Coronavirus - worldwide spread and control

No expert, but I've heard that they have identified the antibodies (to the virus) produced by people who recovered. Once your immune system has learned to recognise this strain of the virus, and has the antibodies waiting, then you're immune for a considerable period (years). Only thing is virus's like influenza change quickly; so new strains are constantly being produced and new vaccines are required. Coronavirus is stable (Radio 4 inside science) so I can't see how there would be a new strain so soon.

Send those high profile immune people out there right now; don't even bother with protective equipment - they're immune!

 

Sven Britton, professor in infectious diseases (and also member of the Swedish ME patient organisation's scientific advisory board), highlights the need for more resources at the hospitals: equipment, staff etc, and shares his thoughts on the Swedish Public Health Authority's approach to the pandemic.

https://www.sjukhuslakaren.se/profe...iktar-nytt-ljus-pa-vardplatsbristen-i-landet/

 

"More measures are needed to curb the spread of infection"
Opinion piece by Swedish experts (virology professors, clinical virologists, researchers).

https://www.svd.se/fler-atgarder-kravs-for-att-bromsa-smittspridning

 

Article from Malcolm Kendrick's blog that may be of interest...

Article continues : https://drmalcolmkendrick.org/2020/03/18/coronavirus-covid-19/

 

Some thoughts on the Imperial College modelling paper​

I know that the findings of this paper have been discussed at length, but I thought it might be worth saying a bit more about how the model works and identifying the assumptions it makes, some which I found quite surprising.



How the model works: a simulation based on a virtual world

The authors adapted an existing simulation model used to support pandemic influenza planning. They use census and other data to create an artificial world that closely maps to Britain (and the US). They created households with an age and size structure based on census data, with an artificial school network based on numbers of children in those households. Artificial workplaces were created based on workplace distribution data and individuals are assigned to these schools and workplaces based on location and commuting distance data.

Transmission occurrred through contacts made with infectious individual either within the household, at work/school or randomly in the community (transmission in the community depended on population density). It works out that transmission occurs roughly equally across split:

— households

— school/work

— community

and this split accords with social mixing surveys.



Assumptions

· R0 = 2.4 (R0 is the number of new people each infected person goes on to infect). This is based on early Wuhan data.

· Doubling time = 5 days. This is almost certainly an underestimate (I think it comes from the influenza rate in the original model; I have heard three days quoted for SARS-COV-2)

· Symptomatic cases are more infectious than asymptomatic cases; 2/3 are symptomatic enough to be spotted for home quarantine.

· The model was "seeded" with enough infected individuals to give the number of cumulative deaths seen in the GB or US by 14 March 2020



· 4.4% of infections are hospitalised

· 0.9% of infections die

· 30% of hospitalised cases require intensive care

· 50% of intensive care cases die



This is all varied by age of infected person, shown in the table below:





The authors let these assumptions play out in the absence of any control measures (or spontaneous changes in individual behaviours). They predict 81% of the population would be infected over the course of the epidemic

The vast majority of cases occur within 3 months

This would create 510,000 deaths in GB, based on the false assumption that the health system isn't overwhelmed.

Yet at the peak, the model predicts that only 1 in 30 cases that needed one would get an intensive care bed.

Note: something doesn’t seem right about these assumptions. 0.9% mortality assumes there are enough intensive cared beds. Let’s assume there are none. Since 50% of those in intensive care are assumed to die, the maximum death rate (assuming all without such a bed die) is 1.8%. Yet we know around 3% died in Wuhan, and a higher rate still in Italy. Any thoughts on this issue?

Okay, that is the Do Nothing scenario.

Mitigation scenario (“flatten the curve”)

Control measures

The model then looks at the effect of 5 non-pharmaceutical controls measures, and there effect following the “mitigation” strategy originally adopted by the UK gov. They are, with compliance rates:

CI - case isolation in the home for 7 days. 70% comply

HQ - Quarantine of whole household for 14 days where anyone in it has symptoms 50% or household comply. 50% comply

SDO - Social distancing of those aged over 70. 75% comply

SD - Socia distancing of the whole population. 100% comply: 75% reduction in community contacts, 25% increase in home contacts.

PS - Closure of all schools and 75% of universities



Full details




Here is how mitigation plays out in the model. Note the red line of critical care bed capacity at the bottom of the graph.




Figure 2: Mitigation strategy scenarios for GB showing critical care (ICU) bed requirements. The black line shows the unmitigated epidemic. The green line shows a mitigation strategy incorporating closure of schools and universities; orange line shows case isolation; yellow line shows case isolation and household quarantine; and the blue line shows case isolation, home quarantine and social distancing of those aged over 70. The blue shading shows the 3-month period in which these interventions are assumed to remain in place.



Using the strictest combination that the authors modelled (case/household quarantine plus social distancing for the over 70 and chronically sick; no overall SD or school/uni closure) gives 250,000 deaths (see appendix table 1A). This assumes unlimited intensive care beds, even though at peak only 1 in 8 of those that needed one could have one.

I can only assume the authors made no attempt to model the real likely number of deaths to spare the government’s blushes, since they admit their assumption does not hold.

NEXT: suppression strategy. ​

 

Absolutely. And it is crucial, because as it is wrong (and it is likely that it is), it substantially brings forward the date at which the epidemic hits the NHS, and shortens all the timescales after that accordingly. Using a 5-day doubling in their seed model presumably gives the timescale they have on their x-axes. Shortening it means that the curves move rapidly to the left. What is marked as April is actually March, and so on.

I was alarmed when I saw these graphs because I realised what they have been doing. They have been waiting for the "right time", but basing that on us being about a month behind where we actually are. The Wuhan authorities didn't wait, and with good reason. They bought us time, but not time to wait.

eta: Another factor they've neglected is that it takes time for the mitigation strategies to work. Italy's experience was about 2 weeks. They [our govt] introduced social distancing with about 2 days to go.

 

I think we can be 99% sure after infection people are immune. Otherwise the infection would not resolve or there would be thousands of cases of repeat illness. There has been a case of a test going negative then positive but it is not a test of immunity and almost certainly means nothing much other than sample variation.

 

A police car was driving around the area with loudspeakers telling people that this is an emergency and that they must not leave the home unless absolutely necessary and that not doing so endangers their own health and that of others. I think this means there are concerns about the lockdown rules not being followed by everyone.

The effect of the nationwide lockdown in Italy should soon become visible in the statistics.

 

Hilda Bastian responds to John Ioannidis' Stat News opinion piece.

A rebuttal to "A fiasco in the making?"
18 March 2020
http://hildabastian.net/index.php/8-secondary/87

 

We really don't know yet whether that is the case. On TWiV this week they seemed to think otherwise, and it was possible that immunity could wane quite quickly - but I guess only time will tell.

 

Imperial college paper comment (continued from here)​

So mitigation, or "flattening the curve" looks like a very poor strategy. Note that is it involves having R0 >1, so the epidemic continues to build until it burns itself out.

Suppression strategy

Notice that this is suppression rather than eradication. And does not include testing or contact tracing. Unlike mitigation, the goal is to reduce R0 to less than 1

Crucially, suppression can keep the number of infected cases who need intensive care beds below the available number of beds within the NHS (and US healthcare system).

There is a eyeful of graphs below, which I will then take time to explain.




Graph A, black line, shows the "do nothing" scenario, as before. But this time, more control measures are used, including school and university closure and social distancing for the entire population (orange and green lines). Although it doesn't say so, the green line does seem to include household isolation/quarantine as well as case isolation (so if one person gets sick their whole household isolates). Graph B just zooms in on the lower portion of graph A.

Assuming an R0 = 2.4, deaths could be kept under 40,000, and under 10,000 if there is almost no relaxing of any of the measures. That is very different from the >>250,000 deaths predicted by modelling of the mitigation strategy.

The light blue shading indicates a period of five months when these control measures are in place. The right hand side of the graph shows that when that those control measures are released, there is a new and very large peak of infections. In fact, the more successful the suppression in the first stage (green line more effective than orange line), the bigger the subsequent peak when controls are released. This is because most of the population hasn't been exposed to the virus so as soon as controls are released a full-blown epidemic kicks off.

And what that means is that control measures need to be kept in place to keep a lid on things.

Because these onerous control measures could be in place for two years, the authors have simulated a situation where population-wide social distancing and school/university closures are relaxed whenever there's plenty of capacity with the NHS. The idea is that giving people a break allows the control measures to to stay in place over a much longer period of time (though also stops a really tight squeeze on infections).

See figure 4 below.





Note that despite the waffle from the government in the UK, it is rapidly move from the mitigation strategy to suppression, and from this weekend effectively school closure will be in place along with a lot of social isolation for most people. The big problem is that the government was messing around the several weeks and, as a result, the NHS is likely to be overwhelmed pretty soon, though will hopefully gain back control.



As before, this is a suppression strategy and not an attempt at eradication, which was not considered in the model.

 

I thought they were turning a corner but new cases today were 4207.
The previous 4 days were all in or around the 3500 mark.
I am not sure what the expected exponential rate is without any measures, but taking the last 5 days new cases are up 20% over 5 days which doesn't seem too bad.

 

What China’s coronavirus response can teach the rest of the world - https://www.nature.com/articles/d41586-020-00741-x

Coronavirus: three things all governments and their science advisers must do now - https://www.nature.com/articles/d41586-020-00772-4

 

Yes there seemed to be some hope a few days ago but now the trends are again not looking good, although at least less bad than before.

It's still early to see the effects of the nationwide lockdown on nationwide statistics.

I was curious and looked at official data and noticed that the Veneto province is testing much more aggressively than some of the others. The deaths/positive cases = 0,032% in Veneto, while in Lombardy it is 0,135%.

Lombardy has 16.220 total cases and done 46.449 tests, while Veneto has 3.214 total cases and 40.841 tests.

http://www.salute.gov.it/imgs/C_17_pagineAree_5351_18_file.pdf
http://www.salute.gov.it/imgs/C_17_pagineAree_5351_20_file.pdf

 

Some may be correct :

https://www.ft.com/content/859e9336-68db-11ea-a3c9-1fe6fedcca75

 

Yea I think I heard 2. days as the doubling time --- 3 days I guess is just 2.5 rounded.

 

Are there any official government reports with info age/sex/comorbidities of all cases and deaths? Cause Italy should have a lot of data by now and I haven't seen much it on social media, only anecdotes.

 

I'm over 60 and have hypertension (treated with varying success with tablets). However, I seem to have the type of ME with an overactive immune system - I rarely catch anything.