do not deflect the ‘new and improved’ virus.
9. The B-cells are more like putty with no memory.
10. The best defense against this coronavirus may be a good offense in working with specialized T-cells which kill off infected cells to prevent the spread of the virus (i.e., destroying the village in order to save it).
11. Think of a counter-insurgency. Most CO-INs try, like anti-bodies and plasma (B-cells), to repel the insurgents. T-cells are more like the search-and-destroy tactics.
12. Let us hope that General Westmoreland’s counter-insurgency plan fares better against COVID-19 than it did in Viêt Nam.
13. South Africa is structuring this science-first approach after classic technology transfer in ‘monetizing’ basic research by supporting the genomic sequencing of the coronavirus.
14. This public-private partnership, also like economic development and the coronavirus, thrives on diversity; it could set an example for the United States to emulate.
15. A South African of Asian descent living in the U.S. converses with a South African of Brazilian extraction. So, take note, those prone to group-think.

METHODOLOGY 
Since this data sweep serves as a information supplement without very little research, this week provides an opportunity to clean up the presentation through the following changes. For informational purposes, this text will follow the second table on thirty-eight states and five territories in subsequent weeks. For comprehensive explanations on methodology and purpose, please revert to Appendix I. 

1st, please remember that percentages for 'population tested' implicitly assumes that anyone taking a COVID test does so only one time. Many people are getting multiple tests. For example, for various reasons, I have had five tests. That would count as five people taking tests for the datum calculated for Maryland. My S.W.A.G. (scientifically wild-assed guess) is that a more accurate level of people actually tested is half, or less, of the percentage cited in the ‘38+ table’ above.

2nd, the two averages of weekly growth rates for the ten bellwether states are clarified in the Appendix. Essentially, the geometric or compound average growth rate is a smoothed average that allows for growth-on-growth increases (i.e., similar to compounding interest). The time weighted weekly averages are a trend-weighted average of each week's particular growth rates. While the compound rate is theoretically more defensible, comparing the two averages gives one a sense of more recent trends and volatilities.

3rd, in the '38+' table (of thirty-eight states and five territories), the risk classifications  -- of very low; low; moderate; high; and, very high -- remain the same. The parameters, however, are loosened to reflect nine months of experience. The new parameters center upon the first year base case fatality level of 335,301 souls that I forecast eight months ago, together with projections of November 2020 from the University of Washington of 470,974 deaths. On 04dec20, the old and new parameters are applied to facilitate  transition.

4th, changes in how positivity rates are presented in the '38+' table above now align the data with the original intention behind presenting them. The intent here is to show whether positivity is trending up or down and to what degree. The parameters are loosened to match the practical reporting constraints and data lags facing most states. 

States with changed positivity rates of less than 10% up (i.e., worsening) or down (i.e., improving) are deemed unchanged and the information unformatted (i.e., appearing in plain black font). The formatting differentiates deteriorations from improvements in the color of the font between 10-20%. Bold fonts indicate material deteriorations or improvements of more than 20%. 

Keep in mind that these percentage changes are based on percentages; percentages of percentages can attenuate the utility of data.

5th, a refresher on the assessment of a state’s testing capacity, again on the 38+ table. The data pivot off of the tests per million people expressed as a percentage. The symbology uses hand gestures to assessment the degree of testing capability and commitment relative to the national average for the week under review. Colors indicate whether testing is declining (red font) or improving (blue font) when a states results place its commitment to a new category of, specifically:

• 👎👎 meaning a state's testing level materially below the concurrent national benchmark (i.e., > 15 points below);
• 👎 meaning a state's testing is noticeably below the weekly national average (i.e., 5-15 points below);
• 👈 meaning a state's testing activity is slightly lower than average (i.e., < 5 points below);
• 👉👈 meaning a state's testing level is basically equal to that of the nation;
• 👉 meaning a state's testing level is < 5 points above the benchmark;
• 👍 meaning a state's testing activity is 10-15 points above the weekly national level; and,
• 👍👍 meaning a state's testing commitment is > 15 points above the concurrent average.