2019 NCOV a.k.a. Wuhan's Diseases

SpaceNut · 2020-05-09 18:03:53

GW Johnson wrote:

The true problem is now that there is no public money left to do this. Everything (and then some) has gone into fighting the economic devastation caused by the pandemic.
But, perhaps there is an "out". Hire some of the unemployed to work on the storage solution (among other things), as a CCC-like approach to addressing pandemic-generated unemployment. It worked very well in the 1930's. Why not now?
GW

Not all states are taking the virus in the same manner when it comes to the closing and furloughing of its people. You can’t get unemployment insurance if you’ve been deemed “essential.”

employees who decline to return to work won’t be eligible for unemployment benefits, even if they’re concerned about contracting the coronavirus. It’s a “voluntary quit,”

NH has taken a safe stance for now but that may change.

SpaceNut · 2020-05-09 20:09:25

We have heard of the isolation success of a few nations but not much is said about The people waiting out Covid-19 in dark, frozen Antarctica

While the rest of the world continues to grapple with the coronavirus pandemic, one continent has managed to remain entirely free of the infection.

SpaceNut · 2020-05-10 10:34:33

Had to go to the local Walmart and noticed many shelves were empty. Containers to store items in, Bicycles, and limits on meats....Pork Chops vs. People: Battling Coronavirus in an Iowa Meat Plant

Of course costs are on the rise for some items and with not working, being not on the receiving list of economic help its become clear that ‘When they see us, they see hope’: Distributing food aid under the lockdown

GW Johnson · 2020-05-10 12:29:35

The supply disruptions coming from infection events in some meat packing plants are real. Complicated by hoarding, perhaps, but real.

Those infection events are in some meat-packing plants, but not all. Some provided infection protections to their workers at one or another level, others did little or nothing. This pretty much reflects the management's valuation of its workers. Some use wage slaves, others have valued employees.

It's that simple. And in some cases, it's that ugly.

GW

Last edited by GW Johnson (2020-05-10 12:30:07)

SpaceNut · 2020-05-10 17:38:49

Look out here it comes again... Wuhan reports first new coronavirus case in more than a month

so where is the contact tracing?
Sort of means that 14 days is a laugh for lock downs....

While serving others A nurse without an N95 mask raced in to treat a 'code blue' patient. She died 14 days later

According to those news conferences there is no shortage of supplies...

state by state news

Symptoms of covid-19 appear to include:

Brain: Strokes from blood clots, neurological issues

Eyes: Pinkeye

Nose: Loss of smell and taste (anosmia)

Blood: Unexpected blood clotting; attacks the lining of blood vessels

Gastrointestinal system: Vomiting and diarrhea in some people

Lungs: Clogs and inflames alveoli (air sacs), hampering breathing; pulmonary embolism from breakaway blood clots and microclots

Heart: Weakens heart muscle; causes dangerous arrhythmias and heart attacks due to small clots

Kidneys: Damage to structures that filter waste from blood; patients often require dialysis

Skin: “Covid toes,” or fingers, a purple rash from the attack on blood vessels

Immune system: Widespread impact, including overactive immune response that attacks healthy tissue

kbd512 · 2020-05-10 18:19:20

GW,

Quantity is important for keeping costs manageable, but quality doesn't seem to count for much in the minds of the average consumer. They'll tell you they want it, but they don't want to pay for it. When you buy the cheapest product the market offers, expect the least desirable long-term results.

Terraformer · 2020-05-11 02:40:23

Crowds and air conditioning. That seems to be where it thrives - places such as nightclubs, where R > 40. Restaurants, offices, protests etc. Which means these blanket lockdowns are ridiculous, and yet may not go far enough (supermarkets are far more dangerous than most shops).

It's a truly pernicious virus. My aunt (nurse) got it, and had coughing and lost her sense of smell. My cousin got it and had a headache. My other cousin got it (presumably - the house was full of the virus, he couldn't have avoided it) and had no symptoms at all. My (diabetic) uncle got it, and was nearly placed on a ventilator (he's back home now). One house, four different manifestations, ranging from asymptomatic to almost fatal.

EDIT: Twitter thread on transmission risk. Close and sustained contact. Offices, rallies, churches. Not book stores or canal paths. The question is, if people meet in small groups, is that enough to drive R above 1? There will be some fraction of time that people can spend in a group n whilst keeping R < 1, and we need to know how much it is.

Last edited by Terraformer (2020-05-11 02:46:43)

RobertDyck · 2020-05-11 09:02:50

I see the chart I posted in post #298 page 12 is auto-updating. The image comes from the Winnipeg Free Press, so that means they're updating the image on their website rather than posting a new one every day. Ok. We're doing pretty well. Only 7 people in this province have died. Some new cases, currently 33 active cases. April 5/6/7 we had close to 200 active cases. Only 4 individuals currently in hospital with COVID19, including one in ICU.

Of course our province a population of 1,377,517 according to the March quarterly estimate by Statistics Canada. Of that the Winnipeg "economic area" has 708,823 as of the 2016 census. That includes "bedroom" communities surrounding the city. So most people live in the city. Brandon is the second largest city in the province with 58,003; it's a 2.5 hour drive away at highway speed. The nearest large city (greater than 200,000 people) is Minneapolis MN, which is an 8 hour drive each way...at highway speed. The nearest large city within Canada is Calgary, a 14 hour drive. So we're pretty isolated. Big beautiful city in the middle of nowhere... um, middle of the continent.

First of this month the province said restaurants could open their outdoor patio seating, but nothing indoors. And those outdoor tables must maintain the 6-foot spacing, so effectively every other table must still remain closed. It's still pretty cold here. We had a couple nice days, but this weekend the daytime high was +8°C (46°F), overnight low -5°C (23°F). Right now it's +1°C (33.8°F). So don't expect a lot of business at those outdoor patios.

Hardware stores can now open. Yea! The power line from my house to garage snapped last winter, so I can buy stuff to fix it. Thinking of burying the cable so a tree can't snap it. Ground is thawed, but still want warmer weather. So this Thursday or later.

We're just barely starting to re-open the economy. Premier of this province said if the virus doesn't come back, he'll allow restaurants to open beginning of June. But still no major events like sports. First two weeks of August is normally Folklorama, the largest multicultural festival in the world. That's cancelled this year. Keycon is a science fiction convention, about 600 people held the May long weekend every year since 1984; it's cancelled. I gave a talk about real space activities (NASA, CSA, ESA, etc) every year since 2002, so this affects me. Local Comic Con was held the Halloween weekend with 20,000 people attending, it was cancelled last year. A new Comic Con convention booked the same space for the same weekend this year. Ok, that tells us why they previous convention couldn't book the space. But will a major event like that be allowed by that time?

Talking heads on TV news are citing unemployment numbers. This weekend they were saying numbers look like a depression. Not recession, they said depression. Some optimists are hoping for a "V" recovery, which means a recovery just as rapid as the shutdown was. Most observers say that's not going to happen. The Small Business Association of Canada said if the economy had not started to open the beginning of this month, most small businesses would fold/close/ permanently out of business. Some people think it's too early to open the economy, but in reality this is the latest it could have been delayed. Those businesses re-opening this month are already having difficulty getting their employees back.

tahanson43206 · 2020-05-11 09:54:04

For RobertDyck re #333

Thank you for your detailed review of the situation in Winnipeg and the region around you.

Your closing paragraph, about re-opening the economy, inspired me to offer a (hopefully brief) report about my first experience of telemedicine. My annual physical was on the calendar for today, but this year I received text messages, telephone answering machine messages and email, all informing me that the activity would be carried out online.

My overall evaluation is that the procedure went reasonably well. I liked the instantaneous transport << grin >>.

The doctor wore a headset, which makes sense to me. The technology worked well. It was a locally brewed system, not Skype or Zoom or anything I'd heard of before. It only works with Microsoft, which I suppose makes sense considering the market penetration.

I asked the doctor how things were going at her practice, and she said that they've been busy and no one is sick there, and I count that as an example of success when success is needed. She still takes on-premise visits when necessary, but keeps them at a minimum. I learned that when I drive over to pick up some tests tomorrow, I'm to call the office from the parking lot and they will bring it out.

This leads me to a point I've made before in the forum, perhaps in other topics.

A time of disruption like this is the exact right time to introduce new ways of doing things.

The meat packing plants, and ANY manufacturing facility for that matter, needs to be re-designed so that people who perform duties today are protected from airborne biological dangers, as well as surface borne ones such as you have pointed out.

The ** best ** way to do that is using teleoperation, and now is a good time for a high-energy push to develop those from the early stage they are in to an all-economy mode for the future.

(th)

louis · 2020-05-11 11:58:02

It is highly infectious. Despite the "lockdown" we still have about 11 million people travelling to work and then mixing at home with maybe another 15 million people at least at home. That's the equivalent of probably something like a country the size of Canada...all circulating in the UK. The people are also going into the same shops and supermarkets as those of us on lockdown.

This is why I think the so-called lockdown can have only a marginal effect over and above sensible measures, as deployed in Sweden. Obviously you don't have football matches, huge sporting events, theatres, clubs etc continuing. But you don't need a lockdown to introduce sensible measures.

What the lockdown does do for certain is create a climate of fear, dissuade people with serious health conditions seeking medical advice and destroy your economy. It is probably the worst public policy ever pursued in the UK.

Terraformer wrote:

Crowds and air conditioning. That seems to be where it thrives - places such as nightclubs, where R > 40. Restaurants, offices, protests etc. Which means these blanket lockdowns are ridiculous, and yet may not go far enough (supermarkets are far more dangerous than most shops).
It's a truly pernicious virus. My aunt (nurse) got it, and had coughing and lost her sense of smell. My cousin got it and had a headache. My other cousin got it (presumably - the house was full of the virus, he couldn't have avoided it) and had no symptoms at all. My (diabetic) uncle got it, and was nearly placed on a ventilator (he's back home now). One house, four different manifestations, ranging from asymptomatic to almost fatal.
EDIT: Twitter thread on transmission risk. Close and sustained contact. Offices, rallies, churches. Not book stores or canal paths. The question is, if people meet in small groups, is that enough to drive R above 1? There will be some fraction of time that people can spend in a group n whilst keeping R < 1, and we need to know how much it is.

SpaceNut · 2020-05-11 17:43:29

President Trump Using Executive Order For Meat Plants issues just 2 weeks ago. The costs of going back to work....
At least 4,500 Tyson workers have caught COVID-19, with 18 dying. The meat giant still doesn't offer paid sick leave, as the industry blames workers for outbreaks.

Tyson previously highlighted its new steps taken to protect workers, including taking employees' temperatures, requiring workers to wear facemasks, additional daily deep cleaning, and installing workstation dividers. Cases span meat processing plants in 15 states, according to data from state and local governments, the Midwest Center for Investigative Reporting, The Counter, and local news publications.

Meat shortages could last another month, says president of local meat packing company

kbd512 · 2020-05-11 18:49:47

SpaceNut,

In general terms, food processing is an essential part of feeding 400 million people. Since 100% automated farm-to-dinner-plate food factories have yet to materialize, meat packing plants and grain mills need to remain open, despite the risks. If the people who went to work with COVID-19 were asymptomatic, then there's very little that paid sick leave would've done to prevent the spread of an influenza-like virus. Incidentally, Tyson Foods does offer paid time off to their employees.

Tyson Foods Employee Benefits:

Tyson Foods Employee Benefits Review: Are Their Careers Worth It?

SpaceNut · 2020-05-11 19:12:28

The term paid time off is vacation or annual based on service years but there are many a company that do not offer any sort of benefits.

I agree that food and processing are essential but with safe guards to all.

Its been over a month since we did find out that some could have no symptoms of the disease and with that in mind, test, screening are essential for all but in harms way as being essential employees. We have known that mask are the best defense for those asymptomatic as the droplets do not get to carry from the infected quite so easily. So why are these not mandatory.

Void · 2020-05-11 22:19:36

I ran across this tonight, thought I would place it here.

Quite a bit of it is over my head, but with effort, I kind of understand some of it. It appears to offer encouragement for the implementation of herd immunity. It seems to indicate that even when a small subset of the population has been infected and recovered, (Or died), the spread slows down. At least I thought it said so.

In another place I read that no-one in Sweden has gotten the disease twice yet, according to their statistics. Apparently they are keeping good records.

If any of this is true, then it is encouraging, we sure could use good news. If it is rather true, then the people who get sick at meat packing plants should have maybe 6 months of immunity. But no one knows at this time. So, if they get an early vaccine maybe most people will get it once or not at all. Of course if it drags out to 18 months before a vaccine, then many people will have to suffer from it, and perhaps more than once.

This link also has charts, graphs. Of course I could not copy them.
https://judithcurry.com/2020/05/10/why- … n-thought/
Quote:

Why herd immunity to COVID-19 is reached much earlier than thought
Posted on May 10, 2020 by niclewis | 156 Comments
By Nic Lewis
Introduction
A study published in March by the COVID-19 Response Team from Imperial College (Ferguson20[1]) appears to have been largely responsible for driving government actions in the UK and, to a fair extent, in the US and some other countries. Until that report came out, the strategy of the UK government, at least, seems to have been to rely on the build up of ‘herd immunity’ to slow the growth of the epidemic and eventually cause it to peter out.
The ‘herd immunity threshold’ (HIT) can be estimated from the basic reproduction rate of the epidemic, R0 – a measure of how many people, on average, each infected individual infects. Standard simple compartmental models of epidemic growth imply that the HIT equals {1 – 1/R0}. Once the HIT is passed, the rate of new infections starts to decline, which should ensure that health systems will not thereafter be overwhelmed and makes it more practicable to take steps to eliminate the disease.
However, the Ferguson20 report estimated that relying on herd immunity would result in 81% of the UK and US populations becoming infected during the epidemic, mainly over a two-month period, based on an R0 estimate of 2.4. These figures imply that the HIT is between 50% and 60%.[2] Their report implied that health systems would be overwhelmed, resulting in far more deaths. It claimed that only draconian government interventions could prevent this occurring. Such interventions were rapidly implemented in the UK, in most states of the US, and in various other countries, via highly disruptive and restrictive enforced ‘lockdowns’.
A notable exception was Sweden, which has continued to pursue a herd immunity-based strategy, relying on relatively modest social distancing policies. The Imperial College team estimated that, after those policies were introduced in mid-March, R0 in Sweden was 2.5, with only a 2.5% probability that it was under 1.5.[3] The rapid spread of COVID-19 in the country in the second half of March suggests that R0 is unlikely to have been significantly under 2.0.[4]
Very sensibly, the Swedish public health authority has surveyed the prevalence of antibodies to the SARS-COV-2 virus in Stockholm County, the earliest in Sweden hit by COVID-19. They thereby estimated that 17% of the population would have been infected by 11 April, rising to 25% by 1 May 2020.[5] Yet recorded new cases had stopped increasing by 11 April (Figure 1), as had net hospital admissions,[6] and both measures have fallen significantly since. That pattern indicates that the HIT had been reached by 11April, at which point only 17% of the population appear to have been infected.
How can it be true that the HIT has been reached in Stockholm County with only about 17% of the population having been infected, while an R0 of 2.0 is normally taken to imply a HIT of 50%?
The importance of population inhomogeneity
A recent paper (Gomes et al.[7]) provides the answer. It shows that variation between individuals in their susceptibility to infection and their propensity to infect others can cause the HIT to be much lower than it is in a homogeneous population. Standard simple compartmental epidemic models take no account of such variability. And the model used in the Ferguson20 study, while much more complex, appears only to take into account inhomogeneity arising from a very limited set of factors – notably geographic separation from other individuals and household size – with only a modest resulting impact on the growth of the epidemic.[8] Using a compartmental model modified to take such variability into account, with co-variability between susceptibility and infectivity arguably handled in a more realistic way than by Gomes et al., I confirm their finding that the HIT is indeed reached at a much lower level than when the population is homogeneous. That would explain why the HIT appears to have been passed in Stockholm by mid April. The same seems likely to be the case in other major cities and regions that have been badly affected by COVID-19.
Figure 1. New COVID-19 cases reported in Stockholm County, Sweden, over the 7 days up to the date shown. Note that in Sweden testing for COVID-19 infection was narrowed on 12 March, to focus on people needing hospital care, so from then on only a tiny proportion of infections were recorded as cases. This would account for the lack of growth in cases during the first week plotted. Since hospitalisation usually occurs several days after symptom onset, this change also increases the lag between infection and recording as a case. Accordingly, from mid- March on the 7-day trailing average new cases figure will reflect new infections that on average occurred approximately two weeks earlier.
The epidemiological model used
Like Gomes et al., I use a simple ‘SEIR’ epidemiological model,[9] in which the population is divided into four compartments: Susceptible (uninfected), Exposed (latent: infected but not yet infectious), Infectious (typically when diseased), and Recovered (and thus immune and harmless). This is shown in Figure 2. In reality, the Recovered compartment includes people who instead die, which has the same effect on the model dynamics. The entire population starts in the Susceptible compartment, save for a tiny proportion that are transferred to the Infectious compartment to seed the epidemic. The seed infectious individuals infect Susceptible individuals, who move to the Exposed compartment. Exposed individuals gradually transfer to the Infectious compartment, on average remaining as Exposed for the chosen latent period. Infectious individuals in turn gradually transfer to the Recovered compartment, on average remaining as Infectious for the selected infectious period.
Figure 2. SEIR compartment epidemiological model diagram.
In the case of COVID-19, the diseased (symptomatic) stage is typically reached about 5 days after infection, but an infected individual starts to become infectious about 2 days earlier. I therefore set the average latent period as 3 days.[10]
The infectious period depends mainly on the delay between infectiousness and symptoms appearing and on how quickly an individual reduces contacts with others once they become symptomatic, as well as on how infectious asymptomatic cases are. In an SEIR model, the infective period can be derived by subtracting the latent period from the generation time – the mean interval between the original infection of a person and the infections that they then cause.
The Ferguson20 model assumed a generation time of 6.5 days, slightly lower than a subsequent estimate of 7.5 days.[11] I use 7 days, which is consistent with growth rates near the start of COVID-19 outbreaks.[12] The infectious period is therefore 4 (=7 − 3) days.
I set R0=2.4, the same value Ferguson20 use. On average, while an individual is in the Infectious compartment, the number of Susceptible individuals they infect is R0 × {the proportion of the population that remains in the Susceptible compartment}.
With these settings, the progression of a COVID-19 epidemic projected by a standard SEIR model, in which all individuals have identical characteristics, is as shown in Figure 3. The HIT is reached once 58% of the population has been infected, and ultimately 88% of the population become infected.
Figure 3. Epidemic progression in an SEIR model with R0=2.4 and a homogeneous population. The time to reach the herd immunity threshold, which depends on the strength of the seeding at time zero, is arbitrary.
Modifying the basic SEIR model for variability in individual susceptibility and infectivity
The great bulk of COVID-19 transmission is thought to occur directly from symptomatic and pre-symptomatic infected individuals, with little transmission from asymptomatic cases or from the environment.[13] There is strong evidence that a small proportion of individuals account for most infections – the ‘superspreaders’.
A good measure of the dispersion of transmission – the extent to which infection happens through many spreaders or just a few – is the coefficient of variation (CV).[14] Two different estimates of this figure have been published for COVID-19. A Shenzhen-based study[15] estimated that 8.9% of cases were responsible for 80% of total infections, while a multi-country study[16] estimated that 10% were so responsible. In both cases a gamma probability distribution was assumed, as is standard for this purpose. The corresponding CV best estimates and 95% uncertainty ranges are 3.3 (3.0–5.6) and 3.1 (2.2–5.0). These figures are slightly higher than the 2.5 estimated for the 2003 epidemic of SARS.[17]
CV estimates indicate the probability of transmission of an infection. They reflect population inhomogeneity regarding individuals’ differing tendency to infect others, but it is unclear to what extent they also reflect susceptibility differences between individuals. However, since COVID-19 transmission is very largely person-to-person, much of the inhomogeneity in transmission rates will reflect how socially connected individuals are, and how close and prolonged their interactions with other individuals are. As these factors affect the probability of transmission both from and to an individual, as well as causing variation in an individual’s infectivity they should cause the same variation in their susceptibility to infection.
A common social connectivity related factor implies that an individual’s susceptibility and infectivity are positively correlated, and it is not unreasonable to assume a quite strong correlation. However, it seems unrealistic to assume, as Gomes et al. do in one case, that an individual’s infectivity is directly proportional to their personal susceptibility. (In the other case that they model, they assume that an individual’s infectivity is unrelated to their susceptibility.)
Some of the variability in the likelihood of someone infecting a susceptible individual during an interaction will undoubtedly be unrelated to social connectivity, for example the size of their viral load. Likewise, susceptibility will vary with the strength of an individual’s immune system as well as with their social connectivity. I use unit-median lognormal distributions to reflect such social-connectivity unrelated variability in infectivity and susceptibility. Their standard deviations determine the strength of the factor they represent. I model an individual’s overall infectivity as the product of their common social-connectivity related factor and their unrelated infectivity-specific factor, and calculate their overall susceptibility in a corresponding manner.[18]
I consider the cases of CV=1 and CV=2 for the common social connectivity factor that causes inhomogeneity in both susceptibility and infectivity. For unrelated lognormally-distributed inhomogeneity in susceptibility I take standard deviations of either 0.4 or 0.8, corresponding to a CV of 0.417 or 0.947 respectively. Where their gamma-distributed common factor inhomogeneity is set at 1, the resulting total inhomogeneity in susceptibility is respectively 1.17 or 1.65 when the lower or higher unrelated inhomogeneity standard deviations respectively are used; where set at 2 the resulting total inhomogeneity in susceptibility is respectively 2.17 or 2.98. The magnitude of variability in individuals’ social-connectivity unrelated infectivity-specific inhomogeneity factor does not affect the progression of an epidemic or the HIT, so for simplicity I ignore it here.[19]
Results
Figure 4 shows the progression of a COVID-19 epidemic in the case of CV=1 for the common social connectivity factor inhomogeneity, with unrelated inhomogeneity in susceptibility having a standard deviation of 0.4. The HIT is 60% lower than for a homogeneous population, at 23.6% rather than 58.3% of the population. And 43% rather than 88% of the population ultimately becomes infected. If the standard deviation of unrelated inhomogeneity in susceptibility is increased to 0.8, the HIT becomes 18.9%, and 35% of the population are ultimately infected.
Figure 4. Epidemic progression in an SEIR model with R0=2.4 and a population with CV=1 common factor inhomogeneity in susceptibility and infectivity and also unrelated multiplicative inhomogeneity in susceptibility with a standard deviation of 0.4.
Figure 5 shows the progression of a COVID-19 epidemic in the case of CV=2 for the common social connectivity factor inhomogeneity, with unrelated inhomogeneity in susceptibility having a standard deviation of 0.8. The HIT is only 6.9% of the population, and only 14% of the population ultimately becoming infected. If the standard deviation of unrelated inhomogeneity in susceptibility is reduced to 0.4, those figures become respectively 8.6% and 17%.
Figure 5. Epidemic progression in an SEIR model with R0=2.4 and a population with CV=2 common factor inhomogeneity in susceptibility and infectivity and also unrelated multiplicative inhomogeneity in susceptibility with a standard deviation of 0.8.
Conclusions
Incorporating, in a reasonable manner, inhomogeneity in susceptibility and infectivity in a standard SEIR epidemiological model, rather than assuming a homogeneous population, causes a very major reduction in the herd immunity threshold, and also in the ultimate infection level if the epidemic thereafter follows an unconstrained path. Therefore, the number of fatalities involved in achieving herd immunity is much lower than it would otherwise be.
In my view, the true herd immunity threshold probably lies somewhere between the 7% and 24% implied by the cases illustrated in Figures 4 and 5. If it were around 17%, which evidence from Stockholm County suggests the resulting fatalities from infections prior to the HIT being reached should be a very low proportion of the population. The Stockholm infection fatality rate appears to be approximately 0.4%,[20] considerably lower than per the Verity et al.[21] estimates used in Ferguson20, with a fatality rate of under 0.1% from infections until the HIT was reached. The fatality rate to reach the HIT in less densely populated areas should be lower, because R0 is positively related to population density.[22] Accordingly, total fatalities should be well under 0.1% of the population by the time herd immunity is achieved. Although there would be subsequent further fatalities, as the epidemic shrinks it should be increasingly practicable to hasten its end by using testing and contact tracing to prevent infections spreading, and thus substantially reduce the number of further fatalities below those projected by the SEIR model in a totally unmitigated scenario.
Nicholas Lewis 10 May 2020
[1] Neil M Ferguson et al., Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team Report 9, 16 March 2020, https://spiral.imperial.ac.uk:8443/handle/10044/1/77482
[2] A final infection rate of 81% implies, in the context of a simple compartmental model with a fixed, homogeneous population, that the ‘effective R0‘ is between 2.0 and 2.1, and that the HIT is slightly over 50%. Ferguson20 use a more complex model, so it is not surprising that the implied effective R0 differs slightly from the basic 2.4 value that Ferguson20 state they assume.
[3] Flaxman, S. et al., Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries. Imperial College COVID-19 Response Team Report 13, 30 March 2020, https://www.imperial.ac.uk/mrc-global-i … pi-impact/
[4] Based on the Ferguson20 estimate of a mean generation time of 6.5 days, which appears to be in line with existing evidence, an R0 of 2.0 would result in a daily growth rate of 2.0^(1/6.5)= 11%. That is slightly lower than the peak growth rate in cases in late March in Stockholm County, and in early April in the two regions with the next highest number of cases, in both of which the epidemic took off slightly later than in Stockholm, and in line with the growth rate in Swedish COVID-19 deaths in early April
[5] https://www.folkhalsomyndigheten.se/con … l-2020.pdf
[6] John Burn-Murdoch, Financial Times Research, 2 May 2020. http://web.archive.org/web/202005070756 … 0028576768
[7] Gomes, M. G. M., et al. Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold. medRxiv 2 May 2020. https://www.medrxiv.org/content/10.1101 … 20081893v1
[8] The 81% proportion of the population that Ferguson20 estimated would eventually become infected is only slightly lower than the 88% level implied by their R0 estimate of 2.4 in the case of a homogeneous population.
[9] https://en.wikipedia.org/wiki/Compartme … SEIR_model
[10] Gomes et al. instead set the latent period slightly longer, to 4 days and treated it as a partly infectious period, unlike in the standard SEIR model.
[11] Li Q, Guan X, Wu P, et al.: Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med. 2020; 382(13):1199–1207.https://www.nejm.org/doi/10.1056/NEJMoa2001316
[12] Once a SEIR model has passed its start up phase, and while a negligible proportion susceptible individuals have been infected, the epidemic daily growth factor is R0^(1/generation time), or 1.10–1.13 for R0=2.0–2.4 if the generation time is 7 days.
[13] L. Ferretti et al., Science 10.1126/science.abb6936 (2020).
[14] The coefficient of variation is the ratio of the standard deviation to the mean of its probability distribution. It is usual to assume a gamma distribution for infectivity, the shape parameter of which equals 1/CV2.
[15] Bi, Qifang, et al. “Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study.” The Lancet Infectious Diseases 27 April 2020. https://doi.org/10.1016/S1473-3099(20)30287-5
[16] Endo, Akira, et al. “Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China.” Wellcome Open Research 5.67 (2020): 67. https://wellcomeopenresearch.org/articles/5-67
[17] Lloyd-Smith, J O et al. “Superspreading and the effect of individual variation on disease emergence.” Nature 438.7066 (2005): 355-359. https://www.nature.com/articles/nature04153
[18] For computational efficiency, I divide the population into 10,000 equal sized segments with their common social connectivity factor increasing according to its assumed probability distribution, and allocate each population segment values for unrelated variability in susceptibility and infectivity randomly, according to their respective probability distributions.
[19] A highly susceptible but averagely infectious person is more likely to be removed from the susceptible pool early in an epidemic, reducing the average susceptibility of the pool. However, no such selective removal occurs for a highly infectious person of averagely susceptibility. Therefore, as Gomes et al. point out, variability in susceptibility lowers the HIT, but variability in infectivity does not do so except to the extent that it is correlated with variability in susceptibility.
[20] On 8 May 2020 reported total COVID-19 deaths in Stockholm County were 1,660, which is 0.40% of the estimated 413,000 of its population who had been infected by 11 April 2020. COVID-19 deaths reported for Stockholm County after 8 May that relate to infections by 11 April 2020 are likely to be approximately balanced by deaths reported by 8 May 2020 that related to post 11 April 2020 infections.
[21] Verity R, Okell LC, Dorigatti I, et al. Estimates of the severity of COVID-19 disease. medRxiv 13 March 2020; https://www.medrxiv.org/content/10.1101 … 20033357v1.
[22] Similarly, the HIT may be significantly higher in areas that are very densely populated, have much less inhomogenous populations and/or are repeatedly reseeded from other areas. That would account for the high prevalence of COVID-19 infection that has been found in, for instance, some prisons and residential institutions or in city districts.
Originally posted here, where a pdf copy is also available
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COVID-19: Updated data implies that UK modelling hugely overestimates the expected death rates from infection
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156 responses to “Why herd immunity to COVID-19 is reached much earlier than thought”
uwe.roland.gross | May 10, 2020 at 10:56 am | Reply
Reblogged this on uwerolandgross.
Andrew Roman | May 10, 2020 at 11:24 am | Reply
Nick: My question is: now what? Neither the UK nor the USA nor Canada have followed the Swedish policy. Assuming your approximation of between 7% and 24% is right, what policy implication follows for these and similar total lockdown countries? And what testing should be done to confirm the inhomogeneity as this new policy is being followed?
Simply Heather McGuigan | May 12, 2020 at 12:10 am | Reply
Inhomogeneity can be assumed. As no two immune systems are the same
Carrick | May 10, 2020 at 11:39 am | Reply
Your narrative about Sweden isn’t exactly matching the facts. Click on link for current numbers:
https://tinyurl.com/yaz3fj5q
Sweden’s the third worst performing country in the world in new infections per day per capita, after the completely incompetent pandemic responses by the US and the UK. Nor is there evidence that it is “over the peak.”
“On a plateau” is a better descriptor.
When you fold in the lower population density of Sweden this comparison looks even worse. Comparing it to its closet neighborhood, it has hardly been a success story, except in right-wing fiction I mean.
Other notes:
Plotting an exponentially varying function on a linear scale can be very deceptive—the dominant noise sources are typically multiplicative. On a linear scale, short period deviations will look more important than they actually are.
Also you need to look at seven-day smoothed data because of lags in reporting. The wiggles in the unaveraged data aren’t representative of the true day-to-day variation in actual cases, just variations in how long it takes for the new cases to appear on the books.
Joshua | May 10, 2020 at 12:01 pm | Reply
Great website at that link.
Could you post again adding Denmark and Austria? I could add them at the site (pretty dramatic) but couldn’t see how to get a URL on my phone to post with those added.
It’s easy to make Sweden look good if you don’t compare it to other countries that did do shelter in place measures.
Joshua | May 10, 2020 at 12:05 pm | Reply
Also, don’t forget to consider –
> More than half of Swedish households are single-person, the highest proportion in the EU, according to Eurostat. Official figures given to the BBC by the Swedish government’s number-crunching agency Statistics Sweden suggest that includes around one in five 18- to 25-year-olds, although its researchers estimate that the real number could be higher, since many remain registered at their parents’ address while they stay in sublet rentals.
dpy6629 | May 10, 2020 at 12:58 pm | Reply
Confirmed cases per million is not a meaningful statistic because “confirmed cases” are strongly dependent on the level of testing. I would have expected better from you Carrick.
By this flawed measure, it looks like New York is about the worst state. That must mean no mitigation (Dakotas) is better than very strict lockdowns. :-). This reasoning of course is not scientific.
RB | May 10, 2020 at 3:18 pm | Reply
The actual prevalence also appears to be much lower at ~5-10%. The 26% prevalence that the Swedish authorities claim appears to arise from a faulty assumption about when people are infectious versus when they test positive.
RB | May 10, 2020 at 3:27 pm | Reply
The prevalence of 26% also seems to arise from a faulty assumption that positive test = infectious. Correcting for this gives a prevalence of 5-10%.

Michelle Louw | May 10, 2020 at 3:29 pm | Reply
Belgium, Italy, Spain, UK, Netherlands and France all have higher numbers of deaths per million citizens than Sweden. The argument that only comparisons to close neighbours are valid ie, Norway and Finland, also doesn’t hold, unless you accept that Belgium is proof that longer and more severe lock downs caused more deaths than Germany’s much less stringent lock down.
RB | May 10, 2020 at 3:45 pm |
This is fair. But Swedes have been self-distancing in a manner similar to government imposed lockdown compliance in the U.S.

Joshua | May 10, 2020 at 3:48 pm |
Michelle –
> Belgium, Italy, Spain, UK, Netherlands and France all have higher numbers of deaths per million citizens than Sweden
Comparing across countries is fraught. There are many comparison variables that are hard to control for. That said, if yi really think there is something to be gained from comparing, Sweden has about the 9th highest deaths per million among some 220 countries at Worldometers.
It is 30% higher than Switzerland. 3x higher than Germany and Denmark. 6x higher than Finland. And it is rising in the ranks. Not long ago it was lower than the Netherlands. Only maybe two weeks ago it was lower than Switzerland.
Also, Sweden ranks considerably lower in tests per million than it does in cases per million. Now that’s a bit tricky because different countries have different testing politicies. Some are more likely than others to limit tests to people who are symptomatic or essential workers. But in general it’s not a good sign that they rank lower in testing per million than in cases per million – by a significant amount.
mesocyclone | May 10, 2020 at 4:25 pm |
The idea that Sweden didn’t order a lockdown is true only if you use a harsh definition of lockdown – a reason I don’t like the term. Sweden ordered a number of measures to be taken. Recently, they closed a number of bars that violated social distancing rules.
Also, Swedes, like people elsewhere, voluntarily socially distance in a dangerous epidemic – which is one reason that their measures of mobility are similar to other countries. As an aside, that behavior means that if a country completely eliminated all rules, the life of its citizens, and its economy, would not “go back to normal.”
Gary Mullennix | May 10, 2020 at 5:43 pm | Reply
The real issue is understanding the role played by Niall Ferguson and his falsely designed model. Millions of people will suffer and die from economies that will not recover, perhaps ever.
niclewis | May 11, 2020 at 3:17 am | Reply
You have confused the position in Sweden as a whole with that in Stockholm.
For Stockholm County, cases and hospitalisations have fallen substantially from their peak, as I show.
It isn’t surprising that they may not have done so for Sweden as a whole, for which the epidemic is some time behind Stockholm. One might expect herd immunity not to have been reached yet in other regions.
Nothing in my exposition depends on the experience in Sweden as a whole.
When comparing countries, the appropriate metric IMO is not how many cases or deaths they have per million population, but the number of their total deaths (or lost life years) divided by the proportion of the herd immunity threshold that they have reached (or, strictly, had reached when the people who died were infected).
Where Sweden has done badly, along with the UK and various other countries, is in letting COVID-19 spread in hospitals and – often from them – to care (nursing) homes. Around 50% of total COVID-19 related deaths have been in care homes in many countries. In the UK, this was mainly caused by deliberate actions taken empty hospitals of old people early in order to “protect the NHS” from a threat of it being overwhelmed that was wrongly predicted by the Ferguson20 model to occur.
RB | May 11, 2020 at 12:43 pm |
To reiterate, your basis hinges on the modeled extrapolation of the 2.5% infected cases over 5 days that is likely flawed as explained by Kucharski. If Kucharski’s calculation is right, you have to argue that HIT was achieved at a 5-10% prevalence. Such a prevalence calculation would also be consistent with an IFR in the 0.7-1% range seen from data in NYC, UK etc. The more plausible explanation is that the curve flattening in Stockholm is well explained by the documented fall in social mobility from voluntary self-distancing in Sweden comparable to that achieved by U.S/UK lockdowns.
RB | May 11, 2020 at 1:00 pm |
As explained here, their extrapolation from PCR positive=infectious is a mistake

RB | May 11, 2020 at 1:39 pm |
Actual testing (albeit 454 samples) as opposed to testing+extrapolation by Swedish authorities is consistent with ~7.5% prevalence

climategrog | May 11, 2020 at 7:50 am | Reply
Also you need to look at seven-day smoothed data because of lags in reporting.
“smoothing” will not remove a lag. Much of the 7 day variations are real, not just low logging at w/e or similar. ( UK may be low logging ).
When you fold in the lower population density of Sweden this comparison looks even worse. Comparing it to its closet neighborhood, it has hardly been a success story, except in right-wing fiction I mean.
Because you are failing to realise that Sweden chose to deal with infections instead of postpone them. Norway still has to pay the price. Your conclusions are premature and uninformed.
Thanks for declaring your left/right bias on how you look at the world. That explains why you see what you want to see to bolster your prejudice instead of what is there.
jeffnsails850 | May 11, 2020 at 10:36 am | Reply
“Sweden’s the third worst performing country in the world in new infections per day per capita, after the completely incompetent pandemic responses by the US and the UK.”
It’s illuminating how many people will go to such bizarre depths to be completely inaccurate for their sad politics.
Sweden isn’t the “third worst” of anything. If you think the handling of the pandemic has been “incompetent” in the US and UK, you must be ready to hang politicians in Belgium, the Netherlands, France, Spain, Italy…
All of that arm-waving and diversion is meant to get us to miss what you can’t accept for political reasons- densely packed urban landscapes with high adoption of public transportation were hit hard by this epidemic. Policies regarding nursing homes- moving old people to them and, as in New York, forcing them to take Covid-positive cases, killed thousands.
Here’s an interesting stat- New York is the fourth most populous state in the US. Almost five times (4.8) as many people died in New York as did in the top three most populous states combined.
Combined.
You won’t be able to paper that over by claiming Texas has no cities, Florida no old people, or that Trump isn’t the president of California. Just like you won’t be able to ignore the fact that the capital of the EU handled the virus with far less competency than Boris in the UK (by your own measurements).
This pandemic was hard on anyone who lived in a city that doesn’t use automobiles (New York City v Los Angeles), did a better job of avoiding visits to grandma, and didn’t have the NHS or Andrew Cuomo’s bad policies toward nursing homes.
And you want us to forget about China, which will depend a lot on how Russia fares. If they have a Swedish death rate, or get really lucky and have same rate as the “incompetent” US, the Russians may not be as angry at China. But if Russia ends up with France or Belgium’s level of “competency” and death rate the global anger at China could get ugly.
Joshua | May 10, 2020 at 11:44 am | Reply
> A recent paper (Gomes et al.[7]) provides the answer. It shows that variation between individuals in their susceptibility to infection and their propensity to infect others can cause the HIT to be much lower than it is in a homogeneous population.

> And the model used in the Ferguson20 study, while much more complex, appears only to take into account inhomogeneity arising from a very limited set of factors – notably geographic separation from other individuals and household size – with only a modest resulting impact on the growth of the epidemic
> > The do not assume a uniform IFR. See page 5 in https://spiral.imperial.ac.uk:8443/bits … port-9.pdf
https://statmodeling.stat.columbia.edu/ … nt-1332014
–snip–
Table 1: Current estimates of the severity of cases. The IFR estimates from Verity et al.12 have been adjusted
to account for a non-uniform attack rate giving an overall IFR of 0.9% (95% credible interval 0.4%-1.4%).
Hospitalisation estimates from Verity et al.12 were also adjusted in this way and scaled to match expected
rates in the oldest age-group (80+ years) in a GB/US context. These estimates will be updated as more data
accrue
Joshua | May 10, 2020 at 11:48 am | Reply
Co-author of Gomes et al. …
> As a coauthor in this study I’m going to start by saying what its conclusions are NOT: (i) it does NOT conclude that lockdowns/social distancing are unnecessary; (ii) it does NOT say “herd immunity” is ~20% regardless. In fact that number is conditional on social distancing 1/6
> As @joel_c_miller put it recently, heterogeneity/variation is complicated, and often doesn’t change significantly the conclusions from “homogeneous” models. The point is that here it just might, but we are mostly ignorant of the actual parameter values 3/6

niclewis | May 10, 2020 at 3:39 pm | Reply
This is a misleading comment. I was writing about inhomgeneity in susceptibility to infection. Inhomgeneity by age in infection fatality rates has nothing to do with that.
I wrote that the Ferguson20 model “appears only to take into account inhomogeneity arising from a very limited set of factors – notably geographic separation from other individuals and household size – with only a modest resulting impact on the growth of the epidemic”.
I did not say that those were the only two factors used in their modelling.
I agree that age related variation in attack rates is a component of inhomgeneity in assumed susceptibility, but I estimate that it only would only reduce the final infected proportion of the population by circa 1% point, which is a minor part of the 7% points that the Ferguson20 model achieves.
Joshua | May 10, 2020 at 4:07 pm |
Ok, so when you said:
>And the model used in the Ferguson20 study, while much more complex, appears only to take into account inhomogeneity arising from a very limited set of factors – notably geographic separation from other individuals and household size
What you meant to convey was:
> And the model used in the Ferguson20 study, while much more complex, appears only to take into account inhomogeneity [with respect to rates of infection] arising from a very limited set of factors – notably geographic separation from other individuals and household size
Now what do you think about one of the co-authors saying?:
> As @joel_c_miller put it recently, heterogeneity/variation is complicated, and often doesn’t change significantly the conclusions from “homogeneous” models. The point is that here it just might, but we are mostly ignorant of the actual parameter values
and
> it does NOT conclude that lockdowns/social distancing are unnecessary; (ii) it does NOT say “herd immunity” is ~20% regardless. In fact that number is conditional on social distancing
Did I misunderstand you there as well, and you actually weren’t arguing against the idea that heterogeneity/variation…often doesn’t change significantly the conclusions from homogeneous models, and you actually weren’t arguing that lockdowns/social distancing are unnecessary?
Paul Kielpinski | May 10, 2020 at 11:53 am | Reply
The SEIR model misses the fifth group in the population, those immune due to genetic and/or other factors that have not been researched.
niclewis | May 10, 2020 at 3:45 pm | Reply
Yes, I thought about mentioning that. But I concluded that the common inhomogeneity in susceptibility and infectivity arising from social connectivity related variability can adequately model this group, without needing an extra compartment for it. In effect, this group can be treated as having zero or near zero social connectivity.
mesocyclone | May 10, 2020 at 4:22 pm | Reply
If there exist people who are naturally immune, you just put them in the “recovered” category at the start of the SEIR run. Whether that immunity exists at all for this disease is unknown.
Joshua | May 10, 2020 at 11:55 am | Reply
> A notable exception was Sweden, which has continued to pursue a herd immunity-based strategy, relying on relatively modest social distancing policies
Funny thing about that….
–snip–
Anders Tegnell, chief epidemiologist at Sweden’s Public Health Agency – the nation’s top infectious disease official and architect of Sweden’s coronavirus response –denied that “herd immunity” formed the central thrust of Sweden’s containment plan, in an interview with USA TODAY. Yet he also said the country may be starting to see the impact of “herd immunity.”
Turbulent Eddie | May 10, 2020 at 12:39 pm | Reply
“The Swedish constitution does not allow for a state of emergency in peacetime”
Funny how much divisiveness the Swedes arouse.
The US has comparably bad COIVD numbers.
Sweden has comparably bad GDP numbers.
This thing sucks, but it seems to suck everywhere.
Joshua | May 10, 2020 at 12:46 pm |
Yup.
Ian W | May 10, 2020 at 12:02 pm | Reply
I would suggest (as you infer) that there are actually 5 groups to be considered:
> Innately Immune
> Susceptible Uninfected
> Exposed Latent
> Infectious Deceased
> Recovered Harmless
From the few antibody/serological tests the number of people who were infected but asymptomatic (recovered harmless) were ~4% and infectious deceased (the normal count of cases/deaths) ~1%. The number of uninfected is in the 95% range. Yet we see in areas where there were crowded ideal infection conditions only ~5% at most infected. The London Underground is a good example with 5milion passenger journeys a day most tightly crowded into poorly ventilated carriages for tens of minutes. Yet the number infected in UK as a whole is ‘only’ ~220,000. So this is either not a very infectious virus – OR – there is a large proportion of innately immune. I would suggest that this number is ~90% in UK and USA. The people in the innately immune have one or more of a genetic immunity of some sort, or a sufficiency of Vitamin D, Zinc and Selenium giving immunity, a strong innate immune system.
So now consider a population with 5% susceptible uninfected possibly not well mixed. For example populations in the North East in winter with a community with genetic disposition to infection will be different to a populations in the South in winter sun and no genetic disposition. The infection will not be consistent in some areas with a lot of susceptible individuals having a large case and death rate.
I propose that the model for the infection should be looked at as a predator prey algorithm (which is what herd immunity implies). The large number of Innately Immune means that the ‘herd immunity’ is almost there anyway. But importantly as you describe herd immunity, the virus will stop. But with a large innately immune proportion the virus will just stop after most of the prey have either been infected and survived or died. There can then be no ‘second wave’ of this or closely similar virus with the same infection method.
SARS and MERS both just stopped.
It should be noted that ensuring a sufficiency of Vitamin D, Zinc and Selenium is likely to move most people from susceptible to innately immune. This is simple to do and cheap why this is not being recommended by governments is extremely puzzling.
Curious George | May 10, 2020 at 12:34 pm | Reply
Is there an estimate of the percentage of the “innately immune” population? Do models really ignore that fraction?
Ian W | May 10, 2020 at 1:53 pm |
I am just basing my estimates on the opposite of the number of cases even adding the serology tests. It is natural for the press to emphasize the number of cases/deaths that gets clicks and advertisers – but I was more struck by the reports of antibody testing in Los Angeles County (population over 10 million) and the reports were:
USC and the health department released preliminary study results that found that an estimated 4.1% of the county’s adult population has antibodies to the coronavirus, estimating that between 221,000 adults to 442,000 adults in the county have had the infection.
So look at the obverse, antibody testing indicates that 95.9% of the population were not infected. If everyone can be infected by a short period inside 2 meters of an infected person – then the number of infections would be in the millions.
But that number seems to hold in New York and in London ~95% of the population are innately immune. It does not suit people for various reasons to put the information that way. To be generous it may be that the population will let their guard down and the full 5% susceptible would be infected. But the response to throw away the lessons of all previous pandemics and keep everyone indoors at home the most likely place to be infected makes zero sense – as New York has found out 60%+ infections in NY are to people staying at home.
So no information on how to raise innate immunity with vitamin D and zinc etc, and then putting people at risk by making them ‘stay indoors at home’ – both completely counter to what should have been done
niclewis | May 10, 2020 at 4:55 pm |
There are a couple of prisons in Ohio where around 70% tested positive for COVID-19 infection, so it seems unlikely that, the innately immune proportion can be much above 30%, and it might be well under 30%.
However, in addition there are likley some fraction of people who are quite resistant to infection in normal conditions, even if they wouldn’t be able to resist infection in prison conditions.
Curious George | May 10, 2020 at 7:52 pm |
Nic, thanks, but .. there is some limited data from the Grand Princess and the Diamond Princess, showing a much lower infection rate – but then it is more difficult to test a cruise ship passenger than a prisoner. Also data from the Theodore Roosevelt point to only 1/6 of the crew being infected.
AJ | May 11, 2020 at 12:32 pm |
Keep in mind that probably about half of those inmates were black.
The Vitamin D Status of Prison Inmates
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3944727/
Results:
Serum 25(OH)D levels peaked in summer and autumn, and decreased in winter and spring. Vitamin D deficiency occurred in 50.5% of blacks, 29.3% of whites, and 14.3% of Asian inmates (p = 0.007).
Ron Graf | May 10, 2020 at 1:24 pm | Reply
“This is simple to do and cheap why this is not being recommended by governments is extremely puzzling.”
Yes, it follows the authority’s clearly greater interest in the success of Remdesivir under patent by Gilead Sciences at the low-low price of $9/ day when they ramp up. https://www.bloomberg.com/news/articles … study-says
They genuinely feel unethical about promoting home-grown actions beyond hand washing and face protection. Promoting vitamin and mineral supplements smacks of hawking store merchandise. By the way, I finally received by back ordered online zinc supplements yesterday. I was eating cashews (high in zinc other minerals) in the meanwhile as a stop-gap. So far they worked.
niclewis | May 10, 2020 at 3:55 pm | Reply
As I replied to Paul Kielpinski , I thought about mentioning the Innately Immune group, but I concluded that the common inhomogeneity in susceptibility and infectivity arising from social connectivity related variability would adequately model this group (by treating it as having near zero social connectivity), without needing an extra compartment for it.
I agree that this group is probably sizeable, although I would be surprised if as much as 50% of the population was actually immune, as opposed to being difficult to infect and (if infected) not very infectious.
Ian W | May 10, 2020 at 4:10 pm |
Thank you for the reply Nic
As soon as the innately immune (or difficult to infect) are a sizeable majority then the algorithms should really change as using a generic average value for infectivity becomes misleading. This is why I suggested a more suitable algorithm would be predator/prey. This also leads to the logic of how can I move the prey into non-prey innately immune group (other than infecting them).
The various governments have signally failed to do this. The politicians are not being assisted by the medical community who know how to increase immunity to SARS-CoV-2 yet do not tell anyone – rather they let people including others in the medical community die a painful death.
mesocyclone | May 10, 2020 at 4:27 pm | Reply
From the modeling standpoint, you don’t need a fifth category. Put the innately immune into the “recovered” category and you get the same result (other than the graph of # recovered will look a bit odd).
It doesn't add up... | May 10, 2020 at 6:04 pm | Reply
The KCL symptom tracker suggests that over 2 million were infected in the UK at its estimate of the peak on 1st April.
https://covid.joinzoe.com/data#levels-over-time
Student | May 10, 2020 at 12:08 pm | Reply
The results are even more striking if the variability is combined with spacial structure, that is, if variability is applied between populations, rather than within populations.
Let’s take a simple example of three equal populations: one population has a median R0, another population has twice the R0, and a third has one-half. This is a natural approximation for a lognormal with a standard deviation of 0.7 and a sample size of three. This would be a variation of 0.5 (whether it is connection related doesn’t matter in this model), or substantially less than the 1.16 (sum of both connection related and unrelated) variation in your smallest model.
In a situation where there are multiple entries of the disease into a population set, the population with the highest R0 will quickly dominate the spread, and R0 for the population will reflect it. Hence the highest population will have an R0 of 2.4, the middle an R0 of 1.2, and the lowest an R0 of 0.6. Combining the equations for herd immunity, we get 0% for the R0 0.6 population, 17% for the R0 1.2 population, and 58% for the R0 2.4 population, for an average of 25%. The whole population set has an immunity threshold of 25%.
Andy West | May 10, 2020 at 12:13 pm | Reply
‘Balanced’ or ‘maintained’ genetic polymorphism in species is supposed in part to be a protection against diseases. I guess this turns up mainly as ‘social-connectivity unrelated variability in susceptibility’, which should also manifest as more than just differences in the immune system. I lost track in the text of the relative importance of this compared to social connectivity factors, and indeed whether this is determinable. Is it so? (The spread of genetic variance over at least some nations must be known, as these have been been sampled pretty often by now I guess, which is maybe helpful in estimating this from a different angle).
niclewis | May 10, 2020 at 4:11 pm | Reply
I’m not aware that the relative importance of the social connectivity unrelated variability in susceptibility has been determined for COVID-19. Possibly it may have been for another infectious disease.
I have mainly focused on cases where social connectivity related variability is the more important factor. In the case I mention where that variability has a CV of 1 and the standard deviation of the unrelated lognormally-distributed variability is 0.8, the two factors contribute similar proportions of the total variability in susceptibility.
Andy West | May 10, 2020 at 5:21 pm |
Thanks, got it. As the populations are large and the variety is also large (apart from minor pockets of interbreeding, we are very far from clones), I presumed the protections from variability would be similar across at least similar classes of disease. But indeed I don’t know if this is so or whether it has been distilled down to an actual figure.
Andy West | May 10, 2020 at 5:26 pm |
P.S. the relatively immune you and Paul K mention above, would be part of the distribution created by genetic variability.
Clive Best | May 10, 2020 at 5:36 pm |
Without a vaccine, reducing R just prolongs the outbreak but does save some lives, although economic collapse will cost more lives.
Joshua | May 10, 2020 at 5:40 pm |
Clive –
> Without a vaccine, reducing R just prolongs the outbreak but does save some lives, although economic collapse will cost more lives.
What are you attributing as the cause for economic collapse?
Clive Best | May 11, 2020 at 11:38 am |
Right now the government is paying 80% wages of several million people to stay at home. That cannot be sustained for 9 months.
Joshua | May 10, 2020 at 5:42 pm |
And to what degree would saving some lives (and having fewer people hospitalized, and fewer people sick, and less strain on health professionals) help reduce the level of economic collapse?
Don132 | May 11, 2020 at 1:01 pm |
“Right now the government is paying 80% wages of several million people to stay at home. That cannot be sustained for 9 months.”
Yes it can, and quite easily. Any government issuing a fiat currency can always pay its bills. It never has to turn to the printing press and say, OK bud, how much do I owe ya?
So long as too few goods aren’t chased by too much money, inflation isn’t a problem.
Not saying I agree this should happen, but I am saying that it’s entirely possible for the US government to keep us on life support indefinitely.
Here’s is a good essay that describes Modern Monetary Theory in relation to where we are today.
https://seekingalpha.com/article/434578 … ation-game
The money quote: “On April 23, Lloyd Blankfein tacitly contended that the US needs to “borrow dollars.” His purpose … was simply to drive home the same point that countless other “luminaries” have attempted to make recently. Thanks to the spending associated with virus relief efforts, the deficit is set to balloon to around $4 trillion in 2020, which “should” entail higher bond yields, and all manner of other scary things that you’ve been indoctrinated to believe invariably accompany fiscal largesse.
“What these folks are inadvertently doing, though, is laying bare the absurdity in this type of thinking for the issuer of a reserve currency. I implore you: Step back from this situation and ask yourself whether it makes any sense to say that the US needs another nation to “lend” America “dollars.”
“Simply put, that is self-referential nonsense. The US can always buy whatever there is to buy that’s denominated in US dollars. It has no need to borrow dollars from anyone else because it is the issuer of those dollars. The US can spend too much, which risks stoking inflation, but the US does not, will not, and has never, needed to borrow dollars. Suggesting otherwise is to traffic in patent nonsense, as Blankfein is doing in the tweet above.”
Heisenberg is, I’ve found, astute in many matters having to do with markets and finance. He’s right here, too. https://www.amazon.com/Deficit-Myth-Mon … 1541736184
Don Monfort | May 11, 2020 at 3:27 pm |
Ah, AOC’s Modern Monetary Policy. I could stop there. But:
reserve currency:”A reserve currency (or anchor currency) is a foreign currency that is held in significant quantities by central banks or other monetary authorities as part of their foreign exchange reserves.”
Modern Monetary Policy says: “What these folks are inadvertently doing, though, is laying bare the absurdity in this type of thinking for the issuer of a reserve currency. I implore you: Step back from this situation and ask yourself whether it makes any sense to say that the US needs another nation to “lend” America “dollars.”
“Simply put, that is self-referential nonsense. The US can always buy whatever there is to buy that’s denominated in US dollars.”
Ask yourself why for example, Zimbabwe’s and Venezuela’s currencies are not reserve currencies.
I will help you: Why would central banks hold as foreign currency reserves the currencies of nations that print the crap willy nilly? Why would anybody not forced to by their own foolish government accept payment in those currencies for anything?
The big flaw in socialist/Marxist theory is that they think they can come along and appropriate the wealth created by a capitalist economic system, transfer it to the have nots and no disruption to the creation of goods, services and wealth will occur.
cerescokid | May 11, 2020 at 3:33 pm |
Don
You do realize that puts you shoulder to shoulder with AOC. In some ways I envy you. In other ways, not so much.
bigterguy | May 11, 2020 at 6:23 pm |
“ Why would central banks hold as foreign currency reserves the currencies of nations that print the crap willy nilly? ”
Um, the US is doing a pretty good job of running their printing presses these days.
Don132 | May 11, 2020 at 6:37 pm |
Seems like my (longish) comment was lost in moderation.
Short answer: I’m not left, I lean right, and any country issuing its own currency can indeed pay all its bills denominated in that currency. When you have hyperinflation for whatever reason, and you have to convert your currency to dollars (or some other reserve currency) in order to buy something you don’t produce, then yes, that’s a problem. The US doesn’t have that problem. Whether you think MMT is leftest or not is immaterial to whether or not it describes how the monetary system actually works, and whether some want to use it to rob the rich to pay the poor is also immaterial. And no, I do not believe in Universal Income, although yes, I may become a heroin addict if the government decides I have nothing else more useful to do and pays me to become one. And yes, I’m joking.
Heisenberg is correct, whether we like it or not. And no, I did not come across MMT just now by reading Heisenberg.
That’s as short as I can manage, except that no, I won’t bother debating this further as it’s really off-topic and doesn’t matter.
dougbadgero | May 11, 2020 at 8:16 pm |
Regarding MMT and other issues with the economics of what we are doing:
The belief that we can continue to pay millions to do nothing forgets the purpose of a capitalist system. The purpose isn’t to make money, it is to produce goods and services. Those millions of people are no longer producing goods and services, but they are receiving the medium of exchange (money) to allow them to buy goods and services. This will eventually reduce the standard of living for everyone since millions are now consumers but not producers.
Don Monfort | May 11, 2020 at 9:55 pm |
Sr. 132:”I’m not left, I lean right, and any country issuing its own currency can indeed pay all its bills denominated in that currency.”
Tell the formerly well off countries that have insufficient hard currency to import food, medicine and other necessities, to insist on having the bills for their imports denominated in there crap currencies. That is not the only problem that countries with debased currencies create for themselves. Google “debased currency”. Take a contemplative week off, then come back and talk.
Mr. Big:”Um, the US is doing a pretty good job of running their printing presses these days.”
We are not printing money willy nilly. What we are doing is spending money that we will borrow. We can borrow a lot of money, because we have a yuuge economy that produces a lot of stuff we can sell, our currency is the reserve currency of the World, and we have a good credit rating. We also have in our reserves over 8,000 metric tonnes of gold.
We are not yet debasing our currency. That’s an inglorious feat the socialist/Marxists will accomplish, if they can convince enough economic illiterates to vote them into power. They are obviously plowing fertile ground.
Joe Born | May 10, 2020 at 12:24 pm | Reply
Could you go into more detail on how you implemented your connectivity and infectiousness parameters?
When I did something similar last night (with a quick-and-dirty SIR model) I simply assigned each member of the population a respective gamma-distributed R0 value. And the likelihood that in infectious person would infect a randomly selected uninfected person within a given time interval (six hours) I merely took as the square root of respectively probability figure equal to the ratio of the respective R0 value and that ratio of that time interval’s duration to the (uniform) infectiousness duration.
Obviously your approach is more sophisticated, but I couldn’t quite that part.
Joe Born | May 10, 2020 at 3:20 pm | Reply
Please ignore my question above. I asked before I read the footnotes, which make your piece clear.
J Martin | May 10, 2020 at 12:29 pm | Reply
My question is, should the governments advisors have known this and could it be seen in the data prior to lockdown, in which case lockdown with all its consequences should not have taken place.
niclewis | May 11, 2020 at 3:34 am | Reply
IMO governments should have realised (through being advised competently) that it was quite possible that the HIT was much lower that predicted by the Ferguson20 model or by simple models that ignored population heterogeneity.
They should also have realised that that, in the absence of an effective vaccine or drug, for which the outlook is very murky, a lockdown that does not continue indefinitely saves few lives except to the extent that, through “flattening the curve”, it avoids health systems being overwhelmed.
There has never been any evidence that the UK health system was about to be overwhelmed, just erroneous predictions from the Ferguson20 model.
IMO it was very stupid to impose a pretty hard lockdown at the stage that the UK did, certainly on a UK wide basis.
However, the position may have been different in some countries, particularly in regions where their health systems were becoming overwhelmed, in which case a temporary hard lockdown to flatten the curve might have been the least bad option.
Turbulent Eddie | May 10, 2020 at 12:29 pm | Reply
Interesting.
A low HIT, provided exposure has been large,
implies two testable hypotheses:
1. No second wave, and
2. No return in the autumn
I’m guessing we’re nominating Sweden as the test case.
We shall see.
Joshua | May 10, 2020 at 1:01 pm | Reply
Bad idea to try to infer too much from cross-country comparisons. Means comparing lots o’ uncontrolled variables.
Almost as bad as extrapolating from non-representarive and non-random sames.
Like a Rorschach test for political biases.
Ron Graf | May 10, 2020 at 1:51 pm |
Hi Joshua, Isn’t it You that is prejudging the results, (as biased), before the analysis? All I see TE doing is postulating there is a potential test. I find it hard to support your skepticism with the mountains of data from thousands of localities, all with known demographics. Shouldn’t you reconsider? The only place we have seen second waves so far are in places where the strong mitigation stopped the virus very early, like in Singapore.
Turbulent Eddie | May 10, 2020 at 2:18 pm |
“lots o’ uncontrolled variables.”
Yes, including the strain of the virus in question.
Evidently, the Euro variant is much more communicable in Europe and America than the Asian variant:
Why the Mutated Virus Spreads Faster in America and Europe Than East Asia
Joshua | May 10, 2020 at 2:32 pm |
TE –
Sure, could be for all I know. Then again:
> There’s no clear evidence that the pandemic virus has evolved into significantly different forms—and there probably won’t be for months.
https://www.theatlantic.com/health/arch … le/611239/
Steven Mosher | May 10, 2020 at 10:44 pm |
ButUncontrolledVariables.
Climate skeptics use this too joshua
bigterguy | May 11, 2020 at 6:21 pm |
All better scientists recognize that there are unknowns, and uncontrollable aspects. That’s why we do many experiments and get a good signal to noise ratio when we can.
Joshua | May 11, 2020 at 6:46 pm |
I’m not arguing arguing one way or the other.
What I’m saying is thst I can see people selecting comparison points, inevitably, to prove associations that agree with their ideological preferences.
I’ll give TE credit for at least bucking that trend. Nic, not so much. What it boils down to is the comprehensiveness of your treatment of the variables.
People are comparing to the economic effect of Sweden’s no lockdown policy without even attempting to control for the effect of the lockdowns in other countries as distinguished from the impact of a raging epidemic. They are making assumptions about the benefits economically to Sweden from no lockdown without even evaluating the economic state of Sweden. Your friend was comparing virus trends in Sweden and Switzerland a few weeks ago – not doing that now, is he? Why do you think he stopped? Maybe because he was making that comparison before enough time had passed to make the comparison meaningful.
“Skeptics” are often right when they raise questions about incontrolled variables. I have often said so.
It’s like when Nic tried to extrapolate from non-representative data on the Princess Diamond, and then had a double down by doing it too soon (missing a high percentage of deaths).
Above all, the question is really about consistency and evenly applied standards.
There are other rules that apply to appeals to uncertainty.
TE gets good marks on this issue in my opinion. He’s applying due skeptical diligence.
Joshua | May 10, 2020 at 12:35 pm | Reply
Chelsea MA.
Serological survey suggested over 30% infected (warning, the sampling methodology wasn’t really that random).
Infections (and fatalities) still growing (40,000 population, 124 currently died from COVID – which at @ 30% infected works out to @ a 1.0% IFR).
niclewis | May 10, 2020 at 4:31 pm | Reply
The Chelsea survey results aren’t inconsistent with what I wrote. See note [22], where I said that the HIT might be significantly higher in areas that are, for instance, very densely populated or have much less inhomogenous populations.
I note that the Boston Globe article reporting the Chelsea MA survey results says:
“about 65 percent of its residents are Latino. Many live in three-decker houses, Ambrosino said, where it’s hard for people to isolate themselves. Many work in the hospitality industry and health-related fields, where exposure to the virus is greater.”
All those factors would cause both R_0 and the HIT to be higher than their US wide population averages.
I don’t think it’s true that infections are still growing in Chelsea. This article ( https://www.bostonherald.com/2020/05/06 … ates-rise/ ) says:
“We’re feeling some level of relief that the rise in cases has stopped and that we’re starting to see less cases a week,” Chelsea City Manager Thomas Ambrosino told the Herald. “That’s certainly good, positive news.”
Joshua | May 10, 2020 at 5:30 pm |
Nic –
> I don’t think it’s true that infections are still growing in Chelsea.
Obviously, that quote suggest that the rate of increase has flattened, not that # of infections isn’t rising. What I said is that infections are still growing (along with deaths). Do you actually doubt that?
And so anyway, what do you see as the value of some kind of generic supposition that in some generic context there might be a particular generic herd immunity rate, given that the herd immunity rate is very likely to be significantly lower or higher than your generic estimate *depending on a whole slew of much more influential variables?* What matters is how those variables play into particular contexts.
Since you’re prescribing policy for the UK, than perhaps you should work on that the herd immunity rate for the UK might be – more than likely significantly higher than Stockholm, don’t you think? Then why do you keep using Sweden as some point of comparison?
If you look at the quote from the co-author that I’ve posted, his point is exactly that so much depends on the particulars of the context.
> All those factors would cause both R_0 and the HIT to be higher than their US wide population averages.
Well, that’s the point, now is it? How useful are the conditions for Stockholm for understanding the herd immunity % in any particular other locations?
HotScot | May 10, 2020 at 12:41 pm | Reply
It’s worth mentioning an article in the Telegraph today by Matt Ridley and David Davis (MP) which states:
“Is the chilling truth that the decision to impose lockdown was based on crude mathematical guesswork?”
Including this: “Details of the model his [Ferguson] team built to predict the epidemic are emerging and they are not pretty. In the respective words of four experienced modellers, the code is “deeply riddled” with bugs, “a fairly arbitrary Heath Robinson machine”, has “huge blocks of code – bad practice” and is “quite possibly the worst production code I have ever seen”.”
https://www.telegraph.co.uk/news/2020/0 … hematical/
Paywalled but easy to hurdle.
mesocyclone | May 10, 2020 at 4:30 pm | Reply
While Lewis’ code was poor, his results were consistent with what is known about epidemiology. My own model got similar results, and the code was very simple – maybe 100 lines of python for a discreet time SEIR model.
A lot of code used in science is poor. Scientists are not often good programmers, plus most of the code is written by grad students – one after another on the same code if it survives for long.
niclewis | May 10, 2020 at 4:33 pm |
I think you probably meant Ferguson’s code, not my code?
Bill_W_1984 | May 10, 2020 at 8:10 pm |
This was an interesting discussion of heterogeneity I came across a few days ago. And I believe it was this (or one linked to in this) that said that one problem with Ferguson’s program is that it gave different answers if run more than once. And that a team from Microsoft was trying to streamline it and thus far, even their code had issues. https://necpluribusimpar.net/lets-have- … -immunity/
matthewrmarler | May 10, 2020 at 12:50 pm | Reply
Nic Lewis, thank you for the essay.
Is there an operational definition of “herd immunity”, that is, a criterion by which we can decide from counts of newly diseased/newly dead that “herd immunity” has been achieved? Is it where the new case count reaches 0 and stays (nearly) there?
niclewis | May 10, 2020 at 4:42 pm | Reply
matthewrmarler, thanks for your comment. Herd immunity is perhaps best seen as a process rather than a defined specific state. But the “herd immunity threshold” is the state where, through individuals becoming infected and thereby immune, herd immunity has risen to the point that, on average, each individual who is infected in turn infects exactly one susceptible individual. Until that point, the number of infected individuals is continuously increasing. Beyond that point the number is shrinking.
The new case count doesn’t reach zero until the ultimately infected proportion is reached, which is higher than the HIT. I state both proportions for the examples that I give (see text just above Figures 4 and 5).
matthewrmarler | May 10, 2020 at 10:55 pm |
Nic Lewis: Herd immunity is perhaps best seen as a process rather than a defined specific state.
I get it. But you did say “reached”. Could you recognize a point at which you might say to a President or a Governor something like “We have reached it. Now you can end the social distancing measures”?
I feel like I’m pushing you unfairly. I was thinking more like, when the time derivative of the smoothed daily new case count was 0 or consistently lower after peaking. What if it becomes endemic like measles or polio before the vaccines, with recurrent outbreaks?
It doesn't add up... | May 10, 2020 at 7:06 pm | Reply
You may find this pair of articles from Simon Anthony a useful backgrounder on SIR models in relation to herd immunity and second waves and the putative effect of lockdowns.
https://hectordrummond.com/2020/05/05/s … omissions/
https://hectordrummond.com/2020/05/07/s … omissions/
matthewrmarler | May 10, 2020 at 10:58 pm |
It doesn’t add up … : You may find this pair of articles from Simon Anthony a useful backgrounder on SIR models in relation to herd immunity and second waves and the putative effect of lockdowns.
Thank you for the links.
Ireneusz Palmowski | May 10, 2020 at 1:21 pm | Reply
The drop in temperature in the east of the US is conducive to viruses.
Clive Best | May 10, 2020 at 2:39 pm | Reply
I find a similar result.
http://clivebest.com/blog/?p=9498
Ferguson’s model was originally developed for a 1918 type flu pandemic with a homogeneous population distribution
Keith A Rowe | May 10, 2020 at 3:03 pm | Reply
There is much more to transmission than R0 = X. X has many factors being how transmissible the disease is with regard to humidity and temperature as well as interpersonal interface with others. In New York, London, Paris, Northern Italy, with it’s high densities and people using the same public transport it means with people living in the same proximity and pushing the same elevator buttons and door handles of cabs it means much higher transmissibility and infection rates. A simple R0=X isn’t very realistic in Idaho when people often have their personal cars going to a small company and have 10’s of people they have interpersonal interface with instead of tens of thousands every day of those in high density high interpersonal interface cities.
Pingback: Variation in R – Markets Fail
Joshua | May 10, 2020 at 4:42 pm | Reply
Nic –
You say:
> Accordingly, total fatalities should be *well under 0.1%* of the population by the time herd immunity is achieved.
In NYC, they’re already slightly above 0.1% of the population dead. That number is obviously only going to increase. And that’s without even factoring the likely under-reporting of deaths (people dying at home and long term care facilities w/o tests, a lag in death reports being officially counted, etc.)
Help me to understand what it is about NYC that is different from your projection? Is it that even after reaching herd immunity people continue to die, or even to still get infected and die?
In Chelsea MA, with a population of 40k, and 124 deaths (already, with a probable undercount as mentioned above), they’ve already exceeded the population fatality rate or 0.1% by a considerable amount. To what do you attribute that difference from your projection?
> The Population Fatality Rate (PFR) has reached 0.22% in the most affected region of Lombardia and 0.57% in the most affected province of Bergamo,which constitutes a lower bound to the Infection Fatality Rate (IFR)…Combining PFR with the Princess Diamond cruise ship IFR for ages above 70 we estimate the infection rates(IR) of regions in Italy, which peak in Lombardia at 23% (12%-41%, 95% c.l.), and for provinces in Bergamo at 67% (33%-100%, 95% c.l.).
https://www.medrxiv.org/content/10.1101 … 20067074v2
Why did that infection rate and PFR get so high in Bergamo?
Joshua | May 10, 2020 at 4:44 pm | Reply
Perhaps your reply here answers my questions:
https://judithcurry.com/2020/05/10/why- … ent-916651
niclewis | May 11, 2020 at 3:49 am | Reply
The authorities failed to protect the elderly from COVID-19 infection. So deaths spread in care homes, and account for ~50% of deaths in many countries, nearly doubling the averaage infection fatality rate. In the UK this appears to have been caused primarily by deliberate (but totally unnecessary) actions by the authorities t clear hospital beds, prompted by the Ferguson20 model predictions, to “protect the National Health Service”.
Also, lockdowns, school closures and general encouragement of social distancing probably reduce the rate of infection among children and the highly connected younger sections of the adult community, relative to that of older people.
Deaths to reach the HIT would be minimised if the ratio of young, healthy people being infected were as high as possible relative to the number of old and vulnerable people being infected, since the fatality rate increases very steeply with age. Lockdowns and enforced social distancing generally may well have acted to reduce rather than increase this ratio.
Joshua | May 11, 2020 at 11:12 am |
> So deaths spread in care homes, and account for ~50% of deaths in many countries, nearly doubling the averaage infection fatality rate.
It isn’t simply a matter of them living in care homes. It’s also a factor of their age. Communities where people tend to live together or work in close quarters (prisons, meat packing companies) also have high infection rates – but other such communities don’t have the same high mortality rates because they don’t tend to be as old on average.
And there are a lot of older people who don’t live in such communities and who are presumably relatively isolated now – in a way that won’t be the case if countries just “open up,” and in particular if they do so before they have a robust infrastructure for testing/tracing/isolating.
> Deaths to reach the HIT would be minimised if the ratio of young, healthy people being infected were as high as possible relative to the number of old and vulnerable people being infected,
This is based on a really speculative assumption – that you can actually isolate those older people and keep them isolated while the infections are spreading around the younger people until her immunity is reached. Experience tells us that is a very questionable assumption – and also that embedded in that assumption is a willingness accept a disproportionate number of deaths among essential workers and particular communities at relatively high risk – such as minority communities. Keep in mind that at least part of the reason they’d be at higher risk is because they are less able to stay isolated.
> . Lockdowns and enforced social distancing generally may well have acted to reduce rather than increase this ratio.
Again, that is highly speculative – and is directly based on an assumption that over time, with slower spread, more effective treatments wouldn’t take place and also that a more robust infrastructure for testing/tracing/isolating wouldn’t be built that would slow the morbidity and mortality rates down, leading to much, much less hardship if a vaccine is developed and distributed.
You are gambling a huge amount on speculation. And there is no clear indication that government mandated shelter in place orders have a significant differential economic impact. You seem to be taking that merely on faith.
Josh Sacks | May 10, 2020 at 4:53 pm | Reply
Nic-
The Swedish paper you linked to appears to be the one that was retracted soon after it was published. AFAIK, they have not explained what the error was that led to retraction, but they have also not re-issued any of these prediction. https://www.forbes.com/sites/davidnikel … 8abaf04349
I don’t speak Swedish, so it’s entirely possible this is a different paper or a version of the paper with errors corrected. But I can’t find any mention of such a correction in any English source, and I can’t find any mention of these high Swedish infection rates past the 4/22 retraction of the paper.
Atomsk's Sanakan (@AtomsksSanakan) | May 11, 2020 at 2:40 am | Reply
Re: “The Swedish paper you linked to appears to be the one that was retracted soon after it was published”
Good catch. I highly doubt something like this would have made it into a peer-reviewed article written by a competent expert in this topic (ex: an epidemiologist or infectious disease expert). Make it rather ridiculous when people say that this pandemic will make the previous model of peer review obsolete.
“The rate of epidemiological and immunological research that is getting conducted and published is breathtaking; after all this settles, the old publication model with peer review and paywall will arguably be dead.”
https://judithcurry.com/2020/03/19/coro … certainty/
“Like the vast range of other non-peer-reviewed material produced by the denial community, book authors can make whatever claims they wish, no matter how scientifically unfounded.
[…]
The general lack of peer review for the denial books is a common feature of the vast body of literature produced by the climate change denial community, ranging from blogs to newspaper op-eds to policy briefs from CTTs.”
https://journals.sagepub.com/doi/pdf/10 … 4213477096
matthewrmarler | May 11, 2020 at 3:33 am |
Atomsk’s Sanakan: The general lack of peer review for the denial books is a common feature of the vast body of literature produced by the climate change denial community, ranging from blogs to newspaper op-eds to policy briefs from CTTs.”
https://journals.sagepub.com/doi/pdf/10 … 4213477096
Boy, what a load of junk that is! a short quote (quote mining) will have to suffice for now: Whereas scientific knowledge slowly but surely accumulates through testing, and then rejecting, modifying, and/or verifying hypotheses and theories,12 the denial literature is cumulative in the literal sense. Regardless of how thoroughly discredited in the scientific literature, denialist claims (the recent warming trend reflects a natural cycle, is the result of solar activity, won’t produce harmful impacts, etc.) are retained and reused whenever convenient. Non-peer-reviewed books espousing climate change denial offer an ideal means of presenting these claims, accounting for the growing popularity of such books. Strikingly, many of
these books not only provide fallacious critiques of climate science but also present an alternate reality in which global warming is a hoax created by a conspiracy of supposedly greedy scientists, liberal politicians, and environmentalists (McKewon, 2012).
The idea that the present warming trend is natural has been “discredited”? All of the disputations rest on (so far) untestable assumptions. Nothing yet explains the apparent periodicity in the temperature proxies, or how the recent warming is about “on time” if there is a persistent periodic causal driver.
What harmful effects have resulted from the warming so far? None. Net Primary Productivity of natural and cultivated plant stands is up (that has been published in peer-reviewed articles in Science Magazine and Nature). No vector-borne disease has increased in intensity or prevalence.
“Supposedly greedy scientists”? Do you really not understand that grant-funded scientists depend on money to pay their food bills and mortgages just the same as industry-funded scientists, and that all scientists are susceptible to money?
If that is what results from peer review, then peer review seriously needs help.
Atomsk's Sanakan (@AtomsksSanakan) | May 11, 2020 at 10:53 am |
Matthew, it’s not my job to walk you through the published literature on global warming being attributed to greenhouse gas increases (ex: tropospheric warming + deep ocean warming + stratospheric cooling that increases with increasing height + mesospheric cooling + thermospheric cooling + decreasing diurnal temperature range + decreased annual cycle + …). The evidence-based scientific consensus on this is clear; it’s clear to the vast majority of experts in this field, and it’s clear to those of us who read the peer-reviewed literature in which the evidence is discussed. The fact that you don’t accept it is no more my problem than is anti-vaxxers refusing to accept that evidence-based scientific consensus that vaccines don’t cause autism, simply because they read some nonsense on a non-peer-reviewed blog. I’m sure those anti-vaxxers will make the same sorts of evidence-free pleas as you (ex: “[a]ll of the disputations rest on (so far) untestable assumptions”), while the rest of us roll our eyes.
Atomsk's Sanakan (@AtomsksSanakan) | May 11, 2020 at 2:57 am | Reply
Re: “But I can’t find any mention of such a correction in any English source, and I can’t find any mention of these high Swedish infection rates past the 4/22 retraction of the paper.”
They apparently updated it in late April. But given their screw-up, and how implausible their results are, I wouldn’t rely on it until it goes through peer review.
“Coronavirus: Has Sweden got its science right?
[…]
That was later revised down to 26% after the agency admitted a calculation error.”
https://www.bbc.com/news/world-europe-52395866
“”A variable had been set at the wrong value and it affected the entire analysis. Now, the estimated date for the peak of the infection curve has been set at April 8 and not April 15 as was previously said. Also, in Stockholm 26 percent of residents are likely to have been infected by May 1, which is somewhat lower than the previous estimate,” said Wallensten.”
http://www.xinhuanet.com/english/2020-0 … 003043.htm
niclewis | May 11, 2020 at 4:02 am | Reply
Nonsense.
The Swedish Public Health Authority report that I cited has not been withdrawn. The article you link to is dated 22 April and relates to an early version of the report.
An Englsih version of the current report is here, BTW: https://www.folkhalsomyndigheten.se/con … r-2020.pdf
Ragnaar | May 10, 2020 at 5:41 pm | Reply
Thank you Nic Lewis. I understand the situation a bit more now.
Dr. Michael Johnson (@mkeljgt500kr) | May 10, 2020 at 5:47 pm | Reply
Excellent study and observations. In addition, my alma mater, MIT, has had their economists looking at optimum lockdown strategies, and it seems no country is paying attention……https://www.nber.org/papers/w27102?mod=article_inline
It doesn't add up... | May 10, 2020 at 6:59 pm | Reply
It looks as though Figure 1 displays clear evidence of a shortage of test capacity. This short piece from the Santa Fé Insitute explains the underlying maths:
niclewis | May 11, 2020 at 4:27 am | Reply
Yes, hence the change in the focus of testing being narrowed on 12 March, as explained in the Figure 1 caption, where I mentioned that this would explain the lack of growth in new cases during a week in mid-March. But test capacity doesn’t explain the fall in new cases, or in hospitalistions, in Stockholm since mid-April.
This report https://www.folkhalsomyndigheten.se/glo … nal-v2.pdf shows that the number of weekly tests in Sweden continues to increase, but that the % positive resutls is not increasing, which implies that test capacity limitations have not been worsening.
It doesn't add up... | May 10, 2020 at 7:43 pm | Reply
On the scaling laws that apply to population density, Santa Fé Insititute has a short introduction here:
and a rather fuller paper that suggests a functional form for adjusting R according to city populations to reflect the greater social interconnectedness of larger cities here:
I produced a chart of case density against population density of English Local Authorities as at April 30th (just before the testing regime changed, which could affect the results) using PHE and ONS data here:
https://datawrapper.dwcdn.net/K3uOD/1/
It supports the Santa Fé analysis, although I did the chart first and then went there to see if they had done anything – they didn;t publish until some days after I did.
Joshua | May 10, 2020 at 7:56 pm | Reply
IDAU –
> This is a large effect. Based on data of mobile phone social networks (8), people living in a city of 500,000 have, on average, 11 people in their mobile phone social network, while people living in a city of 5,000,000 people have approximately 15. This is relevant to disease transmission as the average contact rate is proportional to degree β ∝ k(N) (see Materials and
Methods). Therefore, we expect that initial growth rates of COVID-19 cases to be higher in larger cities (see Materials and Methods). This is what is found empirically (see Figure 1A).
What is the empirical method that prioritizes urban vs. rural setting over cultural factors (like being a rural active church-goer vs being an urban-dweller who passes a lot of people on the street but has no such regular group activity) for determining contact rate in urban vs. rural settings? Does it really scale as described?
niclewis | May 11, 2020 at 4:30 am | Reply
Thanks for the links, I’ll take a look.
niclewis | May 11, 2020 at 6:00 am | Reply
I’ve now had a quick look at the papers that you link to. They make sense to me and your graph looks impressive, although I’m not totally sure what exactly the points on it represent. Could you post a link to the data plotted, and to the source of that data, please?
If I understand your graph correctly, the fitted line implies that cases per head are proportional to population density raised to the power of about 2.3. It would be good to use bivariate regression to separate out the effect of city population (for one might also expect a positive relationship, but with a much smaller power) and pure population density.
It doesn't add up... | May 11, 2020 at 9:24 am |
The data were sourced from PHE (for the cumulative cases per UTLA) and the ONS (for populations and areas). The PHE data can be downloaded here
https://coronavirus.data.gov.uk/downloa … latest.csv
and assembled with care via a pivot table. The latest download may contain minor revisions compared with my original. I would avoid using later data than end April because of the change in testing regime, which was also probably not uniform: it is why I didn’t include Wales in the analysis, where testing has been inadequate.
The data in the chart can be downloaded by simply clicking on the “get the data” link, together with additional data on cases per million of population in each Local Authority. Care is needed if you wish to marry ONS data on areas and populations, because there are a couple of anomalies in the PHE area definitions (Bournemouth, Poole and Christchurch, The Scillies and Cornwall, and the City of London from memory)
Joshua | May 11, 2020 at 10:59 am |
What is the empirical method that prioritizes urban vs. rural setting over cultural factors (like being a rural active church-goer vs being an urban-dweller who passes a lot of people on the street but has no such regular group activity) for determining contact rate in urban vs. rural settings? Does it really scale as described?
It doesn't add up... | May 11, 2020 at 2:11 pm |
I see the ONS has just released updated population estimates that include direct data on population density and area which is a convenience not previously available (see tab MYE5)
https://www.ons.gov.uk/file?uri=%2fpeop … dcodes.xls
niclewis | May 11, 2020 at 3:26 pm |
Thanks, very helpful.
Jim Rose | May 10, 2020 at 8:54 pm | Reply
Reblogged this on Utopia, you are standing in it!.
Turbulent Eddie | May 10, 2020 at 9:06 pm | Reply
South Korea does fit the theory – too effective a lock down causes a second wave.
South Korea warns of second wave of cases as it shuts night clubs and bars
South Korea on Sunday warned of a second wave of cases as a new cluster formed around a number of night clubs, according to Reuters.
It doesn't add up... | May 11, 2020 at 9:05 am | Reply
A small outbreak is not a “wave”. The Koreans will suppress it with their well established trace and quarantine regime.
Turbulent Eddie | May 11, 2020 at 9:20 am |
RB | May 11, 2020 at 10:45 am | Reply
Let’s have some perspective here. They had 34 new cases in a day, the single largest spike recently. Contrast this with 25,000 cases per day in the U.S.
Albert | May 10, 2020 at 10:20 pm | Reply
Reblogged this on sonofbluerobot.
Kevin Roche | May 10, 2020 at 10:21 pm | Reply
Nic, thanks for following up on the paper. I have believed from the start of looking at the epidemic that there is a bucket of people who are exposed but uninfected, so in my SEIR schematic, I start with the population, then you would move it to exposed with a contact model that hopefully would have the correct age, sex, comorbidity, population density, type of residence, etc. factors, properly distributed for the population of interest. But in the exposed compartment, not everyone gets infected. Those who don’t get infected could be a dose issue (somewhere in the models, either in the contacts portion or elsewhere you have to deal with the dose issue), could be genetic variation, could be some other factor we don’t understand (more research shows smokers don’t seem to get infected as often or to have as serious and illness), not likely to be antibodies, the most recent research shows little cross-reactivity between other strains of coronavirus and this one. But from the cruise ship and other examples, there are people who are exposed but not infected. (One clear way to see this is look at the number of cases among people 18 and under in the US versus their percent of the population. And this group is estimated to have three times or more the number of contacts as other groups.) In any event, I move the exposed but uninfected group directly to Recovered, but I call that bucket Uninfected/Uninfectable, because for some reason they don’t get infected, or they have been infected and they have antibodies so can’t be infected (several papers in the last week found almost universal and strong antibody responses to infection).
Then the exposed and infected proceed to asymptomatic, which appears to be a very large cohort, mild illness, and serious illness that requires hospitalization compartments, and from their to either death or recovery.
But a bigger issue than figuring out who gets infected and what the rate of serious illness is, is that you can’t run the whole population in one model, even with the contact model adjustments noted above. This is a phenomenally bifurcated epidemic between the general population and nursing home residents and other senior living facility residents. In Minnesota, congregate care living settings, primarily for the elder, account for over 80% of deaths. Every other state has a huge percent of their deaths in similar settings, and a large number of elderly deaths are occurring at home, but to people doing hospice at home or with advance directives. Using Minnesota as an example, we have 5,600,000 residents, 80,000 of whom live in these senior congregate settings (note that skilled nursing facilities also have a younger population doing long-term rehab from serious illnesses). When I did this analysis a couple of days ago, we had 508 deaths, 407 in those settings (the pattern has remained the same the last two days)(the 407 also doesn’t include those elderly who died at home or the nursing home staff who have died). So 407 divided by 80,000 is a death rate of .51%. 101 divided by 5,520,000 is a death rate of .002%. That is a 255 times greater death rate among that congregate living group. The pattern has been the same for a long time and while there will be more deaths that creep the death rate up, the pattern will stay the same.
For the general population, there are many, many causes of death that kill more people. The models need to be run separately for the general population and the senior congregate care groups. And as you can see from the analysis above, it is crazy to have a general lockdown instead of a focus on the vulnerable. Meanwhile the CDC issued a report on Friday indicating the vaccine dose ordering was done over 3 million doses and measles alone down over 400,000 doses. Scaring the crap out of the population is making people avoid needed health care, and is literally killing children, far more children than will be killed by coronavirus. (60 deaths in the whole US to people aged 24 and under). But maybe those lives don’t count. I have a lot more analysis on all of this at my blog site, http://www.healthy-skeptic.com
Terry Jones | May 10, 2020 at 11:17 pm | Reply
thanks Kevin; should we not start to use the phrase “end of life residential homes” to describe nursing homes? One does not go into such places to get better: we are in the waiting room for the next life; these tragic folks are dying when their life expectancy suggests they will die. It will come to us all.
Don Monfort | May 11, 2020 at 12:39 am | Reply
Mr. Roche has got it right:
“Using Minnesota as an example, we have 5,600,000 residents, 80,000 of whom live in these senior congregate settings (note that skilled nursing facilities also have a younger population doing long-term rehab from serious illnesses). When I did this analysis a couple of days ago, we had 508 deaths, 407 in those settings (the pattern has remained the same the last two days)(the 407 also doesn’t include those elderly who died at home or the nursing home staff who have died). So 407 divided by 80,000 is a death rate of .51%. 101 divided by 5,520,000 is a death rate of .002%. That is a 255 times greater death rate among that congregate living group. The pattern has been the same for a long time and while there will be more deaths that creep the death rate up, the pattern will stay the same.”
My thinking is along the same lines. We know who are the vulnerable populations. We know this because they are dying grossly disproportionately. Have been all along. No need to test the whole herd. We can far more easily and cheaply just count those who need burying. Then we focus our resources and actions on protecting those populations. The rest of us go back to work, earn money, buy things, pay taxes.
cerescokid | May 11, 2020 at 6:05 am |
On the surface that should have been the most effective way to reducing deaths. A closed system with total control over who breaks the seal. It hasn’t been all of the long term facilities that are responsible for the disproportionate rate. For those states who publicize the data, it’s a few bad actors with really high cases and deaths. In some situations,
if the entire US had the same ratio of deaths to population as the worst long term health facilities, we would be losing 40 to 50 million people.
Just last night, I read a quote by a governor about plans to implement stricter controls at their nursing homes. Sorry buddy, but that should have been done early March not Mid May. We don’t need a lethal virus to know well in advance who are the most vulnerable among us.
matthewrmarler | May 11, 2020 at 11:51 am | Reply
Kevin Roche | May 10, 2020 at 10:21 pm
Good post.
Joshua | May 11, 2020 at 12:15 pm | Reply
Belongs here:
https://judithcurry.com/2020/05/10/why- … ent-916681
Joshua | May 10, 2020 at 11:11 pm | Reply
Kevin –
> Scaring the crap out of the population…
Why to you have such a low opinion of the population – as if they’re just a bunch of passive little sheep running around with no agency and who are just scared by the big, bad..what….media? government? liberals? CDC and Birx and Fauci and Redfield and Trump?
What do you expect, for the media to just not report on the tens of thousands of deaths thus far, and hundreds of thousands of his hospitalizations and debilitating illnesses for weeks? Do you expect people who are ill to just be quiet and not tell their friends and families about being infected and ill? Should the 1.3 million people identified in this country as infected just hide that news away?
Should Italy and the UK and Spain and France and Brazil and Ecuador get in on the plan to keep the news of this “plague,” as the president calls it, from the population?
Do you expect government and public health officials to just all agree to keep what’s going on a secret somehow?
People are going to be scared in the midst of a pandemic where even if the fatality rate is lower than it seems, and herd immunity is reached sooner than expected, and effective treatments are developed, and a vaccine is developed quickly and distributed, there will be maybe 130 thousand dead, and maybe 500,000 who are hospitalized, and many more taken ill for a couple weeks, over the next year?
That’s how humans are. You msy have disdain for them in their weakness – but it’s kind of inevitable, isn’t it?
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@MannockDavid | May 10, 2020 at 11:29 pm | Reply
OK, Firstly I’m not an MD or a virologist. My roots are in biological sciences/biophysics & phys chem. This is my opinion & like most reasonable people I’m open to corrections if I’m in error.
I put some info on Twitter yesterday to Willis that adds reality to what are fundamentally human geography-based statistical models without realistic infection transmission/virulence/human immune response variables. As mentioned above there are still unknowns which become estimates that don’t represent the true variables. One of those is infectiousness. It will vary not depending on geographic or social circumstances, but because of the underlying biology. On YT watch this video: https://www.youtube.com/watch?v=qwSjvIixzP8
Covid-19 may be a different virus, but many viruses have the same/similar infection route – musosa & targeting mechanisms. In the video, there’s a regional difference between N & S England & with France. N England & France included the low countries that are primarily of Norse decent, hence ‘Normans’. So where that ‘cultural’ sub-type is dominant, the infection is low/mild. The basis of this differential is ABO blood type as seen for other viruses & some cancers. For types A & B CHO antigens are on the cell surface, whereas for type O they are in the circulation. There is an extra molecule that’s ABO related (all 3 glycolipids), called the Forssman antigen. The distribution of this molecule varies by animal, by mammal, by tissue origin & by blood type. If the population is predominantly type O, then infection is low/mild, but for type A (moi) it is more prevalent with worse symptoms & outcomes. I do not know if these differ in their ability to transmit the virus. There are more blood types, B & AB plus many A & B sub-types – not Rhesus related. I’ve not looked at these sub-types presently, but they may show small differences in symptoms & central locations of infection within the body dependent on the presence of the Forssman antigen per tissue type. I have downloaded & read papers on these issues & have added links in my tweets to various govts for their experts.
Another variable is the virulence of the virus. From what I’ve said above the tissue distribution & expression of the virus varies with asst’d biological variables & consequently ethnic groups. One contributing factor seems to be vit D levels & the skin melanin content & the need for longer sun exposure to synthesize & convert Vit D3 to active form D2. Hence the recommendation to take a vit D + zinc supplement. The explanation of the mechanism of the virus disease prevention is in my twitter bookmarks, but is widely known as is the role of the Forssman antigen.
An added problem with RNA viruses is their ability to mutate. There’s a story of a patient in Wuhan who initially had 1 strain, then 3! Mutations occur at the genetic level & it’s almost pot-luck. The result is a strain that may be more or less infectious/virulent. As you can see a simple statistical model which assumes the exponential spread of the pathogen on cultural/geographic grounds may not accurately model a mutating virus in a non-homogeneous population, thus at best all that’s possible is rough approximations. This is the case with many natural phenomena, like AGW!
There’s another wrinkle in these models which is the willingness of people to follow lock down, distance. mask advisories. Basically anything that reduces transmission reduces the number of hospital cases. The idea of herd immunity is nice, but those of us who are immune suppressed (probably too many cousins marrying in my case), the more time exists to create an effective treatment. It’s not just having a healthcare system becoming overwhelmed IMHO.
From all of the above, it is apparent that darker skinned people of type A blood type with widespread FA distribution are most at risk. The final severe immune response results in organ failure. This is common to many virulent pathogens. The straw that breaks the camels back seems to be the accumulation of fluid in the lungs which reduces oxygen intake. There was recently something about a specific drug used to treat covid-19 – clot buster tPA below (MDs used this Xmas eve 2002 to save me). Many diuretics are used to decrease fluid in the lungs, as well as vasodilators.
https://www.phauk.org/treatment-for-pul … diuretics/
https://www.mayoclinic.org/diseases-con … c-20377014
https://news.yale.edu/2020/04/23/yale-l … 9-patients
https://www.nationalgeographic.com/scie … d-disease/
https://www.medicalnewstoday.com/articl … ished-uses
So the bottom line from Dr Dave is that these models are inaccurate. They are worthwhile however as there has to be a starting point to compare with real world data & later incorporation of new variables as they become known & understood.
niclewis | May 11, 2020 at 3:48 pm | Reply
Thank you for your informative comment. I am aware that, as well as social connectivity, there are biological factors involved, including blood group and vitamin D level.
The factors you refer to relate prima facie to susceptibility, not infectivity. They will likely also indirectly affect infectivity, although to a different extent. A more susceptible person presumably has a greater chance of ending up with a more severe illness and a higher viral load and be more likely to infect a contact with the virus (although the time interval between becoming infectious and self isolating may be shorter in that case).
I seek, in my simple model, to take account of variability in biological and other factors that affect susceptibility and infectivity differently through incorporating separate random variability in each of susceptibility and infectivity in addition to a common social connectivity related factor that affects susceptibility and infectivity identically. I agree that this can only provide a crude approximation, but the point of the model is to provide insight into the effects of the different types of variability rather than to attempt to provide quantitatively accurate estimates of the development of the epidemic.
Terry Jones | May 11, 2020 at 12:46 am | Reply
so the coronaviruses are part of a larger group described as respiratory viruses; their signature trick is they become evident in the cold and dark of a temperate northern hemisphere winter; they fade as spring passes, and are gone by summer.
Please read things such as this: https://virologyj.biomedcentral.com/art … -422X-5-29
and complementary reading: https://www.ncbi.nlm.nih.gov/pmc/articl … 07175a.pdf
I really recommend understanding the work of Hope-Simpson from the two articles:
So the Swedes are about a month away from the summer solstice; how many folks have visited Stockholm in mid-June? It will be close to 24hrs a day of sunlight; if the Swedes can just hang in there; and avoid the baying for their blood of angry folks like Carrick, the season will purge the air of the corona; it will disappear away; mid to late June, the Swedes will largely melt away to their little cottages by the lakes and estuaries; they can swim; take in the sun; eat fish; get omega-3 and Vit D and replete their innate immunity; and (unlike everyone else), they may have an economy to come back to.
.. whilst we will still be trying to impress each other with our knowledge about R0.
Alberto Zaragoza Comendador | May 11, 2020 at 1:30 am | Reply
It seems the FT got the numbers for Stockholm hospitalizations from here:
See page 3. The first day in the FT’s chart with week-on-week decline in hospitalized patients is April 21st, and that’s the case also in the presentation I just linked to (1,053 patients vs 1,073 seven days earlier).
niclewis | May 11, 2020 at 5:01 am | Reply
Good spot. Can you give the page on which you found a link to this report (I assume somewhere on the https://www.sll.se/ website), so that I can locate subsequent versions in due course? Thanks.
Alberto Zaragoza Comendador | May 11, 2020 at 8:26 am |
No idea about the website, but when there’s a new presentation they’ll probably post the link in the news, that’s how I found it.
https://www.thelocal.se/20200505/in-gra … -stockholm
Jonatan | May 11, 2020 at 3:24 am | Reply
Hi. This is very interesting. I made a similar analysis a few days ago, with roughly the same findings:
https://jsmp.dk/posts/2020-05-07-herdimmunity/
Would you share you code? (Or even more details of the model.) I would like to contrast and compare.
Best,
Jonatan
niclewis | May 11, 2020 at 11:44 am | Reply
Hi Jonatan
Thanks for your comment. I will certainly share my code. Once I’ve tidied it up a bit I’ll put a link to it at the end of the version of this article that is on my webpages, here: https://www.nicholaslewis.org/why-herd- … n-thought/ . But in the meantime, if you leave a comment there I’ll email you a copy of the code as it stands now.
Clive Best | May 11, 2020 at 5:22 am | Reply
However, the Ferguson20 report estimated that relying on herd immunity would result in 81% of the UK and US populations becoming infected during the epidemic, mainly over a two-month period, based on an R0 estimate of 2.4.
I wrote a simple SIR model using an effective R0=2.5, IFR= 1% in about 80 lines of Python. For a UK population of 65 million the model shows an epidemic is over in 2 months with ~500,000 deaths. So basically this is the same result as Ferguson.
However it is now emerging that the real death rate is probably lower at 0.4% so that would mean 200,000 deaths.
R is not really a dependent variable of SIR models. It is instead derived from the effective contact rate (people/day) and the infection period (days).
Lockdown efforts try to reduce the contact rate to move R below one, but this always extends the length of an epidemic and alone can’t stop it. You only need a handful of remaining cases after relaxation for the epidemic to spike again and another lockdown. This whole process can take up to one year !
and you can still end up with 92,000 direct deaths, let alone the long term damage to the economy and health of the population. However, perhaps there is a natural way out of this. I think Nic is essentially saying the same thing.
At the start of an infectious disease outbreak the probability of someone getting infected if they are a member of a large social network is very high. These are the super spreaders which force the initial reproduction rate R0 to very high values. It is no real surprise that Boris Johnson, Mat Hancock, Chris Whitty, Dominic Cummins and Neil Fergusson all got infected together as they formed part of the government’s own very large COVID/SAGE network!
However as an outbreak progresses, so the larger networks become increasingly already infected, and the remaining networks for new infections will therefore tend to get smaller and smaller. As a direct result of this gradual process, R will naturally begin to reduce, even without imposing any extra social distancing policies. R is simply proportional to the size of any network (beta) that the average infected person belongs to, so as mean network size diminishes so does R. R is simply equal to beta/g where 1/g is the infection time in days (assumed constant). When R reaches 1 the epidemic peaks (herd immunity) and then falls to zero.
Such a model seems to fit the Swedish data quite well, much better than say the UK data which has a stronger lockdown suppression.
Gerald T May | May 11, 2020 at 6:04 am | Reply
I think you’re full of crap. Look how the Chinese are dealing with this pandemic. They aren’t going for the herd immunity possibilty because there’s no indication that immunity is lasting. While the Chinese are taking this pandemic very seriously they are chuckling at our downplay and minimizing of the coronavirus. I find that a little disturbing.
KevinOC | May 11, 2020 at 6:13 am | Reply
I’m pretty sure I am out of my depth here, but I am sure the denizens will have a better understanding, but has anybody thought about the millions and millions of discarded masks, the world over, many millions of which must be saturated with the virus, ending up where every discarded human waste ends up – in the sewage, drainage, and waste disposal sites. To my mind ideal, steaming “cooking” grounds of chemical and organic stews, frequented by rats, birds, bugs, and desperately poor human waste pickers. To me, unless I miss something, this is just a Pandora’s box of mutations on hold. Are my concerns unwarranted??
Ragnaar | May 11, 2020 at 7:19 am | Reply
Assume what you say is true. It’s been true for a long time with anything like a virus. It seems to be of the body. Our bodies.
maxmbj | May 11, 2020 at 9:50 am | Reply
I don’t know who did more damage to the world, the guy that ate the bat or the guy that went to bat against Boris Johnson with self-written, 13-year-old code that he hid from prying eyes. I’m only half kidding. The power Neil Ferguson had over world leaders is quite astonishing. It’s because “SCIENCE!” — not to be confused with science — is the religion of this age led by its lab-coat-wearing Baals.
Articles like this one and this excellent comment section gives me hope that science will defeat “SCIENCE!” ultimately.
Andrey Osiatynski (@AOsiatynski) | May 11, 2020 at 3:14 pm | Reply
Yep. “Scientism” has been & continues to be one of the banes of our “modern times” for at least 50 years or so.
But, in this particular case & looking at the time-line of the NATIONAL lockdowns – I blame Conte-government’s hysterical decision (March 10th?) of #LetsLockThemALLup – that, I’d bet, had very little “scientific” and/or modelling input.
This decision & the “falling dominoes” of other governments following the suit, within next couple of weeks, seems to have been driven by 2 factors:
1/Global mass-media hysteria about “new deadly BAT-virus”
2/Conte feeling pressure to do something that would LOOK BIG & “decisive”
2B/All following “dominoes” governments feeling the same pressure + additional (“exponentially” increasing urgency of) “other countries are already doing it.”
Only Swedish government had enough trust in the competence of their top HC-bureaucrat(s) (+ Belarusian-dictator Lukashenko – probably asking his favorite physicians) to withstand it.
In this “act first – explain later” scenario – Ferguson’s model & other “scientific arguments” were (at most) supporting props.
Once the national-lockdowns became “international norm” – a deadly combo of authorities’ & media’s hype about them being “necessary & ONLY practical solution” – eliminated from public debates & in most cases, from public action any consideration of (obvious from the go in Italy) vulnerability of the elderly – particularly in the nursing homes; contagion via subways, etc.
We’re now in the later stages of this global mass-hysteria with an alliance of: HC-bureaucrats, authorities that won’t admit ANY mistakes and/or petty tyrants who don’t want to release absolute powers they got over their “subjects” as well Karen-types & in the US – “resistance” supporters who’d like the lockdowns to last until November 3rd – jointly fighting against any meaningful/substantial removal of lockdowns & return to normal.
Meanwhile, the cumulative effects on the national (& global) economies & PREVENTABLE excess deaths (delays of treatment of cancer, heart-problems, strokes, etc.) continue to add up.
In July & August of 1914 we had another case of “falling dominoes” of national governments following each other in taking most irrational & destructive possible actions – to address serious but manageable problem – leading to the government-made catastrophe of WW1.
The scope of THAT disaster could have been hugely reduced if at least a few of these governments were willing to look at what became obvious in the Fall of 1914 & changed the course then & there.
Let’s hope most of our governments will be (a little?) less stubbornly & suicidally stupid – this time.
Hifast | May 11, 2020 at 9:56 am | Reply
Reblogged this on HiFast News Feed.
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A Call for Honesty | May 11, 2020 at 10:43 am | Reply
My son noticed how the projections of countries on https://covid19.healthdata.org/ conveniently only record the latest tweaking and not the comparative projections of each – say a week apart – for the past two months. This hides how far out the previous projections have been.
nickels | May 11, 2020 at 11:20 am | Reply
Yes, I think this sort of analysis is along the correct lines.
Sadly, this whole farce has demonstrated a bunch of people suddenly discovering the exponential and losing their minds.
But nothing in nature is exponential. These 1D models assume everyone lives in the same room and that every potential is realized.
A more accurate appraisal would have to account for spatial homogeneity and would look something like a stochastic reaction diffusion equation with random diffusivity. There are far more cases where the virus extinguishes and does not have access to its exponential potential as a result. This will lower any R0 that is determined concerning people in some glass jar.
Ron Carlin | May 11, 2020 at 11:21 am | Reply
Too complicated. We are all drowning in this sort of analysis.. The simple reason why herd immunity threshold appears to be much lower than expected is that we are not counting enough of the asymptomatic cases.
ristvan | May 11, 2020 at 12:02 pm | Reply
I posted a hypothesis some weeks ago based on the data from CVN71 (Teddy Roosevelt aircraft carrier). All crew was tested. Only about 16% positive despite ideal conditions for contagion spread.
Low hospitalizations and only one fatality thanks to young age and lack of comorbidities obesity, hypertension, and diabetes.
But why the low infection rate. There are four common cold corona viruses responsible for an estimated 25-30% of common colds. Two are beta coronas like Wuhan. It is plausible that a CVN71 common cold ‘epidemic’ conferred at least partial immunity to much the crew.
In that case, NO herd immunity calculations work well because herd immunity is not exclusively specific to Wuhan. Just like Jenner’s famous vaccination discovery that mild cowpox protects against deadly smallpox.
Terry Jones | May 11, 2020 at 4:05 pm | Reply
thanks ristvan; some would say that innate immunity: (AMPs), anti-microbial peptides, destroy invading viruses in the nasal mucosa; if viruses get past the, the T-cells destroy; you could call it Level 3 where the viruses penetrate interstitial fluid or blood and provoke an antibody (IgG/IgM) response;
so when folks do serological testing, they are missing what Ron Carlin calls “the asymptomatic” and a significant % of those have proven resilient; and yet their resilience cannot be measured by our current tests. We do have some understanding of innate immunity; it attacks the lipoproteins of the enveloped RNA viruses eg our friend the corona, and so destroys them.
niclewis | May 11, 2020 at 4:51 pm | Reply
Thanks for your comment.
I agree that it is plausible that exposure to a common cold coronavirus may convey at least partial immunity to infection by the SARS-CoV-2 virus, and I was well aware of that point. Such quasi-immunity would imply that serological tests for antibodies specific to SARS-CoV-2 will undercount the proportion of the population that is immune to SARS-CoV-2.
However, my modified SEIR model can allow for this, if somewhat crudely, by virtue of the variability in susceptibility that it provides for. Immunity has an identical effect to zero susceptibility, while partial immunity implies a very low susceptibility, and possibly also a low infectivity if infected.
Anton | May 11, 2020 at 12:05 pm | Reply
Superb discussion. Thanks to Nic and all….
John Church | May 11, 2020 at 12:54 pm | Reply
Great article. Not sure how relevant this might be, but don’t forget the curious fact that children don’t seem to get ill and may very well not even transmit the virus, a topic of hot debate at the moment. If this was true it would mean we effectively have a cohort of the population that are immediately a large component of the ‘immune herd’. In the U.K. 18% of the population are under the age of 15.
It might also explain why Africa is so unscathed, contrary to the recent scientific scaremongering. As well as having a very young average age most countries have a huge percentage under 15. In Nigeria the average age is 18 and 43% are under 15.
niclewis | May 11, 2020 at 5:03 pm | Reply
Thanks. I agree that children don’t get ill, however, they certainly can become infected. It is however possible that infected children are not infectious, or have low infectivity. I think that there is evidence for that, but I’m not currently sure how robust it is.
Either way, I think that the variability in susceptibility and in infectivity that my modified SEIR model includes can provide a crude representation of the impact of the cohort of children.
A slightly more sophisticated model could allow separately for different age bands in the population having differing average susceptibility and infectivity levels.
Your point about Africa is well made. I had had thoughts on similar lines but regarding the infection fatality rate in Africa, not the effect of children on the spread of the epidemic.
Don132 | May 11, 2020 at 2:25 pm | Reply
Nic Lewis earns a mention in Lockdown Sceptics: https://lockdownsceptics.org/
gymnosperm | May 11, 2020 at 3:01 pm | Reply
Alternate possibilities for low apparent HIT.
1.We are not measuring the true I (infected) and R (recovered).
a. Lack of randomized testing
b. Poor test accuracy
2. Seasonality
a. Reduces R(t) independently of HI or intervention
b. Reduces R(o) and R(t) independently of infectious period or contact rate
pdcarey | May 11, 2020 at 3:08 pm | Reply
Yes, great analysis.
Missing from the discussion are.
1 – whether the presence of Ab confers immunity
2 – duration of immunity
3 – On reinfection of a host with measurable titres of Ab will the subsequent infection be milder or enhanced? (ADE)
In the case of influenza, immunity lasts about 9 (to 18) months. [If] protection from infection is conferred by Ab generated in a covid infection [and if] the duration of that immunity is less than the period required for R0 to drop below 1.0 [then] there will need to be a few more terms to deal with dependencies between compartments.
We’ll see.
Terry Jones | May 11, 2020 at 6:25 pm | Reply
thanks pdcarey; also missing is that maybe immunity does not depend on the presence of IgG or IgM antibodies:
.. all the clever modelling assumes that immunity=antibodies
Underpining that belief is our ignorance; this lack of knowledge then supports the idea that immunity=antibodies
We have an innate immunity system; please read this paper
https://virologyj.biomedcentral.com/tra … -422X-5-29
It may dawn on folks that things are more complicated; on flu, the above paper asks 7 questions during discussion
Why is influenza both seasonal and ubiquitous and where is the virus between epidemics?
Why are the epidemics so explosive?
Why do epidemics end so abruptly?
What explains the frequent coincidental timing of epidemics in countries of similar latitudes?
Why is the serial interval obscure?
Why is the secondary attack rate so low?
Why did epidemics in previous ages spread so rapidly, despite the lack of modern transport?
If you compared and contrasted what is happening now, and how many of these questions are relevant to what we are obsessing about now; the deepening thinking that might ensue, might enrich reflection; as we survey our ignorance of our bodies’ systems.
RiHo08 | May 11, 2020 at 3:51 pm | Reply
In the 60+ years I have been going to the Bruce Peninsula Ontario Canada, situated between Lake Huron and Georgian Bay, I have kept track of life on the Bruce as related to me by people who live there and the folks newspaper, the Wiarton Echo when I am not physically present.
The Bruce has restricted travel enforced by the Ontario Provincial Police (OPP) whereby anyone coming up has to remain and anyone traveling from the Bruce can not return. The Mayor of the Municipality had ordered no one to come up to the Bruce. All these restrictions are a result of COVID-19. Essentially, the Peninsula has self quarantined.
There had been no cases of COVID-19 on the Northern Bruce Peninsula Municipality (population 3600) until one was identified in a nursing home in Lion’s Head halfway up the Peninsula on Georgian Bay (population 600 counting all the nursing home residents).
The curious issue for me, how did the nursing home resident, in an area quarantined from all of Southern Ontario acquire the novel coronavirus? During the summer, mostly July and August, Lion’s Head is a tourist Meca with 5000+, yet in the winter, the major employer is the nursing homes in the various small towns on the Peninsula, the rest is farming, construction and a scattering of machine shops along the central corridor road Highway 6. Lion’s Head has the only K-12 school on the Peninsula (children bussed from towns 50 miles away and they stay during the school year days with relatives or foster parents in the area. There is commercial fishing using small picturesque Great Lakes fishing boats, with one located in Wiarton on the Georgian Bay and one each in Howdenvale and Stoke’s Bay on the Lake Huron side.
As the nursing home industry is a major employer, protecting these residents was foremost on the mind of the Mayor when he made is order. And yet, the virus got in and now jeopardizes those currently living in and acquiring more nursing home people. Case finding will identify how the virus traveled into the Bruce. In a region surrounded on three sides by water and an armed police presence stationed at the base of the Peninsula, is there any better quarantine situation? No need to invoke international air travel or interstate highways or mass gatherings of illegal concert goes, the virus does sneak in by a care worker, a visitor, a delivery person or a new resident from elsewhere.
On the topic of early herd immunity, the Bruce Peninsula will be a case study in the evolution of this pandemic.
Terry Jones | May 11, 2020 at 8:33 pm | Reply
Thanks RiHo08; so this virus has been doing the rounds for a long time: 108 Canadians for example went to Wuhan and spent at least a fortnight there last October; https://en.wikipedia.org/wiki/2019_Military_World_Games with 172 from the US, etc etc. The US jets flew to and from Seattle. Have a read at this https://virologyj.biomedcentral.com/tra … -422X-5-29 .. it might interest that not all viruses obey the “sick to well” rule that we would wish them to obey: well, it would mean they then obey our models, wouldn’t it, and that should be the way the world runs, right? They have now recognised it was in Paris in December; it’s been everywhere man, it’s been up and down man; look at the way flu surfaces in winter; study flu: it’s revealing; flu does not obey the “sick to well” rule: how irritating.
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Alan Cannell | May 11, 2020 at 5:24 pm | Reply
As hindsight is 20/20 we will be able to check the numbers in a couple of months time. One of the worst cases will certainly be Brazil which is extremely non-herterogeneous in terms of income, genetics, health case, habitation and pretty much everything else.
No real testing hsa been done and at best there will be some stats to check on the various factors. elderly, native Americans, blacks, community (favelas), low income, gender etc.Plus the response from both federal and local Gov.
Good news for the folk who study this, but bad news for the thousands who are suffering now.
Wagathon | May 11, 2020 at 7:26 pm | Reply
But, I’ve also heard that herd immunity is impossible without vaccinations… as we have with the measles virus, for example. Also heard that as many as 95% of the people in this country or at least significant areas of this country are covid ‘virgins’ and that while we’re currently going on 60 to 70,000 deaths nationwide there could be as many as 600,000 deaths in the next 18 to 24 months… we just don’t know. But, we flattened the curve so medical facilities we’re not overrun, tra-la, and… It’s time to get back to work. Meanwhile, the death rate in the United States is much lower than Sweden and Sweden is climbing not falling.
Bruce Hall | May 11, 2020 at 9:05 pm | Reply
This reminds me of arguments/discussions about climate models….
My model is correct even if it doesn’t reflect observations; your model is incorrect even if it does reflect observations. Why? Because observations are wrong; models are correct.
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Last edited by Void (2020-05-11 22:50:22)

SpaceNut · 2020-05-12 07:53:29

Why not compare Luxemburg or Iceland....for this herd value oh its not just isolate or social distance but how spread out your population is too start....one could compare that herd immunity to an area of a nation of similar size and density...
The social distancing only works when you slow the spread over years of the cycles in which this disease will come back...The herd immunity is built up over time...that's provided one does get any lasting immunity...

Void · 2020-05-12 08:35:52

I appreciate that you did a reply post.

I am going to argue for a somewhat optimistic notion of immunity. It is not that I consider myself very clever, it is just that to begin with some arguments about the negative, where you might not get immunity at all, seem unlikely. But I am not ready to place my money on a bet, maybe my life, depending on how things turn out.

Spacenut said:

Why not compare Luxemburg or Iceland....for this herd value oh its not just isolate or social distance but how spread out your population is too start....one could compare that herd immunity to an area of a nation of similar size and density...
The social distancing only works when you slow the spread over years of the cycles in which this disease will come back...The herd immunity is built up over time...that's provided one does get any lasting immunity...

You stated it well. But one thing I want to try to get out of the way, is how some people on T.V. keep using the common cold as an example of how you can get another cold pretty quick after being done with another.

Flue has the same perception problem.
https://www.webmd.com/cold-and-flu/qa/w … to-the-flu
Quote:

Why don't people become immune to the flu?
ANSWER
Flu viruses continually change over time. This constant changing enables the virus to evade the immune system, so that people are susceptible to the flu throughout life. This process works as follows: a person infected with a flu virus develops antibodies against that virus; as the virus changes, the "older" antibodies no longer recognizes the "newer" virus, and the person gets sick. The older antibodies can, however, provide partial protection against newer viruses.
From: Causes and Evolution of Influenza (Flu) WebMD Medical Reference
Sources |
Reviewed by Carol DerSarkissian on May 15, 2019

So, what we will want to hope for is that the Corvid-19 has not mutated into distinct strains yet. But even if it did, my bet would be that a recovered person would have some immunity even to a new strain. For how long I don't know.

Certainly we don't have a guarantee.

But at this time, the report from Sweden is that no recovered person has gotten sick again, yet.

I guess what we may see in the fall, is how Sweden then compares to it's neighbors.

If herd immunity has value, then Sweden should do better than it's neighbors. Else we are all, (somewhat) doomed.

If blood plasma therapy has no value, then that will be discovered. But someone seems to think it is worth a try.
https://www.npr.org/sections/health-sho … s-heats-up
Sounds like they have plans. As far as I can tell, blood plasma would only help from two things.
1) Antibodies exist and work.
2) Young blood effects might strengthen a weak person by making their body systems behave more like a young person.
3) Both together, might work very well. If so, then it will be less helpful to transfuse an older persons plasma into a patient.

-----

Common Cold:
https://biology.stackexchange.com/quest … ommon-cold
Quote:

We all suffer from common cold, and that, frequently. Why have we not developed immunity against it till now? By immunity I mean immunity as a species.
immunology virology virus infection immunity
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edited Oct 1 '14 at 18:59
The short answer is we do, it's just that there are so many different causes to common cold. A slightly longer and more complete answer will note that while we know immunodominate epitopes for the 100s of rhinovirus serotypes, we are still researching why viruses like RSV are not immunogenic (my bet is on NS1, possibly NS2 proteins). If no one has put up a good answer by 2100ish EST, I should be back on then to post one. – Atl LED Sep 21 '14 at 7:06

So, the above supports the idea that indeed we do become immune from one variety of cold. However...…

I did just read that our immune system does not handle colds very well. Maybe they will get to the bottom of it and get a fix for it.
I am betting that many nations will lay out a whole lot of research money for things like that now that we had a pandemic.

Yes, this is the article:
https://medicalxpress.com/news/2012-03- … colds.html

My reading of what is being offered from the upper powers to the common people is a desire to discourage.
Also, I think that there is a issue where they do not want to confess that they did not handle things perfectly.

But if Sweden and Colorado work to some degree they will eventually have to come around. On think I am quite certain of is we cannot hide in our houses for 2 more years.

Last edited by Void (2020-05-12 09:01:12)

Void · 2020-05-12 09:47:37

This is a different point of view. It is a good video. The first presenter can be understood by a person like me. Later it is easier.

I am not in rebellion against current policy, I just think it is time to start thinking how we get the best possible results for our future. It is obvious that we cannot have what we had back, until an effective vaccine is produced in mass for the public. So, we just have to pick and choose what we loose until then. (If ever).

https://www.bing.com/videos/search?q=sw … &FORM=VIRE

Last edited by Void (2020-05-12 10:35:20)

Void · 2020-05-12 11:00:56

This is an interesting treatment for the seriously ill. Not antibody treatments, just blood plasma from uninfected people.

https://www.newsobserver.com/news/state … 46006.html

Sounds good.

I think that the more these types of treatments become available, the more justified will be societies experimenting with herd immunity.

I am guessing that the plasma will be found to have that young blood effect.

Last edited by Void (2020-05-12 11:06:03)

SpaceNut · 2020-05-12 17:40:29

It’s normal for a virus to change, or mutate, as it infects people. A Chinese study of 103 COVID-19 cases suggests the virus that causes it has done just that. They found two strains, which they named L and S. The S type is older, but the L type was more common in early stages of the outbreak. At least eight strains of the coronavirus are making their way around the globe, creating a trail of death and disease that scientists are tracking by their genetic footprints. People around the world commonly get infected with human coronaviruses 229E, NL63, OC43, and HKU1.

The World Health Organization issued a warning Friday about coronavirus testing, saying there's no evidence serological tests can show whether a person has immunity as in Antibody testing uses a blood sample to determine the presence of antibodies in response to a recent or past COVID-19 infection. A positive or negative result from antibody testing alone is not enough to confirm presence or absence of infection, ongoing infection and/or long-term immunity.

As this article goes on to say that if you did not test to say you had it you then even with the antibody test still may not get a correct answer.
https://www.usatoday.com/story/news/inv … 065105001/

Something to keep in mind is that Germany is ahead of the US and some with regards to reopening but they are seeing a 3 fold occurrence of corona virus in just the last 3 weeks.

Void · 2020-05-12 18:06:12

I understand your point of view. However, I have a strong suspicion that certain powers in this nation are doing psychological experiments a this time.

But it does not matter. In a Month or two, the Swedish experiment will either succeed or fail, maybe somewhere in between. As I am half Swedish, I know how they think to some extent. I believe they have good chances of success. But the truth will become apparent by the fall for sure I believe.

Other than that their is very little purpose to argument except to lay various points of view out there, and for each of us to try to fairly think about things.

I told a relative that works for a department of health, that people were saying that there might be no immunity generated for Corvid-19, and she thought that would be highly unlikely. I have already given you plenty of examples of why it seems unlikely.

-Sweden says that no one who has recovered from it has gotten it again.

-And I am quite certain that if nurses and doctors have recovered from it we would certainly hear if they got re-infected.

But we don't know the duration of any immunity. It could be less than 6 months, or for lifetime. We don't know at this time more information required. Truth to be revealed.

The last thing I read about the fracturing, mutations of Corvid-19, is that they are still considered one strain, and immunity for one should work for all.

-----

And one very odd thing seems to stick out in all of this. The media and parts of the leadership, seem to want to terrify the public. Again a social experiment? Or is it just the money and attention for news feed? I hope that is not the purpose of it.

We will know soon enough if life is going to continue down the crapper. For now, I am more optimistic.

And it is so strange how much most of the world wants the Swedes to be wrong. Very odd.

But I will eat my words and plan to kick the bucket, if the Swedes are wrong. It just amazes me how insanely opposed most of the world is to allow the Swedes to do their experiment.

It is very odd, that there is so much effort to censor Dr. Erickson. And although I have found very occasional positive articles towards the Swedish experiment, since about 04-29-2020, virtually none seem to be being allowed through, it looks like censorship.

But we will see.

Let me ask a question. Why does flue give immunity, and we presume that Corvid-19 cannot?

Last edited by Void (2020-05-12 18:18:08)

SpaceNut · 2020-05-12 19:21:59

The disease has a protein horn to mimic to set in motion a with the potential vaccine, BNT162.

Pfizer wants to test vaccine on thousands of people by September

The rare 113-Year-Old Woman Survives Coronavirus and Warns Humanity Needs a 'New Order'

Rail worker Belly Mujinga dies after being spat and coughed at

Person should be arrested....

We have faith but do not need a church to show it but for those that did the end is sooner as 2 Hispanic churches in Queens and Manhattan lose more than 100 members to COVID-19

Void · 2020-05-12 19:56:37

I feel that your reply was reasonable.

I might ask who stands to make what $$$ from treatments?

It seems quite co-incidental, that just when May was a possible time when some herd immunity might be found in Sweden, all hell breaks loose, and the American East Coast Establishment, and the Who. Are all over it with what might be propaganda (Or not).

For the moment it smells bad to me.

I have cousins in Sweden, they are older than me, my understanding is that it is the older generation more than the young that want to continue with the herd thing, to see if it could work. I find it odd that world powers are so vehement about shutting it down. It is only one Nation of 9-10 million people.

But egg on my face in the future?

When I get puzzled I might run several theories at once and hope to find validation for at least part of one.

SpaceNut · 2020-05-13 12:44:35

While the US is trying to open many states still remain closed and very have unrest for just wanting all to wear a simple mask to slow the disease if that's possible. There is even confusion for the mask required to enter a store as some have posted that its required while others are posting signs of populous count that a store can have within it.

What's your state's coronavirus reopening plan?

Of course stores have sprouted the directional lanes of the aisle that since they are on the floor most are not seeing as they enter through the lanes to get food as they are not wide enough to maintain social distancing. As some states lift social distancing guidelines, many hesitant to return

Some would rather it be said physical distancing....

Even going to the Gym, hair salon, ect all have the unique rules for all to follow to give a sense that you would be safe in going there.

kbd512 · 2020-05-13 15:10:56

SpaceNut,

Why are there no government orders to wear masks and gloves to prevent the spread of influenza viruses?

Influenza kills 25,000 to 50,000 Americans every single year, vastly more than COVID-19 over the years, but we've never shut down the country over influenza, nor have we ordered people to wear masks and gloves, despite the fact that such supplies have been widely available to the general public at nominal cost for decades now. Globally, influenza kills 300,000 to 500,000 per year. The butcher's bill from the past two years of influenza seasons easily matches COVID-19, but all federal and state governments, Democrat or Republican or otherwise... crickets. I think it's a fair question to ask since the proponents of extending the shut down never uttered a word about influenza.

Beyond slowing the spread of infectious diseases, if prevention of hospitalizations and deaths so great in number as to overwhelm our existing health care system is the ultimate aim of the shutdown, as has been claimed, then when would America even contemplate declaring and then working to resolve our national obesity and diabetes and heart disease epidemics? Those kill vastly more Americans. If that's not placing at least as much strain on our health care system, then some manner of logical inconsistency is at play here. Sure, you can walk into a room with no mask or gloves if someone has diabetes, but the money, manpower, and resources to treat them are at least as great as COVID-19, if not substantially greater.

SpaceNut · 2020-05-13 18:56:44

Here us the act of politics http://www.msn.com/en-us/news/us/wiscon … &ocid=iehp

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