It will be ugly no matter who gets elected. I think w should all expect the election results to be challenged. Should the occupant of the White House lose on all counts and be ousted (peacefully or by force) expect his base to be energized and potentially violent. If the other candidate loses expect his base to be energized and potentially violent. The U.S. (and the rest of the world for that matter) is and has been, in a transitional phase where it’s being asked to examine the pillars upon which it was founded. Expect some major pivots and change of directions over the next 3-5 years during which old structures and institutions will be destroyed or reenvisioned. And since this is a food forum and not a political one, I’ll stop here
San Diego’s CV-19 test results topped 7% over the weekend, pretty sure we’ll see some sort of reaction from the City/County today.
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Interesting paper today in Lancet about the biggest seroprevalence study in Spain (which showed just 5%) One of the key findings against those who argue we will once get to herd immunity also naturally without a vaccine - “In light of these findings, any proposed approach to achieve herd immunity through natural infection is not only highly unethical, but also unachievable…”. Which also makes the Swedish approach even less likely to succeed and points to the many unnecessary deaths in that country.
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31482-3/fulltext
This is a worthy article. But is there any country that actually hasn’t imposed any restrictions/controls whatsoever and is relying totally on natural infection to build herd immunity? Without making an ethical judgement, as a scientist myself and an interested observer, I only note that the data for Sweden (which has numerous restrictions, actually) have shown a steady drop in the 7-day moving average of covid deaths, dropping from a peak of 99 on April 16, to only 4 on July 5. The 3-day running average is even more dramatic, declining from a peak of 106 on April 23 to just 2 on July 5. I’m making an observation, not a judgement, and I think these data are very interesting and germane. I’ve been following the situation in Sweden because its approach is the most radical departure from what other countries have done. I’ve been following the situation in the US because we don’t have a unified approach at all and states are flagging in the wind, basically “do it yourself”. And I live here. And I’ve been following the data in San Diego County because, well, for the same reason.
No, because it would be mass murder and the government would go to jail. (and I don’t mean this comment as a joke but hundreds of thousands of unnecessary deaths in your country would be mass murder)
So we agree on that.
Please look at Fig. 1 & 2 in the Science article I posted July 4, near the end. It would be of interest to see this model re-run with a higher value of R0 (in view of Robert’s comments) and with an earlier date of lifting restrictions (maybe June 15 or so instead of June 30). In any case, for the value of the R0 chosen by the authors (2.5) and a lifting date of June 30, they show four results. The case with no restrictions is moot because as we agree, no country has done that. Perhaps Sweden falls in the “mild” category and S. Korea in the “moderate” category? But the worst case is that with “strict” restrictions. That is the only case that has a true second “wave”, and in the example, the second wave is equally as bad as the first. I’ll speculate that with an earlier lifting of restrictions (earlier than June 30 used in the example), the second wave would be substantially higher than the first.
My point here is that while the model in Science isn’t any more perfect than others – as all involve assumptions – it does show the general effect on case load of the degree of severity of restrictions when followed by sudden lifting, and that “severe” can be worse than “moderate”. Note also that “moderate” is the best, but also the only one that is continuing to rise at the end of the calculated period, howbeit very slowly. I think that may be what’s going on in S. Korea.
Also, the model can hardly be applied to the US given the mishmash of restrictions state to state.
Yes, this new “full stop” with three weeks of downtime will probably choke out the last breath of many more of our already struggling restaurants and bars. And for those that do survive, the equally abrupt “full start” that will follow will once again lead to instability – both economically and health-wise. And on and on.
When will they ever learn?
I don’t really think it’s a case of “learning”. I think it’s really a case of needing a vaccine.
We’re in a massive transition phase of all our social, cultural and economic structures and institutions. We’d be naive to think it wouldn’t also involve restaurants and how food - our lifeline - is delivered. Perhaps we just didn’t expect them to be on the leading edge 
I think our elected officials (State and Local) are having to make some tough decisions in order to keep we the people a safe as possible. I don’t thinking they’re taking great pleasure in shutting businesses down. It hurts everyone, and I think they know that.
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Thanks for your reply. I agree that our elected officials are between a rock and a hard place. I wouldn’t want to be one of them – or one of their advisors.
I just don’t think that an On/Off switch coupled with long gaps is the best way to control, and that “They” haven’t come even close to learning what’s better than that yet.
Yes of course, we need a vaccine and/or highly effective treatments. But those may be months (unlikely) or years (more likely) away. So, how to prevent deaths until then, while at the same time causing less havoc, in particular (per this forum) in the restaurant sector?
Perfect control, zero deaths for the indefinite future, is an impossible dream no matter what we do; some will always die every year from colds, flu, pneumonia, and now covid-19. But IMO the goal of very few deaths can be approached more closely and more quickly with “softer” (i.e., more sensitive detection and less jarring changes) control than the simple On/Off/Gap/On/Off/Gap… ad infinitum approach that’s been implemented in CA.
The reality is that we’re in a sort of Twilight Zone where most of the variables are unkown and we’re all finding that extremely hard to deal with. We’re creatures of habit, we want (need?) a certain amount of security and stability in our lives. At this particularly time, that security and stability is MIA.
We are, aparently, “living in intersting times” 
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I think all the data in different countries so far points to on/off as a better option to try to get corona contained. I don’t see much data that supports your approach as having potentially less deadly - in even without data, just by looking at both approaches I strongly favor an on/off approach
You’re right, I’m stating an opinion with some conviction, but have neither data nor model results as backup. My opinion is based solely on reflections of a single, one-semester course I took decades ago as an undergraduate called Stability and Control, in the aerospace engineering context. I recall that it was both esoteric mathematically and fascinating, the latter to the extent that at the time I wished that perhaps I had gone down that path of specialization. I don’t remember a damn thing except that the objective of feedback control is to achieve stability, based on features in the time variation of the process variable needing control. There are numerous textbooks on the subject and no shortage of specialists.
What I would like to see is engineering-level feedback control integrated into one of the mathematical models for covid spread and deaths. On the CDC website, there are 24 national “forecasts” (models, link below) used to predict future covid deaths in the US. From the (very) brief descriptions of each, I don’t see any that clearly incorporate mathematically rigorous feedback controls.
https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecasting-us.html
Of course, On/Off switching as it’s being implemented is a form of feedback control, but a very clunky one, in my opinion, and as such I suspect it’s not achieving the optimal desired dual results of stabilizing test positivity and minimizing deaths. In my opinion On/Off (hard stop, full start, hard stop, etc.) control can probably easily be bested by even relatively simple engineering-level feedback control, in terms of deaths.
If there is a model of the kind I’m describing out there, I’d be very interested in being pointed to it. The assumption of uniform application nationally of the control would have to have been made, and even though it’s ludicrous to expect that uniform application across states would happen right now, it would still be of interest. But the same model could be applied at the individual state level, CA in particular, and that would be of considerable interest.
By the way, I acknowledge and understand your opinion, and in no way should mine be taken as personal criticism.
Yes, we sure are.
To recap, though, and put some things in perspective, one can look at the plots in the SD Union Local Section of the rolling 14-day average of positive tests (“positivity rate”).
That number was dropping rapidly until May 20, when restaurants were abruptly allowed to fully open, howbeit with lots and lots of rules. Shortly thereafter, the positivity rate stopped dropping. It leveled off at 3%, where it remained for about two weeks, which appeared to be stable at least. Bars were then abruptly allowed to fully reopen (also subject to many rules) on June 12.
On June 19, the positivity rate briefly dropped to 2.5%. Unfortunately, after that encouraging minimum, the positivity rate began to rapidly and steadily go up. Bars were abruptly closed on June 29. The positivity rate continued to climb. Restaurants were abruptly closed on July 6. The positivity rate is now around 6%.
If the State and/or County gets a headache when thinking about employing a stability and control expert, here’s a simple modification to the existing On/Off approach:
Three days after the June 19 minimum in the rolling 14-day average positivity rate, on June 22, it was clearly rising rapidly. In my view that’s when a correction should have been exercised. Not waiting for 10 to 17 days.
But the correction wouldn’t have been the abrupt and complete closure of bars and then restaurants. It would have been a scale-back of some sort of both, on June 22, such as reducing the number of opening days; “dimmer switch” control, if you will, as opposed to On/Off. If the initial scale-back worked, the correction would be held until the positivity rate was leveling off again or declining. If not, there would be further incremental scale-back. If so, the opening days could be incrementally notched back up. And so on.
I don’t really understand why you think any kind of “feedback control” should be part of the calculation for viral spread. I had, job-related, a number of meetings where well known epidemiologists and virologists explained their models and their theories how to counter the epidemic (from a practical and theoretical standpoint) and none of them had any thoughts on feedback control. No offense, but just because you had a few lectures in feedback control for stability in engineering some years ago doesn’t mean that the same concept has any/significant value in the world of epidemiology.
But On/Off is feedback control, Honk.
I just think it would be worth looking into something more refined.
But if it didn’t work initially and you need to continue scaling more back you will have killed many additional, completely unnecessary people during this time (and it will take about 2-3 weeks to see effects in hospitalization rates (which is (beside death rate))a key indicator of success and to a much kesser extend the positive test rate). We can’t afford to kill potentially more people if we can avoid it with a complete closure.
Our objectives overlap: Reduce deaths to the absolute minimum. Zero for all time is impossible, but a very tiny fraction is. We’re talking about the best way to get there.
That is not my definition of feedback control - something like fuzzy logic control is a feedback control you are talking about
I say bring in the experts in feedback control and let them weigh in on this. That’s all. My opinion is that it does have value in the area of epidemiology. And I’m a little surprised that no one has even talked about it in your meetings, because feedback control is being used now.
There are people talking about it in such meetings but they don’t see great value in it in the current situation. In addition, with so many easy unforced errors already made in controlling the pandemic, adding such “fuzzy logic” approach would be way too risky and unknown to kill even more people - until now you still haven’t explained how you want to avoid even a single unnecessary death with your approach when you even admit that it might be necessary to further “notch up or down” during the process. Wouldn’t you agree that this would be too risky already ?
I think that we’ve waited way too long to exert control, and that by the time we’ve taken action, there have been far too many new infections. “Notching down” wouldn’t exclude complete closures over the same (long) time period that “full open” was allowed. It would start reducing opening days much earlier, thereby reducing transmission earlier and saving lives that were lost due to the long delay before a sudden “full stop”. Re-opening would be similarly ramped upwards a notch at a time, based on feedback. “Full open” would be a goal. Just not instantaneous either way. So I see it as less risky, not more.