Per capita, many of the places hardest hit by COVID-19 aren’t urban, but rural (blue circles mark areas with at least 50 cases per day per million population, red circles those with at least 100):
Note the swath of cases crossing the “bible belt” and the many clusters in the corn belt; COVID has arrived in the heartland. But the fact remains that urban areas — especially very large ones — are tinder-boxes for the epidemic. I’d like to take a look at five of the biggest counties listed in the data available from Johns Hopkins University, namely: New York City (NYC), Dallas, Miami, Los Angeles (LA), and Seattle.
I’ve adjusted the data in two ways. Some counts (daily new cases per million population) are ridiculously low, because their cases were not reported until a later day. In addition, there is a distinct weekly cycle (especially recently) which is also due to irregularities in reporting practices. I’ve attempted to compensate for both factors, somewhat crudely perhaps (I’m exploring better ways to go about it).
Without further ado, here are the “adjusted” counts for these five major urban areas:
I don’t have expertise in this area, but my intuition is that when the case load gets as high as 50 new cases per day per million population, it strains the health care system. Health care workers suffer, overworked and stressed with many cut off from their families. Experts warn politicians that it has to be dealt with. When the case load consistently exceeds 100, the system begins to break down and the quality of care suffers. Warnings can no longer be ignored.
During early April, NYC consistently recorded about 600 cases per day per million population. They have suffered far more than any of these other urban areas.
We can also plot them on a logarithmic scale:
Now we can see that Seattle was the first to be hit, but was also the first to “bend the curve.” I attribute this to the wise administration and early preventive measures instituted by the Washington state government, under the leadership of governor Jay Inslee. In early March, Seattle was the “whipping boy” of COVID-19; today, it is the envy of urban areas which can only wish to get their case load that low. When the load is that much lower, there are sufficient resources to use tools like contact tracing to best effect. In other words, if you can get the case load low, you can keep it low.
By April 1st, NYC had taken the “lead” (to their peril) and Miami moved into 2nd place. Since then, cases have declined in Miami and dramatically in NYC, but in Dallas and LA they have hovered around the 50-100 level. I would rank all these cities’ performances as follows:
1st (meaning best): Seattle First hit but first to respond, lowest caseload today, still falling.
2nd: NYC Hardest hit, but responded strongly, and even though the caseload is only now dropping below 100, it is still dropping.
3rd: Miami They succeeded in escaping the over-100 danger zone, but they have slipped lately rather than continue decline (like NYC and Seattle).
4th: Dallas In early April they were well below 50, now they’re flirting with 100, and their long-term trend is still upward.
5th (meaning worst): LA They too show an upward long-term trend, and the caseload is going above 100, into the danger zone.
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Open Mind 
As far as I can judge from afar, California has quite strict rules to fight the pandemic. Still the new cases in California and LA do not go down. Any idea what the problem is? Are the rules not enforced? Does the tracking and tracing not work? Are people not supported enough so that they can stay at home as much as possible? Air conditioning?
At VV: I think you are seeing two things with LA: population density and underlying level of social activity.
It may also be true that LA and NY as international travel hubs have some particular vectors for infection that don’t exist in hubs with lower levels of transfer.
I am happy to be in WA State. Well done, Governor Inslee!
Good article on race and covid mortality rates looking at Chicago. Population density is one of the thing cited. I think the numbers are going to show that aside from the interesting patterns laid out in urban covid, there is going to be a clear pattern that emerges from deadly covid. I believe that primary pattern (aside from the age and ill health aggravators) will be poverty. That may look like class or race, but I think the real issue is poverty that forces folks into higher population density situations both at home and at work that greatly increase the risk of contracting covid in general and also increase the risk of a relatively large initial dose of covid. I think the large initial exposure carries greater risk of “cytokine storm” and simply overwhelm individuals beyond capacity of immune system to fight off the infection.
https://www.theguardian.com/world/2020/may/24/chicago-black-coronavirus-fatalities-us?utm_term=RWRpdG9yaWFsX0d1YXJkaWFuVG9kYXlVUy0yMDA1MjQ%3D&utm_source=esp&utm_medium=Email&CMP=GTUS_email&utm_campaign=GuardianTodayUS
Off topic, slightly. I’ve been tracking the authoritarian countries obviously underreporting deaths. [Many US red states who are doing this too.] Below, in no particular order – those near the top are obvious, and some near the bottom may not have the infrastructure to measure or treat their people. Notice that all the Arab states and all within Russia’s control are included. I suspect that nearly the entirety of foreign labor is being neglected and few are being counted.
Russia
Saudi Arabia
Chile
Turkey
India
Qatar
Belarus
Singapore
UAE
Indonesia
South Africa
Colombia
Egypt
Kuwait
Oman
Iran
Iraq
Colombia
Dominican Republic
Guatemala
Philippines
Peru
Bangladesh
Off topic: My condolences for the loss of your father. He was a great physicist, and I enjoyed the few interactions I had with him immensely.
Interesting. I’d noted the Saudi and Chilean cases–I just called their numbers “absurd” earlier this morning. But I hadn’t tried to be as systematic as you have.
How did you determine they are underreporting deaths?
Robert Rohde showed some data comparing reported numbers to excess deaths? Is that what you did? For the countries Robert looked at, the UK was the worst offender. https://twitter.com/RARohde/status/1264708175334440960
I don’t know how Susan made her determination, but I noted the Saudi, Chilean and Russian death tolls as being extremely disproportionate to cumulative caseload. And by “extremely disproportionate” I mean an order of magnitude.
Deaths/cases:
Russia: 1.1%
SA: 0.5%
Chile: 1.0%
Contrast:
US: 5.8%
Italy: 16%
China: 5.6%
Canada: 7.6%
Sweden: 11.9%
Turkey is on the bubble for me, at 2.8%–suspiciously low, but not quite so egregious as the others I mentioned. I haven’t examined the rest of Susan’s list. And I’d certainly have to concede that my only justification is subjective assessment of plausibility, so I’m not going to be all dogmatic about the conclusion. But it’s just darn hard to believe that with ~45k recovered cases in Saudi, only 399 cases had mortal outcomes instead.
Clearly a better ratio to run, though, would be deaths/resolved cases–it’s just that cumulative caseload is such a conventional ‘top line’ number. (Well, that and an extra step in processing the data.) But rapid ‘increasers’ will always look a little better by the cumulative caseload comparison because deaths lag infections. Using only resolved cases would account for that.
There is a lot of number fudging going on with the covid virus. One of the least “fudgable” numbers is the excess death number. That is really only available in the developed world that tracks death numbers in a comprehensive manner. That number has wiggle room because it includes non-covid infected deaths that occur because people deferred care out of fear of covid. That variable would run the number up. It also includes fewer traffic deaths that arise as a result of the covid-related reduction of travel miles. All in all, it probably washes out and the excess death number is probably sufficiently accurate for big number epidemiological purposes. There are turning out to be a lot of variables that are apparently modifying the mortality rate of covid around the world, so even if we have a good handle on excess death numbers and use that as a close ballpark figure for covid deaths, we can’t run a straight line from that number to the number of infections, we can only run that out to a ballpark number.
One of the ways that Covid 19 is like AGW is that we will have a much better idea of how it works looking back after big events have happened, than we will at looking forward and trying to understand and estimate accurately when big events might happen. Covid is a profound lesson about why we might want to factor in low probability, high impact events when determining public policy. But even if we take those events into account and develop good public policy, we can’t keep folks from doing the wrong/stupid thing – like buying into high emission lifestyles and taking part in dangerous events and gatherings that will spread a pathogen. I file that in the “you can’t fix stupid” section of the filing cabinet.
Doc Snow
Please have a closer look at the data; you’ll find some more suspects in puncto death toll rate (column 4; column 5 is death toll per mio):
QA 42213 21 0 8
SG 31068 23 0 4
AE 28704 244 1 25
BD 32078 452 1 3
BY 35244 194 1 20
CL 65393 673 1 36
KW 20464 148 1 36
RU 335882 3388 1 23
SA 70161 379 1 11
IL 16690 279 2 31
KR 11190 266 2 5
PK 54601 1133 2 5
RS 11092 238 2 34
ZA 21343 407 2 7
I could ask you: how is it possible that Singapore (SG) reported until now 23 deaths for 31068 cases? In such a giant town?
Chile is at 1%, Korea, Israel at 2 %, etc etc.
I’m not sure that this is the right data for such assumptions.
J.-P. D.
bindidion, yes, I find the example of Singapore quite as suspicious as you do. Etc., etc., with the others. I’m not sure what you mean by “assumptions,” as I’ve drawn no conclusions as to why this or that value might be biased low (if it is, in fact, biased).
My response to VV went missing; I hope this is not a duplicate:
VV – California is a huge varied state. This gives you the C19 demographics, but the current reports on a weekend are unreliable. Usually by Tuesday you can see the trend.
https://www.worldometers.info/coronavirus/usa/california/
There are so many variables. The “elites” who can afford to are protecting themselves and each other, but they are served by a population that is far less privileged. Then there are the migrant workers who do our food, and their conditions can be appalling, especially aided by Trumplicans with their otherblaming immigrant bashing.
Today’s horror, fresh on my radar, is that NBC (primetime network TV) has given Joel Osteen a noonday sermon slot, and before I could turn it off he was talking about plague, punishment, and New York City. He’s an oily profiteering hypocritical megachurch guy, whose specialty is the “prosperity gospel” (wealth is god’s gift, poverty god’s punishment, if you give the “church” money that can be fixed). If we have to have mainstream TV Sunday services, they could find some lovely tolerant guy or gal to preach about compassion and caring for each other. This is truly horrible; NBC should know better. It’s not “fair and balanced”. But I digress.
It’s all too easy to blame cities, especially crowded international hubs, for being caught by necessity. Chicago is not doing well. But California is the world’s 6th largest economy, and it’s not all progressive, not even close.
And the tech industry has made housing unaffordable even for the middle class.
So crowding, underprivileged, unserviced, all the sins of the greed is good and devil take the hindmost policies since Reagan, hurt their victims while blaming them. It is devastating to watch the daily degradation and know that there are still 100 days of hours to the election, and two more months after that until Congress changes over (we have to assume, a Democratic takeover of the Senate, which will remove many collaborators) and still 17 more days before a new president. I’m not fond of Biden, but he will not be bad and he is leaning progressive these days. Here’s hoping (the alternative is unthinkable). Of course, R’s are already funding intimidation at polling places, and we’re all to like to have heavily armed protests afterwards. Arms sales are through the roof, again. Every crisis, the profiteers and true believers add to their armories.
You make an interesting point about how many of the hard-hit areas are not urban. I was talking with a friend the other week who lives in Shippensburg, PA who says that the COVID rate per capita is quite high.
I think a lot of the second wave infections will show up in rural areas. That will be felt like first wave was felt in the early hot spots like Seattle and NY. Might be a little less scary than the first wave. It should be relatively to easy for communities to flatten the curve in second wave because we all know what worked from first wave.
It’s too bad we have to go through this and learn these hard lessons and let go of family, friends and loved ones, but it’s also quite wonderful to be alive and have the opportunity to experience our own mortality. This stuff goes a bit like wildfire in care facilities, jails and prisons. That is hard to watch.
Here in South Carolina, we’ve been a little luckier than many of our neighboring states, though with over 10k cases now, we certainly aren’t untouched. And Governor McMaster, though a Trumpist, is a tad more moderate than most such. (IMO, at least–and that doesn’t excuse his adamant refusal to expand Medicaid from being a maleficent one, even if not malevolent.)
But it’s noticeable that the hardest-hit counties on a per capita basis are all relatively rural. (Though, to be fair, so are the least-affected ones.) Urban counties are in the middle, more or less. If you look at the map from DHEC, there’s a big ‘blob’ of semi-rural counties east of the capital, Columbia (Richland county).
And while I think it would fail formal significance testing, it sure looks to me as though we’re seeing a rise in new cases since our ‘reopening’ three weeks or so back. It may be partly coincidence; you wouldn’t expect an immediate response, since it takes time to be exposed, develop an infection and finally get diagnosed. But it doesn’t give much credence to any sort of “wave” framing, nor of a strong seasonal effect (about which, I remain pretty skeptical).
https://www.scdhec.gov/infectious-diseases/viruses/coronavirus-disease-2019-covid-19/sc-testing-data-projections-covid-19
You could be right in the end. But we’ll see. I hope that the second wave will be easier than the first, because the first has been tough.
We have hopefully learned how to live with the virus and may have better treatments, but in principle, the second wave is expected to be worse than the first one.
The first one was mostly local outbreaks. The second wave will start with virus activity everywhere. The number of cases can thus rise much faster and overburdened areas should not expect help from elsewhere. This is what happened with the Spanish/Kansas flu. https://variable-variability.blogspot.com/2020/04/corona-virus-update-german-situation.html
I hope we are smarter this time and better prepared, will monitor closely and pump the breaks fast, but when it comes to America what happens in Washington DC does not give me much hope. Fortunately this is a state issue.
Victor Venema
” I hope we are smarter this time and better prepared, will monitor closely and pump the breaks fast, but when it comes to America what happens in Washington DC does not give me much hope. ”
You are certainly right, but when I look at what happened this Monday on GB’s beaches (snapshot out of the German newspaper ‘Frankfurter Rundschau’), I get hopeless right now.
J.-P. D.
Oops, snapshot forgotten:
https://drive.google.com/file/d/1Y7Wh0I7SUKuenqaWbu0cPPIiBA0u911Q/view
By now, I’ve seen dozens of photos like this beach photo. Every single one has been presented simply as “look what people are doing, how horrible” without any statement of what exactly they’re doing wrong. Every single one has been taken with a telephoto lens with a very narrow field of view, giving the optical illusion that everybody is crowded together when they’re not.
In this photo, I can only find one apparent instance of more than one household clustered together without recommended distancing, in the center foreground (group with purple shorts man, group with orange top woman). Every other apparent family group seems well over 6′ from every other group, with an average distance to nearest neighbor of perhaps 10′.
NB: This is only a flame against telephoto shots of beaches.
John,
While I agree that not every person is ignoring the 2-meter rule, there is more to social distancing than this rule. According to some research, spending 15 minutes 2 meters away from an infected carries the same risk as spending one minute one meter away. It occurs to me that COVID safety is not unlike radiation exposure–you need to consider distance, time and shielding (e.g. masks, partitions…). We need to remember that it’s the Corona virus’s world right now, and we need to be careful if we want to keep living in it.
S –
Yes, those nuances are important, as is the difference in risks between indoor exposure (confined space, oftentimes poor air circulation) and outdoor exposure (excellent ventilation, some UV radiation).
Given all the variables, I expect that the pictured beach is at least a hundred times safer than a college bar, even with 6′ distancing (lots of unrelated people nearby, loud music and hence loud talking generating massively more aerosols, long air residence time). OTOH, I’ve been to a few British pubs that would be quite safe under the circumstances as long as there’s no football or cricket on that day.
It is hard to judge based on a photo, but I am not convinced that this is a problem. Outside the 2 meter rule should work well. Inside also larger distances can be a problem especially when spending more time there.
As long as people behave sensibly going out is a good thing.
Actually, I think the density of hosts matters over and above the 1 per 2 meters. I don’t think you can equate a few people 2 meters apart with a stadium of people 2 meters apart watching a football match for 4 hours.
Does anyone really know how these variables interact? I’m guessing not yet.
On the bright side, apparently there are going to be lots of “experiments” to provide data for analytic study.
The Johns-Hoplins-University leaderboard of Covid-19 infections looks very much a leaderboard of the nations with the most populistic presidents. And the USA is first. Exactly like Mr.Trump promised you.
With the nation misgoverned by his acolyte, Jair Bolsonaro, coming up rapidly.
And their benefactor–a man whose very name is synonymous with flatulence–Putin’.
Singapore low death rate is easily explained by demographics of infections. Infections are mostly among foreign workers in dormitories, where it is much more difficult to limit contacts. These workers are much younger that local population. Since mortality doubles every 6.5 years, then no wonder that the overall mortality is very low. When limited to the locals, where demographics of infections generally is in line with demographics, the death rate is similar to other countries.
I have now tried to post four times to respond to VV and the posts are disappearing. Sorry, VV, I give up, except try this site and sort by cases and look at the deaths column.
https://www.worldometers.info/coronavirus/#countries
I have seen your reply. Just not below my comment, but as an independent comment. Thanks.
VV, no. These were further attempts. (Though the one you saw was an earlier repost of one that went missing so I can see why you thought that.) Three have completely disappeared. They were responses to your reply to my reply asking me if I had done any actual analysis on the discrepancy to which the answer is no. I do, however, stand by my opinion about the correspondence between known autocracies and the visible inconsistencies between cases and deaths reported, both in the US and abroad.
Susan, okay, I was just being a scientist in asking for how it was computed. Especially if you look at current virus activity it is very clear that authoritarian countries (except for China) do much worse than more democratic countries.
If you look at total number of infections or deaths also some more democratic countries did poorly as they did not prepare, notice or respond fast enough. But these countries took action to protect their citizens.
There should be some sort of index for how authoritarian a government is. Would be interesting to correlated that to current SARS activity. (Where possible corrected for the under-reporting of infection and deaths by looking at the excess deaths.)
Thanks VV. I think I’ve figured out how to get my posts to not disappear. It’s interesting that Massachusetts has now had a jump in cases due to reporting. I attach the note in full because I think it is informative and I’m pleased to come from a state that is willing to be honest. The truth may be difficult, but it matters; and I think this explains better why it’s all too easy for those who don’t like the numbers to fudge.
5 efforts to reply to VV and ask what’s wrong have now been trashed. Definitely giving up here, sorry.