I added the data for Los Angeles County (whose aggregate data still apparently excludes the cities of Pasadena and Long Beach). Averaged daily new case rates / million people have exceeded 600 in recent days (compared with just under 300 for the whole SF Bay Area, and 120 for Marin, where I live.)
COVID climb every mountain
A graph comparing average daily new case rates (per million people) for each of the Bay Area counties, plus their average ... and the average for the whole of California.
California now averaging about 378 / million / day; the Bay Area averaging about 250; Marin just under 140. California excluding the Bay Area: 406.
Sources: Marin HHS, SFist, LATimes (github repository), current 2nd December.
COVID dropping
COVID in Marin - 26 new cases, 4 newly hospitalized, no new deaths.
A continuing trend of new cases at far lower rates than two or three weeks ago. Assuming (hoping?) that this is not because of deficiencies in reporting, as was the case in mid-August, the diminution in new cases seems to extend throughout the entire Bay Area and - not shown - California.
Sources: Marin HHS, SFist.com, LATimes github repository. (Data for Marin have San Quentin cases subtracted; Contra Costa data at SFist had anomalies in August where I relied instead on the LA Times.)
COVID the 6%
Last 24 hours in Marin County: 23 newly diagnosed cases; no new hospitalizations, no deaths.
A little headline going around says that 94% of those with deaths attributed to COVID had underlying conditions. I find it hard to respond to this without emotional involvement, but will try. And then I include a related note from a medic, and a clarifying note from a neighbor.
There are two major problems with the idea that only 6% of COVID deaths lacked other medical conditions.
The first problem is this: I don't understand why it isn't zero. All human beings have other health conditions; perhaps it's that 6% of us haven't had them diagnosed yet.
The second problem is the implication that somehow COVID isn't that lethal. (In a few days I hope to post a comparison of COVID with seasonal flu. Summary: COVID is far worse.) The fact is that approximately 100% of those who died from COVID died prematurely. About 100% of them would still be living still and, if not fully well, would still be about as vibrant and alive as they were a month before COVID took them.
From a friend, citing a close friend, a medic, who notes ... "I've been getting some questions about the whole 94% of people who died from Covid had other contributing factors thing. That's because when we fill out a death certificate, we're supposed to list all contributing factors. Say you got covid, then developed pneumonia from it and got respiratory failure leading to you dying in the ICU (even though you were fine before). Then I list covid, pneumonia, respiratory failure. If your kidneys failed because of covid clots, I list 'kidney failure' as a contributing cause of your death. If you threw clots to your lungs and infarcted them, I put 'pulmonary embolism'. If being intubated with covid affected your heart you might get 'myocardial infarction' or 'heart failure'. If you had a chronic condition, then you will also get 'diabetes' or 'hypertension' or even 'obesity' listed. It's like if someone comes in and dies from a heart attack, their cause of death is listed as 'myocardial infarction', with the contributing factors of 'coronary artery disease' maybe, and if they've ever had a high cholesterol reading 'hyperlipidemia' or if they had higher BP before 'hypertension'.
If you have diabetes, and that leads to renal failure, and heart disease and a stroke, the diabetes still caused it, but you're not going to just have 'diabetes' listed as your cause of death either.
What it doesn't mean is that we are overcounting covid deaths. Thanks.”
—-
Carolyn Lecoque added this helpful clarification:
To respond to your, "problem with the idea that only 6% of COVID deaths lacked other medical conditions...I don't understand why it isn't zero. All human beings have other health conditions; perhaps it's that 6% of us haven't had them diagnosed yet.
Within the healthcare system, an "underlying health condition" refers to a medical problem that is chronic or significant and usually requires long-term treatment- such as diabetes, heart disease, obesity, cancer, or kidney disease. Yes, none of us are perfectly healthy so we may have some other health condition but it is not severe enough to be labeled as an "underlying health condition." Having a medical history does not mean you have an "underlying health condition."
I fully agree that COVID-19 is lethal as over 180,000 people in the US have already died from this disease. When the immune system is already tackling an underlying health condition, the body's ability to respond to a novel virus is compromised. There are hundreds of health conditions which may affect immune function but, heart disease, diabetes, cancer, obesity, and high blood pressure have seen the highest number of fatalities from COVID-19. The reasons for this lie with the aggressiveness of the conditions themselves and how they are already affecting the body's ability to fight off illnesses.
—-
Thanks, Jay McGill for discussing, I lifted the first quoted text from a Facebook post from Shelly Glennon and Carolyn Lecoque for the added commentary.
Compendium / placeholder
The posts for 10 days that I didn’t put up in time.
Heat map
A few exceptional days of torrid heat (and wild storms) tempted me to attempt a new heat map of COVID case density in Marin County. Notes: the data are from Marin County HHS and are likely to be undercounting cases, due to the well-established CalRedie system problem. I entered San Quentin with a 10x lower case density than it really had - otherwise the software wouldn’t show any gradations at all for the rest of the county. And all the bright yellow areas - that’s where the county doesn’t provide specific numbers, so I entered plug data (as I did also for Pt. Reyes, where there are known cases, but the zip code population count seems far too low). The white space is atop Mt. Tam, which doesn’t count as being in a zip code at all.
COVID & GIGO
Marin in 24 hours. 1,530 tests completed. 8 new positive cases. 1 death.
GIGO? Garbage in / garbage out.
It's a common expression in analysis. Your model may be great, but if the data are no good, your output's going to be bad.
An example. The SFChron reports on a model from Georgia Tech (good school!) that tries to predict what the probability is that someone in a crowd of 25 people has COVID. From the article (and note, the Marin projection is badly wrong): "A quick browse through the map yields some troubling numbers. If you’re in San Francisco County and decide to attend a gathering of 25 people, there’s a 34% chance that someone who’s coronavirus-positive will be in attendance. In Marin County, the risk is 75%. In Alameda County, it’s 31%. Increase the gathering size to 50, and the risk goes up significantly. In San Francisco County, the likelihood is 56%; in Marin County, it’s 94%."
Two errors apply to the Marin case.
First, and worst: they include the San Quentin outbreak in the Marin general population. That's 2,212 cases on top of the nearly 3,000 cases in Marin's general population: a major difference.
Second, and more subtle: the estimate of seroprevalence is 10:1 x the known count. They acknowledge that this estimate will be too high in areas where there is a lot of testing (like Marin, where completed tests exceed 53,000 - 21% of the county's population). The online tool allows adjustment of the seroprevalence ratio to 5:1. I did that and the risk of someone in a group of 25 in Marin having COVID dropped to 31%. That still includes the SQ cases in the general population.
The risk in Marin - especially the south of the county is closer to and likely lower than that in SF. I'm not saying it's safe to gather in crowds. Wear masks! Keep distance! I'm saying: the SF Chron article is wrong. (I've written to Georgia Tech and offered to help them correct their data.)
Map attached from Georgia Tech: the whole USA map is their general case w/ seroprevalence ratio at 10:1. The zoomed-in map of Northern California has the ratio set to 5:1.
Maps attached from Georgia Tech. Model at https://covid19risk.biosci.gatech.edu/, Chronicle article at https://www.sfchronicle.com/bayarea/article/If-25-people-gather-in-SF-odds-are-34-that-at-15458554.php
COVID by the dock of the Bay
Marin, 24 hours: 1,147 tests; 39 new confirmed positive cases, no deaths.
So, how is Marin County doing, compared to the rest of the Bay Area? Let's look at the average number of cases over the past week. And then make that new cases per million people: Marin has just 258k people: only Napa (135k) among the Bay Area counties has fewer. Santa Clara has 1.8 million.
The graph: Marin has doing rather worse than other counties, but the past week has seen a considerable improvement.
How this works: Marin has about 46 new cases / day (down from 70 /day two or so weeks ago), and a population of 251k, so it rates about 180 cases / day / million. San Francisco has about 137 cases per day. But its population is 871k, so it has an effective rate of 157 cases / day per million.
BA9C = the average across the nine Bay Area counties.
Sources: Marin HHS, SFist, LATimes github repository. Marin data adjusted to subtract San Quentin. Current as of 3rd August.
COVID spread
40 new cases on 1,848 tests, and two deaths.
While the contagion spreads, it is doing so at a slower rate per day than a few weeks ago. California's official assessment puts R(t) at 0.78 in Marin County, which would imply that we'd be on course to get COVID well under control. This is puzzling: it might be true, but could be an artifact of the number of cases in San Quentin declining as infected inmates are transferred out. The underlying data puts Marin R(t) at 1.03, which seems more reasonable, so that’s the basis of the map below.
rt.live shows R(t) for the entire state at 0.97 (the official State website has R(t) at 1.02, estimated from a calculation based on using about a half dozen institutions' different models in an ensemble analysis). The estimates are both within each other's estimate range.
Sources: Marin HHS, https://rt.live/us/CA and https://calcat.covid19.ca.gov/cacovidmodels/
Seroprevalence! Wassat?
Quantifying the reach of an epidemic
Today’s little discussion is brought to us by the number 8 and the word “seroprevalence”. I don’t think Sesame Street got that far, but it’s interesting.
We ALL by now know that one of the quirky things about COVID is asymptomatic transmission: people get it, but don’t know they have it, and pass it on anyway. And some people get it, but don’t suffer much, recover and get on with life. How many people have got it beyond the numbers which have tested positive?
Seroprevalence is a key word used by epidemiologists (scientists who study epidemics for a living). What it means is: how much of a population HAS caught the disease, how far the disease has propagated into the population - separate from the number that TESTED for it.
Quantifying that is difficult, without lots of testing and, as we all know, the USA at first dropped the ball on testing. Despite wailing from on high, the USA today is routinely performing more tests per 100k of population than any other country: in Marin County, about 19% of the population has been tested. California has carried out nearly 900,000 tests in the past week, and nationwide there are more than 2 tests per thousand people per day - nearly 400,000 per day in total.
But as many people as are being tested, there are some people who contract COVID and don't show up in the numbers. (Perhaps because they don't know they've got it - the symptoms are mild - or because they DO know they've got it, alongside a family member or neighbor who was tested.)
The huge increase in testing in the USA means scientists now have some idea of how far the disease has spread beyond confirmed cases. The lowest credible ratios I can see between confirmed and total cases are 2x to 4x. Some renowned scientists believe the ratio to be as high as 7x or 8x. Applied to Marin that'd mean perhaps 8% (one in 12) of the county has contracted it - perhaps as many as 20% in central San Rafael. Simple summary:
For California there may be more than eight times as many people in California who have contracted COVID as have tested positive for it. So, over 9% instead of 1.1%.
Is that good or bad news? How do we know about people we haven’t tested? Good questions:
Is it good or bad? Yes. Both.
Suppose that eight times as many people have contracted COVID as have been tested. That’d mean that 8% of the county’s population has - or has had it. If (and this is probably a bad assumption) that 8:1 ratio applied uniformly throughout Marin County, then nearly 22% - nearly one in four people - in San Rafael (94901) would have been affected, but just 4% - one in 25 - in Southern Marin. Bad news, absent 100% mask compliance and distancing and hygiene, it’s easy - and getting easier - to get this disease.
The good news - obviously - is that the actual fatality rate is lowered. But don’t be fooled: it’s still far worse than any other contagion to have shown up in the USA in ages. 150k deaths on 4.4 million confirmed cases and perhaps 32 million total cases across the USA is still ghastly, whether it’s the 3% of confirmed cases or the 0.5% of all cases. (Flu fatality is typically 0.1% on confirmed cases, far less again versus total cases, and its spread is limited by vaccines.)
Also good news is that the chance that a random person in southern Marin is COVID-positive is quite small.
However, the worst news is that we’ve a long, long way to go before there’s any form of herd immunity. Herd immunity only occurs when something like 70% of a population cannot transmit the disease. They can’t transmit it because they have immunity from having had it - or because they’ve been immunized by vaccine. When lots of people in a crowd are immune, the disease cannot propagate.
In contrast: southern San Rafael might be about one third of the way to immunity. In principle. In theory. And in the absence of a vaccine.
Note: the journey to full immunity without a vaccine is a journey in which at least seven times as many in the county would have to catch it. You can imagine what that means in terms of illness, death and grief.
How do we know?
I assume that everyone now knows someone who has tested positive for COVID. There was a cluster on one of the docks where four people were sick with identical symptoms and one tested positive: the others weren’t tested. The County has no (official) knowledge of this. But there are ways that allow researchers to get increasingly accurate estimates of who is not being counted otherwise:
Test lots of people: there was a hot spot in SF’s Mission District, and a big push to test LOTS of people, without regard to any known exposure. This suggested, back in late May, that at least 80% of the people in that area who had contracted COVID had not previously been tested. This is the best approach to getting an accurate read on seroprevalence, but it assumes widespread and repeated testing availability.
Following local test surges in hot spots around the Bay Area, UCSF’s Monica Gandhi said: If we did a mass testing campaign on 300 million Americans right now, I think the rate of asymptomatic infection would be somewhere between 50% and 80% of cases. Millions of people may be spreading the virus without knowing it.”
Test lots of blood: not as much as before, perhaps, but lots of people have blood drawn for lots of reasons. Some samples are additionally being tested (I assume there is strict compliance with privacy regulations) for COVID. A University of Minnesota study based on this approach early on found twice as many people had COVID as had tested positive. This methodology has a systemic flaw: it only tests people who are already having blood drawn for something and are in a healthcare system.
Mathematical modelling: as we learn more about the disease, particularly with data on how people get it and recover, scientists can make reasonable estimates of what fractions of a population will be asymptomatic compared to those who get tested and are found positive.
As of this week, somewhat over 450,000 Californians have tested positive: that’s 1.1% of the state’s population of 39.5 million. The estimate of seroprevalence in California that has won at least some highly credible support is that of YouYang Gu of MIT. The published estimate there is that 9.5% of Californians are infected, whether they know it or not, and whether they’ve been tested or not. So, about 8 times as many people are infected as have tested positive for it. Nationwide, the same source estimates that slightly over 10% of the entire country’s population is or has been infected. Thus, instead of 4.6 million (the known number of positive cases), there could be 32 or 36 million infected to date.
Remember: this is good and bad news.
Sources: lots including:
https://coronavirus.jhu.edu/testing/international-comparison
https://ourworldindata.org/epi-curve-covid-19
https://covid19-projections.com/us-ca
https://www.health.state.mn.us/diseases/coronavirus/blooddonorstudy.html
and Marin HHS for local data.
COVID
Four people newly dead from COVID per the Friday Marin HHS report (this does not include San Quentin inmates).
66 new confirmed cases; no newly hospitalized. Total cumulative tested positive as of Friday was 2,482 - a whisker under 1% of the county. The HHS numbers don't quite add up on geographic distribution, but you'll see that over 2% of San Rafael has tested positive (it's 2.7% in 94901). Spread in southern Marin remains at a lower pace. The number of tests (or tested people?) in Marin is equivalent to nearly 19% of the county's population.
(Tomorrow, I hope to describe the estimates of how many people have been infected and not counted via tests.)
San Quentin counts 864 inmates as currently infected; the county, using a different approach, lists 2,071 - out of an inmate population of 3,771 - as having been infected: 55%!
(All today’s data from Marin HHS, current as of Friday 24th July)
COVID of the day
Marin update: just 18 positive test outcomes (on 615 test results). No new hospitalizations, no deaths.
SQ continues to report declining numbers as, I assume, it transfers sick / confirmed positive inmates elsewhere. The total had reached 2,108 (not sure how large the inmate population is, but not more than 3,500?).
Masks - the county now allows ANY county government employee to issue citations for not wearing masks. In theory. We'll see.
A little heat map attached just for Marin, mapping positive cases as % of population for the county. (Converting Marin HHS data, which is by named town, into a map organized by zip code, is more work and less precise than I'd anticipated. Yellow = few people / no data or areas where the count doesn't pass the threshold at which Marin HHS issues data - and so I used 0.1% to just make the areas show up; white = no zip code.)
COVID big and small
Our docks - the ripped-down signs I noted yesterday have been replaced. Thanks to the harbor (and thanks to all for the interesting discussion).
Marin County - 62 new confirmed cases (32 are in 94901 San Rafael; 2 in Mill Valley, none new in Sausalito, Marin City, ...), no new hospitalization, but another death (the 4th this week). So much grief.
This brings the % of the county's population confirmed to have COVID to 0.96%. That's close to the state's average of 1.04% (409k cases).
USA - nationwide.
The heat map attached depicts the cumulative case count as a % of population for all 50 states. Highest - over 2% in dark blue ... New York, Louisiana, Arizona. Lowest - in faint yellow ... Hawaii, at ~0.01%.
Not in the map: Washington DC, 1.62%; Puerto Rico, 0.41%, Guam, 0.78%; US Virgin Islands, 0.29%
Sources: Marin HHS data accurate as of 22 July, NYtimes github repository for the 50 states, accurate as of 21 July. Various sources for population data.
Masked warriors
A longer version of the short Facebook post. Three parts:
Masks on the docks
Masks everywhere across the USA
The physics of masks
Masks on the docks
At the risk of sounding like a NextDoor whiner. I’m pissed. The docks are narrow; typically the total width of the passageway between flowers is 5 feet. Hard to keep 6 feet from strangers, then. And many of our residents have significant health risks: they’re elderly or have infirmities that put them at risk. Our oldest residents are well into their 90s.
So, it makes enormous sense that we have a mask-wearing and social-distance protocol. Actually: it’s now not significantly different from the statewide mandate. What makes me feel disheartened and betrayed is that the entire set of signs on Issaquah Dock calling for compliance - and reminding people that the docks are private property, and that we have immuno-compromised residents - have been ripped down. All the signs, both the official signs from the Harbor and the unofficial ones that residents added. All of them.
What bothers me is that some people are aggressively asserting that they won't wear masks in our confined space.
Not a surprise: the same people destroyed and removed the Black Lives Matters signs people had posted. From people’s flower boxes and from the closed poetry box in front of one home. Really! It’s as though there’s a set of people who will not do even the slightest thing to care for strangers.
Yes, there are people, even in bucolic Marin, who think that they can assert some imaginary right to put the health of others in danger.
Masks everywhere
Despite this, the otherwise good news on masks is that Marin County is, in general, a place of high adherence to mask-wearing protocols. The New York Times this week reported on a nationwide survey on mask-wearing intents. The survey got over a quarter of a million responses (and I’m imagining there’s a lot to be challenged in the survey’s methods, including that people often report their behaviors as better than they are, but that’s a different subject). 250,000+ responses are so many that you can zoom in to quite small localities. Here’s the national map. Few surprises, to be honest. (Texas looks stronger than I’d anticipated.)
Nifty! Now, you zoom in to Northern California, and can see that the Bay Area looks like it has good mask protocol compliance!
And further, into the dark-looking area of northern Sausalito, Richardson Bay / Marin City … wait, that looks great! The hover-over text suggests that 91% of people self-report as always wearing masks. And the algorithm predicts - as you can read - that there’s a 90% chance everyone will be wearing masks in five random encounters. That, unlike the hoodlums invading our docks, feels like the Sausalito dock residents I know and care for.
And now, because I’m a physicist by trade and training …
The physics of masks
The virus mostly is a respiratory pathogen. It exits the body of the infected person via droplets. Some are small and some are large. Since all these droplets emerge from the moist passages of the human carrier’s body, each of the droplets carries about the same density of virus per volume. The idea of similar concentrations means that droplets that are small as they leave the respiratory system carry far less virus. Large ones carry more. (This is an r^3 relationship, where r is the radius of the drop: the volume of the drop - and thus the number of viruses - rises as the third power of r.)
After exiting the mouth or nose, two things start happening. The droplets both start falling with gravity and evaporating in the air. The virus is believed to become concentrated as this evaporation occurs: it’s the water that’s leaving the droplet. (There's no evidence I know of that the viri themselves can propagate airborne without water.)
How they fall: Bigger ones fall faster (because their weight is again proportional to r^3, whereas the drag from the air that slows their descent is proportional to the area, an r^2 dependence); ones that start out small don’t call, but also don't carry enough viral load. The medium size ones stay airborne as aerosols - a diffuse mist of microdroplets with a higher viral concentration. These would not be as effectively blocked by cloth masks as larger ones.
How they evaporate: the evaporation rate is approximately proportional to surface area: r^2 dependency. It will also depend on temperature and humidity: higher temperatures and lower humidity cause faster evaporation. So the droplets that are smallest evaporate slowest but those that start out small have little viral content.
It seems there is some class of Goldilocks droplets by size that are large enough to carry a significant viral load and small enough to stay in the air for a long time.
Droplets that start out small may linger in the air but not carry enough viral load to be dangerous.
The medium size ones fall more slowly, but evaporate and some stay airborne as aerosols - a diffuse mist of microdroplets with a higher viral concentration. These would not be as effectively blocked by cloth masks as larger ones.
How they evaporate: the evaporation rate is approximately proportional to surface area: r^2 dependency. It will also depend on temperature and humidity: higher temperatures and lower humidity cause faster evaporation. So the droplets that are smallest evaporate slowest but, again, those that start out small have little viral content.
It seems there is some class of Goldilocks droplets by size that are large enough to carry a significant viral load and small enough to stay in the air for a long time.
Masks generally have a blocking mesh you can think of as effectively linear to r.
Conclusion from physics: the infected person absolutely should wear a mask, since it'd block nearly all the droplets and certainly an extremely high percentage of those carrying a significant viral load.
Since few people know if they're infected, all people should wear masks. People in constant contact with others of unknown status should wear N95 masks, since those are the only masks sufficient to protect against inhaling microdroplets.
Now let’s deal with the whiners.
You’ll hear some people arguing against cloth masks “because cloth masks are not basically useless”. This is incorrect. What they're good at: they prevent the infected person from spraying droplets. What they're not very good at: preventing an uninfected person from inhaling microdroplets (but they're still a lot better than nothing). Alas, due to government incompetence, we don't have enough N95 masks to go round, we have to ration them. And most people don't know if they're infected. So: cloth masks for everyone N95 masks for all at risk.
You’ll hear some people saying blood oxygen levels drop too low. Either they’re lying, or their lung function needs help. Surgeons and dentists and dental assistants and biolab techs and metal workers and dozens of other professions require mask wearing for hours. (I mean: can you imagine open-heart surgery and the whole team not masked?)
You’ll hear some people saying masks aren’t effective because you can still smell things. That’s nonsense. The smells (kitchen or toilet smells) are mostly tiny molecules: methane and hydrogen sulphide and things like that. These are unbelievably small: 0.13 nanometers for each arm of Hydrogen Sulfide; simple esters, like those in perfumes, are larger: benzyl octanoate is (I believe) less than 0.2 nm long. The Coronavirus itself is about 120 nm in diameter - 1,000 times larger. And it’s contagious vectors are microdroplets - typically 10 microns or larger in diameter - that’s vast.
Here are those numbers again, using the nanometer as a measure - 1 nm / one nanometer = one millionth of a millimeter
Hydrogen sulfide / rotten eggs small, also present in farts and overcooked cabbage: 0.13 nm
Esters used in perfume: 0.5 - 1nm (I used benzyl octanoate as my metric)
Coronavirus, naked (not in droplet): 120 nm
Aerosol droplet: 10 microns, 10,000 nm
Typical droplet as exhaled / expelled: 100 microns - 500 microns: 100,000 nm - 500,000 nm
Wear masks. All the time.
COVID how're we doing
Monday data is always the catch up for Marin HHS. Cumulative total as of last night is 2288, up 200 from Friday night. 10 newly hospitalized. 1 new death. 124 of the new cases were in San Rafael; two each in Belvedere and Tiburon; none in Sausalito, Marin City or Mill Valley.
So, how is Marin County doing, compared to the rest of the Bay Area? Let's look at the average number of cases over the past week. And then make that new cases per million people: Marin has just 258k people: only Napa (135k) among the Bay Area counties has fewer. Santa Clara has 1.8 million.
The graph: Marin doing quite a bit worse than other counties. Checking these: Marin has about 68 new cases / day, and a population of 251k, so it rates about 250 cases / day / million. San Francisco has about 126 cases per day. But SF has a population of 871k, so it has an effective rate of 155 cases / day per million.
Sources: Marin HHS, SFist (with their data for Marin 'corrected' to subtract San Quentin).
COVID climbing
(Originally posted to FB on 20th July 2020)
The numbers of new cases keep rising.
As of the last data from Marin HHS on Friday, the cumulative total for the county was 2,088 on 41,762 tested, a rise of 73 positive cases day over day, with one new death and two newly hospitalized.
This morning, it's showing 2,234, with two new hospitalized.
The geographic breakdown for the new numbers isn't available (nor is a revised number of tests). The table was current as of Friday evening. The case density for San Rafael of 1.8% - positive cases per population - breaks down into 2.4% in 94901 (south of the hill, including downtown and the canal district) and 0.9% in 94903 (north of the hill, the civic center, Terra Linda, San Pedro, Marinwood, etc.)
Details very much tbd but I'm guessing that the new numbers reflect the surge in tests and the backlog in results. Don't know.
I've excluded San Quentin for a few reasons. SQ is only reporting "active cases" which number is declining. Why is that number declining? Probably due to infected inmates being moved to a different location. Not clear. As of Friday pm that number was 1,118, down from over 1,400 a week ago.
COVID the heat
Yesterday in Marin: 106!!!! confirmed new cases of COVID. 916 new tests. No new hospitalizations or deaths.
Nifty heat map depicts confirmed case count as % of population for all 58 California counties. The outliers, high and low, make it rather weird. Here are some highlights:
* Dark red: Imperial county, bordering Mexico and Arizona - 4.5%!
* Dark blue: several northern counties - below 0.1% (Modoc in the north east, large in area, tiny in population, has no cases). Alpine County, south of Tahoe, has a 0.09% count ... but that is literally just one case.
* Los Angeles: 10 million people - the most populous county in the USA - 1.43%
* Marin County: 0.79%
Data sources: LA Times COVID github for the case counts, accurate as of 15th July; Marin HHS for Marin data (subtracting SQ), accurate as of 16th July; Wikipedia for county population.
COVID everywhere
Marin County: 940 test results; 53 positive; 3 newly hospitalized; 1 new death (in the county's general population).
SQ data - declining number of active cases, the website shows 11 deaths but this may be cumulative, it's not clear.
---
Everywhere. Yesterday, for reasons I note at the end, I was on a call with community activists from some poor places: the Eastern Cape, in South Africa; rural Maharashtra, India; two areas in Brazil; Myanmar. Some notes:
* In parts of South Africa, the government guidance to wash hands frequently is absurd - if a town has no running water or, perhaps worse, just one tap for hundreds of households.
* In rural India: schools have gone online. But the poor kids don't have devices, and their parents often went into debt to get them into the good schools and rural economies are collapsing because villages or towns are clustered into quarantine zones.
* In Brazil, big ISPs have cut off community networks so many poor communities have no access to the Internet, let alone relevant news.
* In more places than you'd imagine, the "holy men" advocate getting crowds together to pray.
---
Even for wealthier folks ... a close friend of mine here in California faces a dilemma. His father, in southern India, is in fading health - not COVID related. The dad cannot get decent health support unless the son shows up. There are occasional, overbooked, government-sanctioned evacuation flights from JFK to New Delhi. There's no obvious (healthy) way to get from New Delhi (a COVID hot spot) to Hyderabad.
---
Why I was on this call since I'm not a healthcare specialist or community activist? Later this month, I will be giving a short talk on a separate subject at a meeting at Internet Archive. The meeting mostly will feature live presentations from these people, if anyone's interested.
COVID in Marin ... ugh
Marin HHS reports 119 new cases from 10th July to 13th, on 1818 tested. No net increases in hospitalizations, but 5 deaths are recorded on the website!!
That means that COVID has taken 10 lives in the past two weeks in Marin County (this seems to exclude San Quentin inmates). Insofar as this is true - and MarinHHS has not updated its website properly for some days - Marin has about average ( = quite bad) cases / 100k residents, but only Imperial County is worse on fatalities.
The scatter plot here covers cases and fatalities from COVID over the past 14 days. All data from LATimes' COVID website except that I've had to manually intervene on the Marin data to exclude SQ and to insert the fatalities just recorded. The data depicted only cover the 20 or so counties with the highest case rates over the past two weeks.)
That means that COVID has taken 10 lives in the past two weeks in Marin County (this seems to exclude San Quentin inmates). Insofar as this is true - and MarinHHS has not updated its website properly for some days - the past 14 or so days have seen Marin County go from 1091 confirmed cases to 1808, a change of 717. This, on a population of 251k is 285 / 100k residents. And the 10 deaths take Marin to an effective 4 fatalities / 100k.
The vertical scale is logarithmic; horizontal is linear.
COVID big picture
The official state depiction of R(t) now has Marin county with R(t) of 0.91, which would suggest that growth would be easing. That's hard to square with the rapid rise in case counts in recent days.
Two places I rely on for R(t) at a state level give estimates of 1.09 and 1.17 - close enough to each other to align on steady spread.
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One oddity that many have observed is that many states - including California - have seen rapid rises in case counts but not in deaths. That has been attributed to lots of factors: younger new cases, time lags, and so on. But the most recent statewide picture indicates that the approximately exponential growth in cases continues - and fatalities are again climbing: 137 yesterday, and 151 the day before.
Marin HHS data doesn't quite add up (again) but ... 63 new cases yesterday, no new deaths.
The geographic breakdown suggests more new cases, including 3 in Sausalito. A big contribution to growth in the San Rafael contagion numbers in recent days has come from (yet another) nursing home - this time one off San Pedro road, which has recorded, gulp, 66 cases (49 residents and 17 staff) and three deaths in the past week.
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Sources: Statewide picture LATimes (statewide case counts and fatalities) calcat.covid.ca.gov (map and R(t) estimate for Marin), rt.live, covid19-projections. MarinIJ for the nursing home count. County data: Sources: Marin HHS except the SQ data, which is from SFist, MarinIJ.com for the data on the nursing home outbreak.