Impact of re-opening

How soon, people ask, will we know about the impact of "re-opening" states with quarantines or some other version of "lock-down"?   And, of course, there are so many variables that it might indeed be hard to discern, as new organizations and institutions have specific hotspots (e.g. the Fresno prison outbreak this week).

In fact, three 'local' counties exhibit this issue well.   We live in Tulare County, one of eleven roughly contiguous agricultural counties in the area.

Santa Barbara County, with 544 cases total on May 5, had 1,371 cases on May 12.   Of the 827 "new cases", 792 were at the Lompoc prison, 131 of them with guards and staff, the rest were prisoners.

Kings County, with 506 cases on May 23, had already had one food processing plant turn up 170 cases, but by May 31, they had 1,122 cases, and by June 6, 1,492 total cases.   Of the 986 cases in the past two weeks, 878 traced to the prison outbreak.

Fresno County had 1,448 cases on May 23, and two weeks later it had grown to 2,122.   Of the 674 new cases, 614 were at the prison.  

So, for those three counties, 2,284 new cases were specifically at local prisons, but only 203 in the population at large.   By contrast, Tulare County had no prison or nursing home outbreaks of late (they had plenty of nursing home and food processing plant issues earlier), but they had 475 new cases, the bulk of which appear to be 'community spreading'

We're seeing things like this all over America--Iowa, Nebraska, Texas, Oklahoma, South Dakota just to name a few 'unusual' locales.

Here, from our website https://anywhereanytime.io/covid19/ are comparisons of all the states in America, comparing the past two weeks (May 23-Jun 5) vs. May 9-May 22) for Changes.    We only report on States that are UP more than 30%, or DOWN more than 30%.   15 states are up that much or more; 12 states are down that much or more; 23 states and DC are 'more or less' constant.

States Rights

Page 2 of our InnovaScapes Institute Covid19 Dashboard https://anywhereanytime.io/covid19/ is for states and state comparisons, but Page 1 is where the true comparisons are best made in my view

Here, from a sample done two weeks ago, is a comparison of the breadth of Confirmed Cases for ten states--Orange is the 'bad' color, descending to Brown and Rich Blue.   White or Light Blue is GOOD



Note that many of these states exhibit widespread infections while others do not.  WHY?  Is it policy (e.g. the governor of Georgia being 'unaware' of asymptomatic community spreaders) such as early re-opening, or willful disobedient citizens congregating (e.g. "church rights"), or failure to institute 'lock-downs' soon enough?  

Clearly rural counties have, by and large, avoided the levels of confirmed case-rates that more urban centers experienced.   Not surprising in some respects--they travel less, have less interaction with strangers, etc.    It is not true (anecdotally at least) that they abide by social distancing, shelter-at-home, or wearing masks more than their urban counterparts.    But what is happening in Georgia and Alabama and major portions of Colorado obviously suggest that rural areas are not immune.

California Ag counties and COVID19

Agriculture--feeding us--is big business.   Almost $400 Billion dollars per year in cash crops.  All 50 states produce cash crops, ranging from $30M in Alaska to $50B in California.   Eleven contiguous California counties (of California's 58) account for 75% of California's total agricultural output, and three San Joaquin Valley counties -- Fresno, Tulare, and Kern counties -- are 70% of those eleven.    These three counties alone produce roughly the value of Iowa, the #2 state in America.    Among 30 major crops (more than $100M each), they deliver 90% or more of products like almonds, pistachios, pomegranates, and nectarines for America.  Surprisingly, Tulare County (the smallest of the three) produces one-third as much milk as the Diary State, Wisconsin.  Who'd have thought that?

And this is not counting wine.   Yes, 'AG Cash Crops' plots the grapes sold externally, but wine is considered a processed product, and hence "not agricultural" by definition.   California produces 89% of America's wine, a $700B market.  

But we're here to consider Covid19, and its potential impact on America's food supply.   We plot herein eleven counties, all primarily rural, none more than a million people, half of them Hispanic, with few towns of size, low per capita income rates, and by urban standards, low education achievement and health services.  

Being somewhat isolated has been an advantage for rural areas during the Covid19 pandemic, punctuated by hotspots in food processing plants as well as nursing homes, prisons, and retailing.
And, of course, the absolute numbers are small.   These eleven counties have  five million residents,  just one-half that of Los Angeles County itself.

Thus, meaningful statistics for these counties therefore must be per capita measures rather than absolute.  But trend lines--7 day moving averages, for example -- and Cases per 100K, or Deaths per 100K, can give us meaningful comparison data.

How about an example or two?  These are cumulative for March, April, May and early June.  They are compiled from our InnovaScapes Institute Covid19 Dashboard https://anywhereanytime.io/covid19/

The first example shows the "new case rate" for each county:



The second example shows the per capita Case Rate and Death Rate for the eleven counties, both in table format and in geospatial map.  Tulare, with five to ten times the death rate of the other ten counties (worth asking WHY on that one!), sticks out like a sore thumb on the geospatial map

"The Valley"

For the past eight years, we've lived in "the Valley" for the first time.   We spent many years in "Silicon Valley" which people here call "a little Valley" compared to this "Big Valley"
What they refer to, of course, is the Central California agricultural belt, the "San Joaquin Valley"

Three counties are the heart of this belt, starting with Fresno County at the north, then Tulare County in the center, and Kern County on the south.   These three counties are 'always' the Big Three in terms of annual agricultural revenue--with between 6 and 8 billion dollars each year per county.   Tulare is our home now, the smallest of the three in terms of area, but often the dollar leader.  It is a county with fewer than a half million people, with one town (Visalia) of 130,000 folk, two towns of about 50,000, and seven total incorporated towns.   Our town (Woodlake) is the smallest at 7,600--with something close to 90% Hispanic, and 57% of adults without a high school diploma.

I met this morning with Jessica Reynoso, who graduates from Stanford this week (our first Stanford alum from the local high school in years), and another local man, Gabriel Benavidez, who is a PhD candidate at the University of South Carolina in epidemiology.    He had seen my InnovaScapes Dashboard   https://anywhereanytime.io/covid19/   and had some interesting and challenging questions.   Like "where do we get our data?" and "do we have hospitalization data" and "who are you anyway, our school hasn't heard of Chuck House or InnovaScapes Institute but we follow the Covid data trail with much time and effort.

Jessica starts work in Washington DC next month, working with a non-profit, non-partisan group on issues of governance and equity for gender equality.   At sixteen, she pioneered an Unwed Mother's Community group that won her acclaim in Sacramento (& probably helped her Stanford application).
She was sponsored for several projects by the Woodlake Kiwanis club. Her parents were disappointed when she wanted to leave home for college; today they are incredibly proud of her accomplishments.

Gabriel 'knew' he wanted to go to college, but couldn't afford it.   His folks said, "you can, if you can earn it."   He parlayed a football scholarship into a Physical Therapy major at Montana State U, but he said he found that work not interesting compared to the metrics for sports kinesthetics.   His coach urged him to consider Public Health if he found statistics that interesting.   Baylor University agreed, and granted him a one-year residency for a Master's degree in Public Health.   Then UCLA, UNC, and U of South Carolina offered him a PhD program in Epidemiology, all with the same stipends.  His folks urged UCLA (close to home), but he said his single apartment in Columbia costs $800 per month and a shared apartment with four others at UCLA would be $1,000.   So--costs won out, but he's still proud of Woodlake and things here.   He did wave his arms though and say, I'm probably the only epidemiologist within twenty miles, if not more.   So, I'll have to live elsewhere no doubt.

Why do I relate this story?   Three reasons:
1. Local kids are resourceful, accomplished, and goal-oriented, but they often don't get the credit they deserve, and I just wanted to acknowledge a couple of them that I've come to know.
2. Local kids, to succeed, too often have to leave the area, which is of course a common story for agricultural communities, but it is also a saga of 'brain drain' for areas that need the help
3. Gabriel had incredibly good questions--the best I've gotten-- about our Dashboard, and what data he'd like to see, and how he gets the data he finds relevant.   And that will be the subject of our next set of posts.

A month of tuning the Dashboard

I've often got ahead of myself...thinking that "this" as in "this particular project"--must be ready for PRIME TIME.   Only to find that the real learning begins when the first prototype is released.  Such is the case with our Dashboard, first released four weeks ago, and now in its embryonic trial by real users.    Try it, at https://anywhereanytime.io/covid19/ and see what you think.  Fully interactive, county by county, for any date range you'd like--comparative stats are trivial, you'll find.

Where does the data come from?   We use seven sources, primarily USAFacts, the Johns Hopkins Center for Engineering, the 1point3acre Covid 19 site, the New York Times and the Washington Post
All are virtually the same, but occasionally they are out-of-sync, and we pick 'the best'.   Data itself comes from  County Health Departments, and the problems of this are rife--my own county last week announced that they'll only report on weekdays sans holidays.   So Tuesday is usually a "Big Day" in the press, as they roll Friday, Saturday, Sunday and Monday data together.    Counties in some states are forbidden to share Nursing Home data, others asked to forego sharing Food Processing cases--something about causing 'undue fear in citizens'.  

What were our initial learnings?

First, the choice of colors for the Choropleths--red and blue.   Turns out many observers thought this was a political statement, even though the Red Splotches were in fact mostly Blue Urban centers, and the light Blue to Blue areas were more the rural segments of America.  But go figure--everything these days, whether wearing a face mask to thwart (hopefully) Covid19 spreading is seen as unmanly or Left Wing Nuts, or opening a disco tech is seen as cavorting with the devil.  So we changed RED to ORANGE, and kept the various hues of blue.   Not quite as striking for "hotspots" but much more Politically Neutral.

More importantly, the calculation and 'load' time for 3142 counties for all this data is unconscionably slow, so we pre-load California now as the base page, and working from there can be reasonably time-efficient.   Always load a second state before dismissing the first one, will affirm for the program that it only needs to calculate the 2 requests, and not all 50 states.   Then, discard the first state, and voila, you have the new state replete with counties for about 1/25 the time it would be otherwise

And we now offer three pages--US Counties for each state, US States, and the World in combination with US States.   Interactive, powerful, fascinating, and a good way to spend more time than you might think you have available.  https://anywhereanytime.io/covid19/

I plant to issue some YouTube instructional videos--tips for using the site--in due course.   One is now available.   See https://www.youtube.com/watch?v=pp0VsSIBx4Q

Our Covid-19 Dashboard goes LIVE tonight

In my last post, I described our work on a Covid-19 dashboard, which has now proceeded to its first official release tonight.   It is a bit complicated, so we plan to do a couple of short video tutorials, but anyone familiar with geo-mapping tools can play from the get-go.

The page opens (albeit slowly, so we have to do some tuning), with four USA maps of all 3142 counties on the right half of the screen.   For any time interval selected, from one day to the past four months, the upper left map is of Confirmed Cases, the upper right map is of Deaths, and the lower two are of the same per capita.



We have some tuning to do on the color breakpoints, but this gives you a good idea of the very different perspectives that each of these views affords.  

On the left side is a table of all states, viewable via the slider since only about fifteen are shown at a given time.   There are four columns there, each one corresponding to one of the maps.  And clicking on each column stacks the rank order of states for each attribute.   Here are the same four in order:

 

Note, for example, that California ranks 5th in Confirmed Cases, and 8th in Deaths, but does not appear in the top 16 for either per capita table.   It is 32nd for Cases per capita, and 30th for D/PC

What is more fun, is the table at the far right allows selection of any state, and in fact any county or combinations of either or both.   That gives some fascinating additional understanding.   Here, for example, are four maps of California at the county level, followed by a comparison of CA and Texas

   

You can, for example, rank ski resort outbreaks, or meat packing locales, or anything that can be represented on a geo-spatial map, along with the data that corresponds.

Try it.   www.anywhereanytime.io/covid19

 I would like to acknowledge the help of Anywhere Anytime, LLC without whose support and their interactive Dashboard technology, this could not have been accomplished. This dashboard, created from conception to posting on May 7, 2020, took a total of 14 days.

I think you might find it intriguing.

And please, let me know of errata, etc.
Best regards
Chuck




 

Covid19 on our minds

Robert Burns once said, “The best laid schemes o' mice an' men / Gang aft a-gley.”
I didn't intend to get caught up in this Covid pandemic, nor did many others.
But somehow, in the fourth week of January, for the next two weeks, I couldn't get out of bed for more than ten minutes at a time, and my chest felt like it was being squeezed by a python.

By the time I sought help, the hospital was none too eager to see me.  They popped me into an isolation room, gave me a few antibiotics, and refused to test me for Covid although President Trump that day at CDC (March 6) announced that "a million tests are now available".   Well, he was, shall we kindly say, 'mis-informed.'    

Over the next five weeks, I was poked and prodded, given five separate X-ray exams for pneumonia (and presumably the virus), tested for Valley Fever, heart issues, pleurisy, and a host of less well-known things.   I have a thesis about medicine--if the name of the disease has a doctor's name associated with it, it is probably not a good thing to be considering.

At this point, I am functioning again, and in the past two weeks have gained back enough strength to be able to walk to the front gate and back (about three hundred yards).  The dog is grateful--his evening walks have resumed, and his constitution has never been better.

And then, voila, the studies started emerging that claim that the virus was community-circulating in January and February in both California and Washington--despite numerous assertions that it came from China only in late February.   Granted, the studies have been roundly criticized, but not about that finding, simply that the samples weren't entirely random.

And although I had mused that I'd taken no trips for months, reviewing the calendar revealed a three-day sojourn in Napa and Sonoma counties in January, plus a large funeral service in Los Altos, and then a four day February trip to Palm Springs, staying with numerous friends from the Seattle area (about to have an epicenter explosion, we now know), and a work-week at the Tulare County agricultural fair.   

The Tulare County Fair was one of the last big gatherings in CA before "shelter-in-place" orders from the governor.   It has 150,000+ visitors, from 65 countries.   I managed to spend a couple days with a vendor from Daegu, Korea, unaware that Daegu was the epicenter that very week for the Korean covid-19 outbreak.   When the hospital urged that I call the Korean person, I shouldn't have been surprised that the company answered in Korean.   Engaging an emissary a day later generated an e-maill from them, written in Korean, saying they were fine, and they hoped that I and my colleagues were likewise.

A total of six people at our ranch wound up sick (four saying they felt "deathly ill" for days), all at the same time.   We're not exactly a nursing home here, except for geriatric horses, but it seemed a strange coincidence.

So, not that you care about this particular story, what is perhaps important to share is that it caused me to take more interest in the data behind the events, and that in turn has led to what I am now terming the "InnovaScapes Institute Dashboard"    You can see rudimentary versions at www.anywhereanytime.io/covid19  

This has several important features that are difficult to find on the more prevalent dashboards, that I plan to describe in succeeding posts.    Notably, you can group any set of USA counties, and just see them in comparison.   Example-- how about just the counties with major ski resorts, destination places where world-wide travelers encamped for days during January-March.  Were they worse than surrounding areas, the same, or relatively unscathed?   Or, in the case of little Tulare County where I live, it seems odd that a small rural county with only one town of 100,000 folk, would have the seventh highest case-load per capita in CA, or the third highest 'kill-rate' out of 58 counties.  Was it that Farm Show, or the two nursing home flare-ups, or a combination?

The macro-map, of 3,144 counties for the 50 states and D.C., reveals the dichotomy of rural vs. urban case-load incidence, giving credence to both those urging relaxed standards and those fearful of future flares.   We can plot case-load, new cases, deaths, death-rates per incidence, death-rates per capita, timelines in both linear and logarithmic plots, etc. at the click of a button.   

I've longed for this capability, as many of you know, for years for the COPD issues in America, but unavailable to me until now, with the help of Microsoft Power BI business analytics (similar to but seemingly more powerful than Tableau), and with the help of wizards at AnywhereAnytime LLC (anywhereanytime.io) which specialize in Silicon Valley Executive Dashboards.  They do an amazing job for C-suite executives seeking powerful synchronous data-visualizations for their business--I thought "why not?" for my concerns.

Stay tuned...