Blog readershiip

 An author is usually curious about who might read their work.   We don't have much idea on this, but we do have a streaming counter that keeps track of page views.   And of course we have the index of blog posts, so that gives us a rough metric.

This blog was a burst of activity in 2013, with 12 posts, and two more the next year.  Then it was quiescent for the next decade, until 8 posts in 2024 to update it and introduce some parallel COVID work.  

For the first decade, a modest 5,345 page-views were logged; in the past 15 months, an additional 3,158 page-views have been logged.   No one has bitterly complained to me directly, so I think that is a good sign.   And, truth be known, COPD has declined in terms of being a massive killer in the USA, down from a high of the third most prevalent death reason to sixth (ah, yes, COVID is still ahead, so there's some dynamic movement in the standings).

Nonetheless, the blog is worth 'keeping in place' for a while.   At least that's my conclusion.  Here's a plot of several blogs that I maintain.

COPD, COVID, and CDC --

Yes, this blog is about COPD.   I've been a COPD patient for nigh on sixty years at this point.   COPD is not exactly the most fearsome diagnosis.  You can live, sometimes for a long time, with COPD; I have.

Those of you who have followed this blog for some of the past fifteen years know that I have been passionate about COPD issues.    COPD rose from America's eleventh leading killer in 1960, to third in 2004, but in recent years has ebbed slightly to sixth leading killer in the U.S., claiming roughly 140,000 per year.   Astonishingly, despite the AMA and CDC's best efforts to describe COPD for the past sixty years as almost entirely a 'smoker's disease', the data is clear--other causes contribute, a lot.   85-90% was always said to be from smoking, but now even the 'best sites' say, "Ummn, looks like up to 1 in 4 victims never smoked."   And the recent findings about lung cancer (up to 60% in Taiwain who never smoked) give further credence to the notion that maybe air pollution is also pretty deadly.

A point that I have insisted since my first major study in 1970.   Never mind CDC's recalcitrant stance.

You might ask, "So what?"   Well, "so what" means that if CDC and the AMA are not viewing COPD as a disease that people get whether or not they have smoked, they likely are not backing research into further cause and effect, or treatments.   Which explains perhaps why for the past 35 years, COPD has gotten between one-tenth and one one-hundredth the per capita victim amount of NIH research money for studying dementia and cancers and strokes.

So, a long-term rant about CDC.  But wow,  I just finished a draft of a book about COVID.   I call it a COVID Anthology, because it mostly traces the discovery and progression of the worst world pandemic in a century.  Already, a mere five years past its initial onslaught, I find that few people, even in the medical profession, share a very consistent understanding of 'what happened and why'.  

The first draft is available, labelled "Advance Copy", at https://www.lulu.com/shop/charles-h-house/a-covid-19-anthology/paperback/product-57e6rwr.html?page=1&pageSize=4

What happened to me as I composed the book, and then reflected on what I learned in the process, is that  numerous mistakes were made along the way by key medical organizations and institutions, which helped contribute to a confusion, and even public distrust of some of these sources (e.g. CDC, WHO).

Unfortunately, CDC showed on two major issues that they still had their head parked where the sun doesn't shine with respect to being awake, alive, and helpful.   I'm not here to plead support for the idiot with the brain worm running HHS--that is truly much worse, but I do argue that CDC didn't do itself or the nation very much good during the COVID years, which in part has contributed to today's mistrust.

First, they supported the thesis that COVID was transmitted by contact--"wash your hands for twenty seocnds, humming a song so you know it is 20 seconds"     They ignored the clear evidence that it was airborne droplets, so small that only N-95 masks were of value, for nearly a year.   They gave advice to the administration for when and where to control the borders, and missed the most leaky of borders for six weeks, long enough that America was totally infected before any decrees were issued.   And worst of all, they muffed the COVID test kits in four successive attempts--in fact, never solved it but finally allowed independent university testing to be used.

The National Institute for Allergy and Infectious Diseases (NIAID), headed for many years by Dr. Anthony Fauci, was hardly blameless either.   Consider their strong support for the thesis that COVID emerged from the live animal market rather than an accident at the infectious lab in Wuhan; consider also that Fauci lobbied for years against the mRNA vaccine work, and only through DOD funding did that heroic work proceed.  Such stances alienated many who knew; more public knowledge would have been even more damaging.

These kinds of errors, mistakes, or biases don't require conspiracy theorists to cause public concern; more to the point, they help stimulate belief that maybe in fact there is something to this conspiracy stuff.

And historically, and even today, I have the highest regard for these institutions and their avowed purpose--we need them and their skill and dedication working on all of our behalf for public health. But it does pose questions--what went wrong, and why is this seemingly happening. 

I'll pose some thoughts in a subsequent post.

Some Vindication?

 I've long belabored the point in this blog and elsewhere that the primary description for COPD causes is misguided.   That smoking, "the smoking gun" if you will excuse the pun, is NOT the primary cause of COPD, never mind what CDC and AMA and ALA have promoted and proclaimed for sixty plus years.

My first clues date back to my first term on the Colorado Air Pollution Control Commission, when we were assured by CDC that Colorado was the 2nd worst state per capita for Emphysema (the primary portion of the COPD cluster), and neighboring Utah was 15th.   Married to a Mormon girl, I thought, "They don't allow smoking in Utah, how can that be?"

Armed with a dizzying pile of Z-fold computer printer paper with a decade of Colorado Health Dept statistics from their fancy new IBM 370-195 in 1970, I transferred the data to an unknown personal computer several years before the world knew of such a thing (the HP 9100A), and created a novel geographical demographic sheet for every death.  It revealed that smoking (and not incidentally the bad urban air of every Colorado city) did not correlate with the deaths.   Instead, small (often sub-micron) particulate matter, in a trapped toxic air environment, correlated extremely well.

This is all outlined in some detail in an essay entitled "Confronting COPD". https://www.researchgate.net/publication/236865558_Confronting_COPD

For years, I'd show the CDC maps (seen sporadically throughout this blog for years) that indicated poor correlation with smoking for COPD deaths but great correlation for Lung Cancer deaths.

Now, a disturbing truth is emerging on a world scale.   Even Lung Cancer now seems less related to smoking, and more to small-particulate toxic air, as Taiwan continues to experience surging Lung Cancer deaths in non-smokers.   Oh, my, how can CDC explain this one?

From the Journal of Clinical Oncology, reported at the 2024 annual meeting, "Lung cancer incidence in Taiwan has been rising with the epidemiological profiles distinct from Western country. Notably, nonsmoking lung cancers accounts for more than 60% and half of lung cancers were diagnosed in advanced stages."

https://ascopubs.org/doi/10.1200/JCO.2024.42.16_suppl.8009

Indeed, this story has been brewing for some time.   Two years ago this week, Climate News published a story over the headline, "Lung Cancer in Nonsmokers? Study Identifies Air Pollution as a Trigger."   Author Victoria St. Martin sub-titled it, "Researchers have discovered how tiny particles from fossil fuel emissions exploit a gene mutation to promote the growth of cancer."

https://insideclimatenews.org/news/05102022/lung-cancer-nonsmokers-air-pollution/?gad_source=1&gclid=Cj0KCQjwu-63BhC9ARIsAMMTLXSnnEG7l2DunzDhwAscxjVdRjAFP8aVOEIlBCU0QXv38r-H5gje-fMaAhLmEALw_wcB

This study 'fingers' coal-fired power-plant emissions, much as my study a decade ago does.   And it notes that we're now finding that 20% of American lung cancer victims were never smokers.   By the way, America's energy needs have resulted in 600% increase in power plant emissions since my CAPCC study--could there possibly be a relationship?   Duh...   

And COPD is more susceptible to this phenomenon than Lung Cancer.  Whew.   When will geospatial demographic studies begin to make an impression?

Revisiting the story

In the last post, early April, I described some preliminary thinking about twin proposals for a Virtual Medical Observatory.   Well, we decided to winnow the ideas into one proposal--and we await the decisions on that front (probably several months from now).

Meanwhile, our Bucky Beaver team cannot sit still.   We took the Chronic Illness idea on, and chased it to an interesting point.   Turns out that CDC has a host of major chronic illnesses 'on-line' as choropleth maps (well, not perfectly designed choropleth maps, but certainly maps built along that line.  Did I ever define choropleths within this blog, especially the issues involved in their proper design and display?

Ahh, choropleths--a fancy word, to be sure, but an important one for cartographers, demographers, or epidemiologists.   Here's the Wikipedia defiinition: A choropleth map (from Ancient Greek χῶρος (khôros) 'area, region', and πλῆθος (plêthos) 'multitude') is a type of statistical thematic map that uses pseudocolor, meaning color corresponding with an aggregate summary of a geographic characteristic within spatial enumeration units, such as population density or per-capita income.

Choropleth maps provide an easy way to visualize how a variable varies across a geographic area or show the level of variability within a region. A heat map or isarithmic map is similar but uses regions drawn according to the pattern of the variable, rather than the a priori geographic areas of choropleth maps. The choropleth is likely the most common type of thematic map because published statistical data (from government or other sources) is generally aggregated into well-known geographic units, such as countries, states, provinces, and counties, and thus they are relatively easy to create using GIS, spreadsheets, or other software tools.

I authored a descriptive essay to illustrate key features for choropleths using our COVID maps.  See.  https://www.researchgate.net/publication/377777227_Choropleth_design.   

Well, the point of this discussion is to say that we have adopted the COVID mapping models for a slew of chronic diseases.  29 of them, yup!   Here is the first view, showing all tractable illnesses on the left and a COPD choropleth map for California, Oregon, and Colorado (including ranked counties @ right)

Another choice is to compare two diseases for the same geographies.  Here, for example, we show the same states for COPD and Diabetes.   Note that Colorado and Oregon have much lower Diabetes rates than COPD rates, while counties in Southern California climb.  

Imagine this kind of comparative illustration for the panoply of chronic diseases, mapped to the granularity of counties for every nation on earth, able to be time-sequenced so that disease and treatment efficacy can be longitudinally evaluated.   This is the dream of the Worldwide Medical Observatory.

Telling the bigger story

 Well, maybe this is not yet "telling" the story, but it is a chance--a huge chance--to create a very large story.   We have been invited to participate in a pan-European bid for Next-Gen Internet capabilities, and we're immersed in preparing two bids for possible grants.

The first proposal is to expand the dataset that we built several years ago, for COVID-19 cases and deaths, along with per capita calculations of same, for 1,024 days for 3,141 USA counties and 196 countries.  

How might you expand that?  Well, some would like to have ethnic and age data, others would like vaccine rates and pre-existing conditions, etc.   That's for the data already gathered.   But what about equivalent data for other countries where today all we have are macro-data for the entire nations.

And, if you can get that, how about other 'pandemic-like' diseases (e.g. flu, colds, SARs).  But then immediately medical folk say, "that's all well and good, but what about many chronic diseases?  Diabetes, COPD, heart attacks, lung cancer, and many others have major findings related to geospatial mapping, and each would be good to work with.  Granted the data is not as dynamic as COVID data was for the early days, but what a treasure trove.

So, we're imagining putting a proposal together to build a Global Virtual Health Center or Observatory, hopefully to build something useful for the world's underpaid, underresourced Health Community.

We'll keep you posted, but we WELCOME your input.

Telling the story

 Well, interesting--Brian Berg and the Asilomar committee (this is the long-standing, e.g. 50th anniversary) microprocessor workshop) are granting me a ten-minute slot in the RATS section tonight.  My theme--"A Picture--Really worth 1,000 words?" is buttressed by a video tape with lots of URL's to other video clips, and it uses both the COPD and the COVID stories as the backdrop for why we've done so much with Virtual Multi-Display environments.  Here's the link for your viewing enjoyment

https://www.youtube.com/watch?v=UldbgcTl8Pg

This is actually a great opportunity.  The AMW workshop is one of the more prestigious events in our industry.  Today's technical talks were amazing--quantum computing made 'clear' and the incredible power hogging of the data centers and what a speciific Nvidia chip burns.   Most cities cannot host a data center of the Google size, and Google cannot hardly cool these systems enough to keep them running.  

I heard a definition of "Big Data" being done for one cancer study-- they had to 'reconfigure' Excel, from 1 million cells to i trillion cells--howze that again?   10 to the 6th, vs 10 to the 12th.   A mere 23 Million rows and 55,000 columns, easily and quickly scanned, according to the speaker!

So what we are showing is a quick overview of AVI capabilities, starting with the focus on what a picture can tell you, especially if using math tools such as Conformal Mapping and Convolution Integrals, not to mentioin AI Deep Dives.   And then, we show comparative pictures for "why multiple pix at once" and then we show the 3D aspects of walking through our environments (with accompanying companions from anywhere), getting to an interactive screen, scanning it and selecting from it to engage a stored video for that person, etc.

Quite the opportunituy!

Chuck

UNGA '78 -- A Day in Court

 As outlined in the last post, I did get re-energized about the state of COPD, and I was encouraged to bring the story to an august meeting of the United Nations General Assembly last September in New York City.  

How did that come about, you might ask?  What did you say?  And how was it received?

Well, the story could be viewed as a long one, or a short one.

The short version is that I got stimulated about COVID-19 statistics, like the week after I myself got COVID (the first person in Tulare County, California--on March 6, 2020, the same day that President Trump triumphantly announced at CDC that America has "plenty of tests, over a million. . . " when in fact there were none that worked, and only a few that had been shipped.

And I thought back to the old CAPCC days, when the data was slow and imperfect for a disease few cared about.  I thought "THIS will be different.  There will be LOTS of data, coming fast and furious (yes, we might quibble about how 'perfect' it will be)."

So, I began a major data acquisition of COVID data--confirmed cases and deaths--and quickly discovered that, YES INDEED, this was a LOT of data.   I knew an old HP colleague, Scott Futryk, who had a small company called AnywhereAnytime LLC that specialized in multi-variate spreadsheet presentations using PowerBI from Microsoft (Business Intelligence is the meaning of BI--Microsoft dubs it 'Data Analytics Report Software).    I asked him if he could help me construct a PowerBI view that was roughly akin to the old COPD geospatial maps (see blog posts herein for May 1, 2013 and May 11, 2013)

He did, and here is a snapshot of what he built (showing not only Confirmed and Deaths but per capita occurrences alongside those absolute numbers).  

I reported much of this work in another blog, InnovaScapes Institute, something like 49 posts in 54 weeks.    https://innovascapes.blogspot.com/2021/

I also posted one paper in ResearchGate   https://www.researchgate.net/publication/344751028_Four_'waves'_of_Covid_Confirmed_Cases_per_capita#fullTextFileContent

Well, the upshot of three years of work, was that Professor Martin Curley, the chief information officer for the Irish Health Service, was co-chair of the UNGA event.  Curley and I knew each other from our time at Intel Corporation a decade earlier, and he knew of this COVID study.   Hence the invitation.

The net was a chance to present an updated COPD story on the first day, and the COVID story on the second day.  Wow!   So that is 'how it happened'--I'll share what we said in the next post.