Testing resources are in short supply, so testing is being performed to guide clinical decisions (ie sick people) rather than public health/science (ie random sample).
The handful of serosurveys that have been performed have been quite valuable, but there aren't nearly enough.
Hopefully this changes as testing capacity ramps up.
- SARS started out with a similar <4% estimated fatality rate and was then revised upwards to anywhere from 9-15% later.
- COVID-19 is caused by a different strain of the same virus as SARS.
- The CFR of SARS and COVID-19 appear to be very similar, and more notably, appeared by be very similar when we had around 8,000 infections which is where SARS ended. (Similar meaning the CFR hovers between 4% and 20% of closed cases.)
How are we so sure that this is any less deadly than SARS?
The above suggests to me one of the two is likely to be true:
1. There could have been many more undetected cases of SARS than we knew about, indicting an IFR much lower than it's recorded CFR.
2. COVID-19 could actually end up having an IFR that is similar to SARS (~10%).
But of course, I am no epidemiologist, so I assume there's a flaw in my logic.
Did I miss something, or is this pretty much the same disease as SARS but with a higher R0?
There's little to no data that backs up your guess.
Studies on COVID-19 estimate that the true IFR is somewhere between 0.1% to 0.39%...why? Because the more we test, the more we find asymptomatic and mild cases. And we're yet to even do the type of serological testing that would give us such a decisive sample. Yet we're ALREADY seeing data that suggests that the IFR is lower than SARS and asymptomatic cases/transmission are common. [0]
I never read anything about SARS being mild or asymptomatic in the majority of patients...in fact it was the opposite. It was so severely symptomatic that the virus killed itself with natural selection. If you had SARS-COV-11 and exhibited high viral load, you were likely too sick to go spread it. The only serological testing they did on SARS-COV-1 deemed asymptomatic cases to be uncommon [1]. Quite the opposite of COVID-19.
The main study which backs up his guess is the report from the WHO's trip to Wuhan, where they actually did what was suggested above and mass-test random samples from the population, finding a very low incidence of positives. Personally I would find the WHO on a trip to China as not the most reliable of sources, so take it with an enormous grain of salt. But it's one data point.
Meanwhile, your link in [0] flat-out says we don't know the percent of asymptomatic cases. It is well-documented they exist. I have also seen some papers estimating the percent of cases that are asymptomatic as well under 20%, and as high as the 80-90% range, the difference between them making an enormous difference to the implied mortality rate.
A month ago, people pointed to South Korea's 0.5% fatality rate, a country which tests very aggressively, as an indication that the true fatality rate is much lower. Well, they still test just as aggressively, and now their mortality rate has risen to 1.96%. The disease started spreading in a population that skewed young there, and but now the disease has started to hit older demographics who have a much higher mortality rate. And of course, "asymptomatic" cases can also mean pre-symptomatic cases, as happened with the Diamond Princess, which had an observed 46% of positive cases be asymptomatic...only to have this rate fall to ~17% later.
Yeah basically the extreme correlation of mortality with age makes it hard to state a mortality rate. Small changes in the population age distribution create big changes in mortality.
I’ve seen these reports but I don’t understand the math. The true simple CFR meeting actual deaths as reported over actual cases as reported should be adjusted for the course of disease which would make it in places like Italy well over 10% and in other places perhaps 4-6. % or more and we know China’s data, the only place with a major outbreak where it’s really run its course, is bullshit. How do you get to 0.1%? Maybe I’m missing something here but you’d have to believe there were probably 50-100 times the Number of reported cases that were actual cases which would mean the US would have to have had 50-100 million people already have contracted the disease but 98-99 pct of them had no idea. I’m not seeing that as a passes the smell test possibility. But again maybe I missing something here.
I am not convinced that this data is conclusive yet.
In two closed environments where everyone was tested, the Diamond Princess and the Washington Choir, the CFR is currently 1.55% and 4.44% respectively, with still cases in critical condition.
Of courses both populations are older, but it seems safe to say that the IFR is much higher than the numbers you quoted for older populations.
What your safe to say claim misses however is that the CFR drops off dramatically below a certain age, and very dramatically, especially if you compare between people in their mid 40s and blow to people in their mid-60s and above. Thus, your own mention of the populations of both cruise ships heavily tending towards elderly passengers (and infected) would almost certainly skew the CFR very strongly upward, and even with this upward skew, it's still so far resting at a fairly moderate 1.44% in the case of the Diamond Princess. As for the Washington Choir, not sure of why its CFR is almost three times higher, perhaps more of the passengers were older than in the DP? Either way a look at all current aggregate data on fatality counts by age from nearly any region of the world you'd like to look at clearly shows that same near drop off a cliff as soon as you reach age groups below 60.
Agree for the most part, especially with the claims with respect to SARS having a higher IFR
However, given the high R0 and still somewhat high IFR for older populations and even a relatively high IFR compared with the flu IFR for younger populations this virus still has the potential to wreak havoc.
What we are seeing is that a disease with a high R0 can be much more deadly than a disease with a lower R0 and higher IFR.
I think there are also several issues that are causing the reported CFR to be understated, that counteract to some degree the “denominator problem” from undiagnosed mild cases. The one that I think is the most important is the simple understanding of cohort analysis which I just don’t ever see explained or included any calculations. The number of cases is rising exponentially, and there’s a six week course roughly to the disease, so the number of deaths at any point in time is six weeks behind the number of diagnosed cases at any point in time and the number of cases is increasing exponentially, so this seems like a big error. I have to say I’m truly surprised by how we are this far into this thing and it doesn’t seem like anybody has even done some of the basic mathematical maneuvering you would need to do to understand this or at least they haven’t done that and explained it very publicly.
> Did I miss something, or is this pretty much the same disease as SARS but with a higher R0?
Yes, SARS-1 and SARS-2 (Covid-19) are more similar than not. But debating IFR, CFR or R0 with the testing data we have is pointless.
You can learn a lot about the nature of SARS-1 by reading about the 2002 warzone in Toronto hospitals, which wiped out whole ICU teams. Sounds just like corona today in Italy or NY.
I really appreciate this answer, and as a lay person, it helps me put some pieces together in my mind. I suspect there are at least four reasons for testing, and they all benefit from better results, but two of these need good quality unbiased general statistics, and the other two only need high confidence negative/positive results for specific cases:
- Policy makers weighing the strategic pros/cons to orders for the public
- Individuals (either frightened or skeptical) weighing their decisions
Follow up question: are you guys seeing a drop in norovirus, rotovirus and D&V? I would expect social distancing has reduced opportunistic infection rates: no swimming pools, less interactions at large.
I have anecdotal evidence from a hospital saying that wards usually reserved for norovirus and C. difficile at this time of year have not been required this year due to the lack of those infections.
We clearly saw this coming. In fact, in 2006 President Bush signed “National Strategy For Pandemic Influenza, Implementation Plan”, Homeland Security Council, May 2006. As an epidemiologist, what do you think went wrong? How come we are caught off guard?
Here is a comparison of our policies and fight against the Spanish flu and Covid-19. Remarkable how stay-at-home and social distancing policies worked then too. https://thepeel.news/stay-at-home-orders-worked-a-century-ag...
My grandparents were dating at the time of the Spanish flu. They lived in a little town in the middle of Iowa and practiced social distancing by having their dates at my Grandmother's home, doing quilting, instead of socializing with others.
It strikes me that R0 could be a very rubbery figure because surely it's dependent on the social setting. An R0 of kids crawling over each other in a kindergarten must be different to an retired estate where most people spend their time in their own house.
The final R0 is I guess is how all those values average out in a society. Is it normal for all the different societies around the planet to have the same values?
R0 is the expected number of cases generated by one infected case in a susceptible population. Usually derived through mathematical models, it is not a measure / rate of transmittablity or infectivity of the pathogen, but an indicator used to predict severity: R0 <= 1 implies the disease is endemic, otherwise; an epidemic.
R0 is dependent on parameters taken into consideration and the model itself. R0 makes sense only in the context laid out by the model.
> An R0 of kids crawling over each other in a kindergarten must be different to an retired estate where most people spend their time in their own house.
Do you have any insight into the validity of the Nasopharyngeal covid19 PCR test? I suspect I got a false negative. Get to have a "conversation" with HR tomorrow since I am essential.
When the clinical demand wanes, I hope there will be extensive antibody testing in various regions to do a comparison between how many people actually got it vs. how much damage it did. If, as I suspect, there are significant differences (ex: almost everyone in this town seems to have the antibodies, but nobody died, vs. a third of these people have the antibodies, but a lot of people died), we might be able to learn things such as which public policy decisions mattered most and maybe even which ethnicities are more vulnerable or resistant genetically. If a genetic variation is found, it might even lead to a new generation of preventative therapies that go beyond vaccines to shield people against viruses that don't even exist yet.
There are a million reason for differences like that, without studying the problem extremely carefully, you'll never know which of those reasons was consequential. For instance, more people may die in a certain city because there is more pollution in the air, or the concentration of fluoride in the city's water supply is higher, or maybe that city houses a large meat packing plant and an abnormally large number of residents had to roll the dice and work throughout the lockdown. The number of possibilities are nearly endless, and you'd need to eliminate them prior to drawing any conclusions.
Even ethnically, you can't really draw any conclusions. Were people of this ethnicity or that ethnicity more likely to be essential Walmart stockboys than others? That one little detail can have an enormous impact on medical outcomes depending on the contagiousness of a pathogen like covid-19.
To draw any reasonable conclusions, you'd really need far more than just a comparison between regions, because the different regions have such different public health needs and environmental realities. You'd even need more than a simple comparison between ethnicities. You would need to go wayyy more deep. But I can guarantee that researchers will dig deep to find anything that can be used attack similar pathogens in the future.
I'm convinced this is my aliens theory, but I do think pollution plays a big role. My hypothesis being that long term exposure to high pollution is akin to chronic asthma.
Fits in Italy, as their elderly are retired locals exposed to their terrible air for life. In China, the hard hit had a transient population that moves away on retirement. In New York, it is hitting more men, who are proportionally more likely to with outside jobs such as construction. That is to say, all of the hard hit groups had long term exposure to pollution.
And again I stress. I view this as my conspiracy theory. Really want to not believe it.
Firefighters have an inordinately high rate of lung cancer, even though comparatively few smoke (as their job comes with physical fitness requirements). This rate of cancer is believed to be tied to regular smoke exposure.
On a lower, slower timeframe I wouldn't be surprised if pollution had the same effect re: weakening the lungs.
As I said, test for antibodies. Put the "who's more likely to work at Walmart" speculations aside and start with, "Of the people who were provably infected, how likely were they to die?" question. If there are large differences, then look at age (for sure), prior health factors, gender, ethnicity, etc., to see what (if anything) made the virus not matter, and consider whether there might be other ways (besides vaccination) to make future viruses (prob some category) not matter to anyone.
Can surveillance testing not be done using standard laboratory reagents (ie not FDA approved)? (I suppose the rather invasive sample collection protocol might pose a bit of an issue though.)
Preliminary results and conclusions of the COVID-19 Case Cluster Study (Gangelt municipality)
Prof. Dr. Hendrik Streeck (Institute for Virology)
Prof. Dr. Gunther Hartmann (Institute for Clinical Chemistry and Clinical Pharmacology, Speaker of the Cluster of Excellence ImmunoSensation2)
Prof. Dr. Martin Exner (Institute for Hygiene and Public Health)
Prof. Dr. Matthias Schmid (Institute for Medical Biometry, Informatics and Epidemiology)
University Hospital Bonn, Bonn, 9 April 2020
Background: The municipality of Gangelt is one of the places in Germany most affected by COVID19 . It is assumed that the infection is due to a carnival session on 15 February 2020, as several people tested positive for SARSCoV2 in the aftermath of this session. The carnival session and the outbreak of the session are currently being investigated in more detail. A representative sample was taken from the community
Gangelt (12,529 inhabitants) in the Heinsberg district. The World Health Organization (WHO) recommends a protocol in which, depending on the expected prevalence, 100 to 300 households are randomly examined. This random sample was coordinated with Prof. Manfred Güllner (Forsa) to ensure its representativeness.
Aim: The aim of the study is to determine the status of SARS-CoV2 infections (percentage of all infected persons) in the community of Gangelt, which have been and are still occurring. In addition, the status of the current SARS-CoV2 immunity shall be determined.
Procedure: A serial letter was sent to about 600 households. In total, about 1000 inhabitants from about 400 households took part in the study. Questionnaires were collected, throat swabs taken and blood tested for the presence of antibodies (IgG, IgA). The interim results and conclusions of approx. 500 persons are included in this first evaluation.
Preliminary result: An existing immunity of approx. 14% (antiSARS-CoV2 IgG positive, specificity of the method >.99 %) was determined. About 2% of the persons had a current SARS-CoV-2 infection detected by PCR method. The infection rate (current infection or already been through) was about 15 % in total. The case fatality rate in relation to the total number of infected persons in the community of Gangelt is approx. 0.37 % with the preliminary data from this study. The lethality rate currently calculated in Germany by Johns-Hopkins University is 1.98 %, which is 5 times higher. The mortality in relation to the total population in Gangelt is currently 0.15 %.
Preliminary conclusion: The lethality calculated by Johns-Hopkins University is 5 times higher than in this study in Gangelt, which is explained by the different reference size of the infected persons. In Gangelt, this study covers all infected persons in the sample, including those with asymptomatic and mild courses. In Gangelt, the proportion of the population that has already developed immunity to SARS-CoV-2 is about 15%. This means that 15% of the population in Gangelt can no longer become infected with SARS-CoV-2, and the process has already begun until herd immunity is achieved. This 15% of the population reduces the speed (net reproduction rate R in epidemiological models) of a further spread of SARS-CoV-2 accordingly.
By adhering to strict hygiene measures, it can be expected that the virus concentration in a person infected can be reduced to such an extent that the severity of the disease is reduced, while at the same time immunity is developed. These favourable conditions are not given in the case of an exceptional outbreak event (superspreading event, e.g. carnival session, après-ski bar Ischgl). With hygiene measures, favourable effects with regard to total mortality can be expected.
We therefore expressly recommend implementing the proposed four-phase strategy of the German Society for Hospital Hygiene (DGKH). This strategy provides for the following model:
Phase 1: Social quarantine with the aim of containing and slowing down the pandemic and avoiding overloading critical supply structures, especially the Health care system
Phase 2: Beginning of the withdrawal of quarantine while ensuring hygienic conditions and behaviour.
Phase 3: Lifting of the quarantine while maintaining the hygienic conditions
Phase 4: State of public life as before the COVID-19 pandemic (status quo ante).
"By adhering to strict hygiene measures, it can be expected that the virus concentration in a person infected can be reduced to such an extent that the severity of the disease is reduced, while at the same time immunity is developed. These favourable conditions are not given in the case of an exceptional outbreak event (superspreading event, e.g. carnival session, après-ski bar Ischgl). With hygiene measures, favourable effects with regard to total mortality can be expected."
This is the most interesting part of this and should be discussed more. There seems to be a lot of evidence that viral load is a factor. If social distancing and proper hygiene doesn't just lead to less infections but to more mild infections that's a big dea.
My understanding is that viral load is always a factor for every virus. Laboratories don't use soap and water, because they want to kill 100% of the viral particles, not 99.9%. They work with samples that have extremely high concentration of viral load.
Everyone on the Diamond Princess was checked. That's why it keeps being cited as a closed population with statistically valid sampling (100%). It's the re-projections from that ship onto the age range of the general population that yields low fatality rates comparable to flu.
If you don't test a patient that's positive and put them with other patients and unprotected health personnel you'll infect others and significantly weaken the hospital's ability to treat patients. If you don't test a patient that's negative and put them with covid patients they risk getting infected, taking up an extra ICU spot, and might die. Would you want one of your loved ones in that position?
What would change in public policy with more randomized tests?
Do you know what's even worse for the hospital's ability to treat patients? If the city continues to operate normally until the number of cases is so large that it's obvious the outbreak is unmanageable even without testing.
Randomized tests would have told policy makes exactly how fast this spreads, even in Western cities. Lockdowns would have happened earlier. The total number of infected would be 1-2 orders of magnitude lower. Hospitals would have been better off.
>Would you want one of your loved ones in that position?
I wouldn't want one of my loved ones to die because my civilization was so short-sighted that it let a disease run rampant. Your appeal to emotion is garbage, and it doesn't even make sense, since all of our chances would be better if we'd known what was going on.
A full nationwide shut down without waiting for individual states to shockingly have the same issues as every other state was one possibility.
By comparison many ill people are currently being told to stay home until they have difficulty breathing, making tests have minimal clinical value. Especially as the risk of false negatives are significant.
* PCR tests to check if you are carrier of the virus right now. That's what you do with patients and personnel.
* Anti-body tests to gauge the number of people having been exposed to the virus in the past.
It takes a couple of days to develop anti-bodies so you don't want to use that one for the first use-case. And you can have anti-bodies without carrying the virus. (Well, it depends on the type of antibodies)
If you know the exposure in the general public, we would better know the real mortality, how far we are with herd-immunity, and if general quarantines do make sense, or it might be sensible to be more selective.
Hard to make this decisions in smaller contacts when you are potentially endanger real patients needing care right now Vs future "less dead" estimations.
Health systems deal with scarcity on a daily basis. There's no room for the emotional hand-wringing you're describing. Moving scarce resources from diagnosis patients to studying the population during a pandemic will be one event in a causal chain that results in deaths. It also prevents the outbreak from spreading beyond control.
Several orders of magnitude more people have been killed by uninformed policy than would have been killed by redirecting a portion of tests. What kind of MONSTER chooses for so many more people to die?!?
At this point do we even need to test most of the serious cases. if it walks like a duck, quacks like a duck, coughs like a duck, it's a duck. Didn't China start counting cases based on CT scans at one point too?
Testing resources are in short supply, so testing is being performed to guide clinical decisions (ie sick people) rather than public health/science (ie random sample).
The handful of serosurveys that have been performed have been quite valuable, but there aren't nearly enough.
Hopefully this changes as testing capacity ramps up.