8 ms·

Here are my observations as an actual epidemiologist: 1) Quarantine / non-pharmaceutical interventions effects start to be visible after about 2 weeks from the

Here are my observations as an actual epidemiologist: 1) Quarantine / non-pharmaceutical interventions effects start to be visible after about 2 weeks from their introduction, and are fully effective after 1.5 months. 2) Daily new deaths growth lags from daily new cases growth about a month (which is somewhat obvious, but needs to be reiterated). So, unless some new mitigation measures are going to be introduced _right now_, this record-breaking growth will continue for quite more than a few weeks, followed by the corresponding growth of deaths a month later. We are far away from the saturation point and any resemblance of "population immunity".

ghiculescu 6y ago
#2 isn’t obvious to me. Can you explain why?
- hef19898 6y ago
  Bluntly put, it takes time to die from any disease.
- heavyset_go 6y ago
  It takes about two weeks for symptoms to arise and become severe, and then about another two weeks of severe symptoms that require ventilators before people die.
  - jupp0r 6y ago
    The pre symptomatic time wouldn’t be part of this gap unless the infected person got a test before symptom onset, which I believe is rare (most people who test positive get tested after they develop symptoms)
    - SketchySeaBeast 6y ago
      No, these measures affect new cases, not the already ill - so you've got to build in those 2 weeks to display symptoms for those people who would or wouldn't now be infected.
      - jupp0r 6y ago
        It’s new cases. Those are people that have tested positive. This usually happens days after the actual time they have been infected. At the time of infection, you’d test negative because it takes time for viral replication to increase viral load to levels that are over thresholds used in the PCR testing process.
        SketchySeaBeast 6y ago
        But we're not talking testing negative, are we? We're talking those people showing up in the system (the > 2 week lag in time it takes to change course), or did I miss a level of questioning that threw this off course?
        jupp0r 6y ago
        The original question was what the delay between “new cases” and “new deaths” charts was.
    - emn13 6y ago
      If you look at the graphs side-by side for areas with clearly defined peaks (I looked at MA, NY, Italy, Spain, UK, Netherlands) the peak fatality rate is no more than a week behind peak case numbers, and perhaps less. Testing rates in at least some of those areas were fairly constant around the peaks, so that doesn't seem a likely confounding factor. I'm not sure what to make of the meaning of such a short gap, and of course people may now be testing earlier than they did in the early hot spots, so I'm not sure if this has any predictive value.
      - heavyset_go 6y ago
        Testing in the beginning lagged significantly from the initial infection.
      - rsynnott 6y ago
        One caution about those numbers; many/most sites show cases based on the day that reporting was received and aggregated, _not_ on the day it was taken. This doesn't matter very much now, as turnaround on tests in most places is quick. But a couple of months ago delays of weeks were common.
    - rsynnott 6y ago
      People are far more likely to be tested before symptoms today than a few months ago; at least in Ireland when a case is detected everyone they've had contact with is tested, and some of those will be pre-symptomatic positives. And then anyone _they've_ had contact with will be tested and so on.
- jupp0r 6y ago
  It takes time to die from this disease and time for that death to show up in the official numbers.
- mononcqc 6y ago
  The time for symptoms to show up is of roughly 2 weeks but the median time is at about 6-8 days. After symptoms show up, it takes a while before people get hospitalized, and then mortality seem to take roughly 21-24 days after hospitalization. This means that from the time someone is infected until they die, a month and a half can have gone through. By the time you take new isolation measures, you have to wait roughly two weeks to see if daily infection rates start to vary. But the lethality at this point, assuming no change in healthcare system overload, can be more or less statically predicted for weeks after the fact. Those are called "lagging indicators"; the main thing you try to prevent are deaths, which you can lower by reducing the overload on the healthcare systems, which you can lower by controlling infection rates and keeping them low. Due to the duration of the disease's evolution, you get to see if your policies really worked more than a month and a half after enacting them, which is extremely slow for a disease that propagates at exponential rates. So people look for proxies like infection rates that are still lagging, but far less so. Do note that the one good metric you want in the end is going to be "excess deaths", which counts the impact of not just the diseases, but of all other side issues that the disease may have caused. This can usually take months up to years to properly account and analyze.
  - ghiculescu 6y ago
    Yep. That was obvious. Thanks!
    - jacquesm 6y ago
      I don't understand. If it wasn't obvious before then it can't be obvious now. You've had it explained to you. If it was obvious then that would not have been necessary.
      - s1artibartfast 6y ago
        Sometimes I will look all over for my keys, only to find them in my pocket. This is the obvious place to check first, but I am not perfect, so sometimes I overlook it.
    - 6y ago
emiliobumachar 6y ago
Thanks for the info. Could you, or anyone else, please explain why quarantine takes 1.5 months to be fully effective?
- atemerev 6y ago
  Because there is an incubation period, where people already infected start to develop first symptoms. There is a development period (from the first symptoms to the point where they are severe enough for the person to seek medical help — only at this point the case is registered). The introduction of quarantine measures is not immediately effective — there is a transition period of at least few days. There are response / case registration delays. And finally, it takes some time for the new epidemic regime just to be visible on the curve (a perceptive delay until the trend is understandable).
  - telotortium 6y ago
    Do you have an estimate of the number of days for each of the delays you mentioned?
m4r35n357 6y ago
Presumably downvoted because of your qualifications?
IAmGraydon 6y ago
> Here are my observations as an actual epidemiologist In your recent posts, you’ve said that you just applied for your PhD, that you are a “consultant software engineer” in finance, that you are studying physics and that you have a masters in CS. You really must be a renaissance man.
- yardie 6y ago
  My former roommate graduated double majoring in Physics and CS. I don't see the problem of people having studying multiple disciplines.
  - brobdingnagians 6y ago
    Yeah, a guy upstairs from me was on a path to get an MD and a PhD in microbiology, I think he was majoring in something else as well. Unusual, but it exists. Some people really like being students.
    - yardie 6y ago
      Especially the case for rich young woman from the Middle East*. As long as they were in school they were free of family obligations. That 4 year BS turned into a 8-10 year BS-MBA-PHD track. If school ever truly finished they’d be back home to SA in a niqab.
- atemerev 6y ago
  https://www.unige.ch/medecine/isg/en/staff/alexander-temerev/ https://www.unige.ch/medecine/isg/en/staff/alexander-temerev... (All opinions here are of my own, not of my faculty or the university).
  - acqq 6y ago
    And: https://reactivity.ai/#about https://reactivity.ai/#about Edit: to respond to the question below, it clearly supports a "renaissance man" question by IAmGraydon above: it confirms both a "“consultant software engineer” in finance" and a "masters in CS." I don't see how it is not relevant. Moreover, it's not that somebody questioned atemerev's posts based on his qualifications, it's atemerev who claimed to be "an actual epidemiologist" in his first sentence, and that it definitely something that can be tested for veracity, if atamarev wanted to give more credibility to his claim with that (he didn't have to do that -- and then his claim could be evaluated on its own too, but biases by the authors of some claims are also something that could be questioned). Anyway, in this case, it's obvious that atemerev's university degree isn't in epidemiology. Edit2: atemerev's first claim: "an actual epidemiologist" now gets to be closer to the truth in the response below as "an epidemic modeler." I still believe IAmGraydon was right to question the claim, and that the initial claim was indeed misleading and incorrect.
emn13 6y ago
On number 2: that makes a lot of sense; yet in places that have had peaks (e.g. new york, italy, UK, spain) the peak observed fatality moment is barely shifted vs. the peak positive testing moment - maybe more like a week or so, normally? In all the data it's a little hard to spot trends, especially with testing rates scaling up, but still the graph peaks are not even close to a month apart, even where testing rates don't appear to be too variable. One comparison: https://datagraver.com/corona/#/?regions=italy:hex005FA2,spain:hex7FAB60,united%20kingdom:green&logScale=false&perCapita=true&cutYaxis=true&cumulative=false&types=1,2,4,3&mappingType=date&mappingMaxDays=120&mappingStartNumber=100&mappingNumberStyle=absolute&mappingEventType=lockdown&mappingDate=2020-3-1&smoothening=undefined&description=Tool%20for%20comparison%20on%20Covid%2019%20development%20for%20countries%20and%20regions https://datagraver.com/corona/#/?regions=italy:hex005FA2,spa... Massachusetts has fairly well defined peaks too: https://covidtracking.com/data/state/massachusetts https://covidtracking.com/data/state/massachusetts What's causing this discrepancy? Clearly the disease progression isn't that fast, so... what then? Maybe the more vulnerable groups tend to get hit more quickly, and as cases ramp up either die earlier or lock down more rigorously or both, such that the less-vulnerable form an infection peak after the death peak has passed? Or is it simply that people get tested late in the disease progression? Given how little the MA testing rate has varied, and that the positive rate peaks also are much closer than a month apart from the fatality peak, I don't think testing changes seem likely to be a primary cause of the (to me) unexpectedly short period between case peak and death peak.
- lubujackson 6y ago
  The big difference is testing capabilities. All places hit by big waves early on suffered from poor testing and public awareness, so testing happened in a burst as the deaths were starting to become problematic. And generally those getting tested at peaks were the symptomatic/hospitalized. NYC is estimated to have been around 20% infected, so the actual infection count was highly undereported. It is important to also recognize that every location hit hard was met with immediate lockdown, generally followed well by scared populations. The situation is far different now, with a good chunk of people actively rejecting even basic distancing measures. If you look beyond positive test numbers at the % positive you can see the rates are rising even faster beyond our testing capabilities. And the idea that only 20-30 year olds are getting the disease is wishful thinking - the highest risk situation is from household transmission, at over 80% likely. Combine high infections with a general disregard of safety and those older populations are bound to be infected as young spreaders interact with their families, at offices, supermarkets, etc. I think this is why the death spike lags a fair bit further than expected.
ramraj07 6y ago
How do you explain the "sudden drop" in cases in new York [1] after reaching some 25% infection rate? Do you think herd immunity (ish) can be reached at a lower saturation rate possibly? [1] https://www.nytimes.com/2020/05/20/nyregion/hospitals-coronavirus-cases-decline.html?smid=tw-share https://www.nytimes.com/2020/05/20/nyregion/hospitals-corona...
- belltaco 6y ago
  That seems to fit into the theory that quarantine lockdown measures are most effective after 1.5 months.
  - guscost 6y ago
    It also fits (perfectly) an alternate theory that the population exhibits a wide variation in susceptibility, which lowers the herd immunity threshold. https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v3 https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v...
  - nradov 6y ago
    What is the basis for that hypothesis?
    - belltaco 6y ago
      That it takes that long for this cycle to die out --> (infection, exhibiting symptoms, infecting close contacts(who start this same cycle again), becoming unable to infect others)
guscost 6y ago
> So, unless some new mitigation measures are going to be introduced _right now_, You will be able to claim that any changes made by local and state governments in the next few days/weeks “did the trick”. Nevertheless, this is a fair escape hatch when the following prediction does not come true: > this record-breaking growth will continue for quite more than a few weeks, followed by the corresponding growth of deaths a month later. We are far away from the saturation point and any resemblance of "population immunity". You will be proven wrong, both about the coming “wave of death”, and about how far we are from the saturation point. I’m quoting this and publicly disagreeing today, so that you might remember later on, and maybe even acknowledge that you got it wrong.
- elipsey 6y ago
  Hi. I read the essay "Pandemic Woo" which is linked in your profile. Is seems like your position is that: --COVID response strategy based on invalid "post-modern science", --the conclusion that the disease death rate is order of one percent is incorrect --and therefore, the policy response is grossly disproportionate and harmful. It seems like you are arguing about facts not values, and you think the disease death rate is not really order of %1. Is this what you mean? I'm also asking because I have heard many heated statements about "post-modern" science around here as of late that wherein the speaker seems to treat that concept as common knowledge, and then walks off without explaining themselves, but I don't really understand what they are on about.
  - guscost 6y ago
    The first point is characterized correctly. We are reaping the whirlwind from a pernicious post-modern academic culture that has been thoroughly corrupted, even in the traditionally "harder" sciences to a degree. Here is a much drier, but still excellent, argument along the same lines: https://americanaffairsjournal.org/2020/05/science-without-validation-in-a-world-without-meaning/ https://americanaffairsjournal.org/2020/05/science-without-v... The second characterization is way off base. All IFR numbers are rough estimates at this point, and in fact the number is just a model parameter that does not correspond to anything in the real world, so it's a bit hard to talk about any "fact" there. The disease evolves, treatment protocols change (early venting was a terrible mistake), and susceptibility may vary widely from community to community. Still, the most recent CDC estimate for this model parameter is 0.26%. The third is a prediction, not an established fact. Right now there is no way to know what the long-term effects of our policy response will be. I have cited many anecdotal "bad" effects which (together with others) I believe will outweigh the "good" effects, but we will have to wait and see.

ghiculescu 6y ago

#2 isn’t obvious to me. Can you explain why?

hef19898 6y ago
Bluntly put, it takes time to die from any disease.
heavyset_go 6y ago
It takes about two weeks for symptoms to arise and become severe, and then about another two weeks of severe symptoms that require ventilators before people die.
- jupp0r 6y ago
  The pre symptomatic time wouldn’t be part of this gap unless the infected person got a test before symptom onset, which I believe is rare (most people who test positive get tested after they develop symptoms)
  - SketchySeaBeast 6y ago
    No, these measures affect new cases, not the already ill - so you've got to build in those 2 weeks to display symptoms for those people who would or wouldn't now be infected.
    - jupp0r 6y ago
      It’s new cases. Those are people that have tested positive. This usually happens days after the actual time they have been infected. At the time of infection, you’d test negative because it takes time for viral replication to increase viral load to levels that are over thresholds used in the PCR testing process.
      - SketchySeaBeast 6y ago
        But we're not talking testing negative, are we? We're talking those people showing up in the system (the > 2 week lag in time it takes to change course), or did I miss a level of questioning that threw this off course?
        jupp0r 6y ago
        The original question was what the delay between “new cases” and “new deaths” charts was.
  - emn13 6y ago
    If you look at the graphs side-by side for areas with clearly defined peaks (I looked at MA, NY, Italy, Spain, UK, Netherlands) the peak fatality rate is no more than a week behind peak case numbers, and perhaps less. Testing rates in at least some of those areas were fairly constant around the peaks, so that doesn't seem a likely confounding factor. I'm not sure what to make of the meaning of such a short gap, and of course people may now be testing earlier than they did in the early hot spots, so I'm not sure if this has any predictive value.
    - heavyset_go 6y ago
      Testing in the beginning lagged significantly from the initial infection.
    - rsynnott 6y ago
      One caution about those numbers; many/most sites show cases based on the day that reporting was received and aggregated, _not_ on the day it was taken. This doesn't matter very much now, as turnaround on tests in most places is quick. But a couple of months ago delays of weeks were common.
  - rsynnott 6y ago
    People are far more likely to be tested before symptoms today than a few months ago; at least in Ireland when a case is detected everyone they've had contact with is tested, and some of those will be pre-symptomatic positives. And then anyone _they've_ had contact with will be tested and so on.
jupp0r 6y ago
It takes time to die from this disease and time for that death to show up in the official numbers.
mononcqc 6y ago
The time for symptoms to show up is of roughly 2 weeks but the median time is at about 6-8 days. After symptoms show up, it takes a while before people get hospitalized, and then mortality seem to take roughly 21-24 days after hospitalization. This means that from the time someone is infected until they die, a month and a half can have gone through. By the time you take new isolation measures, you have to wait roughly two weeks to see if daily infection rates start to vary. But the lethality at this point, assuming no change in healthcare system overload, can be more or less statically predicted for weeks after the fact. Those are called "lagging indicators"; the main thing you try to prevent are deaths, which you can lower by reducing the overload on the healthcare systems, which you can lower by controlling infection rates and keeping them low. Due to the duration of the disease's evolution, you get to see if your policies really worked more than a month and a half after enacting them, which is extremely slow for a disease that propagates at exponential rates. So people look for proxies like infection rates that are still lagging, but far less so. Do note that the one good metric you want in the end is going to be "excess deaths", which counts the impact of not just the diseases, but of all other side issues that the disease may have caused. This can usually take months up to years to properly account and analyze.
- ghiculescu 6y ago
  Yep. That was obvious. Thanks!
  - jacquesm 6y ago
    I don't understand. If it wasn't obvious before then it can't be obvious now. You've had it explained to you. If it was obvious then that would not have been necessary.
    - s1artibartfast 6y ago
      Sometimes I will look all over for my keys, only to find them in my pocket. This is the obvious place to check first, but I am not perfect, so sometimes I overlook it.
  - 6y ago

emiliobumachar 6y ago

Thanks for the info. Could you, or anyone else, please explain why quarantine takes 1.5 months to be fully effective?

atemerev 6y ago
Because there is an incubation period, where people already infected start to develop first symptoms. There is a development period (from the first symptoms to the point where they are severe enough for the person to seek medical help — only at this point the case is registered). The introduction of quarantine measures is not immediately effective — there is a transition period of at least few days. There are response / case registration delays. And finally, it takes some time for the new epidemic regime just to be visible on the curve (a perceptive delay until the trend is understandable).
- telotortium 6y ago
  Do you have an estimate of the number of days for each of the delays you mentioned?

m4r35n357 6y ago

Presumably downvoted because of your qualifications?

IAmGraydon 6y ago

> Here are my observations as an actual epidemiologist In your recent posts, you’ve said that you just applied for your PhD, that you are a “consultant software engineer” in finance, that you are studying physics and that you have a masters in CS. You really must be a renaissance man.

yardie 6y ago
My former roommate graduated double majoring in Physics and CS. I don't see the problem of people having studying multiple disciplines.
- brobdingnagians 6y ago
  Yeah, a guy upstairs from me was on a path to get an MD and a PhD in microbiology, I think he was majoring in something else as well. Unusual, but it exists. Some people really like being students.
  - yardie 6y ago
    Especially the case for rich young woman from the Middle East*. As long as they were in school they were free of family obligations. That 4 year BS turned into a 8-10 year BS-MBA-PHD track. If school ever truly finished they’d be back home to SA in a niqab.
atemerev 6y ago
https://www.unige.ch/medecine/isg/en/staff/alexander-temerev/ https://www.unige.ch/medecine/isg/en/staff/alexander-temerev... (All opinions here are of my own, not of my faculty or the university).
- acqq 6y ago
  And: https://reactivity.ai/#about https://reactivity.ai/#about Edit: to respond to the question below, it clearly supports a "renaissance man" question by IAmGraydon above: it confirms both a "“consultant software engineer” in finance" and a "masters in CS." I don't see how it is not relevant. Moreover, it's not that somebody questioned atemerev's posts based on his qualifications, it's atemerev who claimed to be "an actual epidemiologist" in his first sentence, and that it definitely something that can be tested for veracity, if atamarev wanted to give more credibility to his claim with that (he didn't have to do that -- and then his claim could be evaluated on its own too, but biases by the authors of some claims are also something that could be questioned). Anyway, in this case, it's obvious that atemerev's university degree isn't in epidemiology. Edit2: atemerev's first claim: "an actual epidemiologist" now gets to be closer to the truth in the response below as "an epidemic modeler." I still believe IAmGraydon was right to question the claim, and that the initial claim was indeed misleading and incorrect.

emn13 6y ago

On number 2: that makes a lot of sense; yet in places that have had peaks (e.g. new york, italy, UK, spain) the peak observed fatality moment is barely shifted vs. the peak positive testing moment - maybe more like a week or so, normally? In all the data it's a little hard to spot trends, especially with testing rates scaling up, but still the graph peaks are not even close to a month apart, even where testing rates don't appear to be too variable. One comparison: https://datagraver.com/corona/#/?regions=italy:hex005FA2,spain:hex7FAB60,united%20kingdom:green&logScale=false&perCapita=true&cutYaxis=true&cumulative=false&types=1,2,4,3&mappingType=date&mappingMaxDays=120&mappingStartNumber=100&mappingNumberStyle=absolute&mappingEventType=lockdown&mappingDate=2020-3-1&smoothening=undefined&description=Tool%20for%20comparison%20on%20Covid%2019%20development%20for%20countries%20and%20regions https://datagraver.com/corona/#/?regions=italy:hex005FA2,spa... Massachusetts has fairly well defined peaks too: https://covidtracking.com/data/state/massachusetts https://covidtracking.com/data/state/massachusetts What's causing this discrepancy? Clearly the disease progression isn't that fast, so... what then? Maybe the more vulnerable groups tend to get hit more quickly, and as cases ramp up either die earlier or lock down more rigorously or both, such that the less-vulnerable form an infection peak after the death peak has passed? Or is it simply that people get tested late in the disease progression? Given how little the MA testing rate has varied, and that the positive rate peaks also are much closer than a month apart from the fatality peak, I don't think testing changes seem likely to be a primary cause of the (to me) unexpectedly short period between case peak and death peak.

lubujackson 6y ago
The big difference is testing capabilities. All places hit by big waves early on suffered from poor testing and public awareness, so testing happened in a burst as the deaths were starting to become problematic. And generally those getting tested at peaks were the symptomatic/hospitalized. NYC is estimated to have been around 20% infected, so the actual infection count was highly undereported. It is important to also recognize that every location hit hard was met with immediate lockdown, generally followed well by scared populations. The situation is far different now, with a good chunk of people actively rejecting even basic distancing measures. If you look beyond positive test numbers at the % positive you can see the rates are rising even faster beyond our testing capabilities. And the idea that only 20-30 year olds are getting the disease is wishful thinking - the highest risk situation is from household transmission, at over 80% likely. Combine high infections with a general disregard of safety and those older populations are bound to be infected as young spreaders interact with their families, at offices, supermarkets, etc. I think this is why the death spike lags a fair bit further than expected.

ramraj07 6y ago

How do you explain the "sudden drop" in cases in new York [1] after reaching some 25% infection rate? Do you think herd immunity (ish) can be reached at a lower saturation rate possibly? [1] https://www.nytimes.com/2020/05/20/nyregion/hospitals-coronavirus-cases-decline.html?smid=tw-share https://www.nytimes.com/2020/05/20/nyregion/hospitals-corona...

belltaco 6y ago
That seems to fit into the theory that quarantine lockdown measures are most effective after 1.5 months.
- guscost 6y ago
  It also fits (perfectly) an alternate theory that the population exhibits a wide variation in susceptibility, which lowers the herd immunity threshold. https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v3 https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v...
- nradov 6y ago
  What is the basis for that hypothesis?
  - belltaco 6y ago
    That it takes that long for this cycle to die out --> (infection, exhibiting symptoms, infecting close contacts(who start this same cycle again), becoming unable to infect others)

guscost 6y ago

> So, unless some new mitigation measures are going to be introduced _right now_, You will be able to claim that any changes made by local and state governments in the next few days/weeks “did the trick”. Nevertheless, this is a fair escape hatch when the following prediction does not come true: > this record-breaking growth will continue for quite more than a few weeks, followed by the corresponding growth of deaths a month later. We are far away from the saturation point and any resemblance of "population immunity". You will be proven wrong, both about the coming “wave of death”, and about how far we are from the saturation point. I’m quoting this and publicly disagreeing today, so that you might remember later on, and maybe even acknowledge that you got it wrong.

elipsey 6y ago
Hi. I read the essay "Pandemic Woo" which is linked in your profile. Is seems like your position is that: --COVID response strategy based on invalid "post-modern science", --the conclusion that the disease death rate is order of one percent is incorrect --and therefore, the policy response is grossly disproportionate and harmful. It seems like you are arguing about facts not values, and you think the disease death rate is not really order of %1. Is this what you mean? I'm also asking because I have heard many heated statements about "post-modern" science around here as of late that wherein the speaker seems to treat that concept as common knowledge, and then walks off without explaining themselves, but I don't really understand what they are on about.
- guscost 6y ago
  The first point is characterized correctly. We are reaping the whirlwind from a pernicious post-modern academic culture that has been thoroughly corrupted, even in the traditionally "harder" sciences to a degree. Here is a much drier, but still excellent, argument along the same lines: https://americanaffairsjournal.org/2020/05/science-without-validation-in-a-world-without-meaning/ https://americanaffairsjournal.org/2020/05/science-without-v... The second characterization is way off base. All IFR numbers are rough estimates at this point, and in fact the number is just a model parameter that does not correspond to anything in the real world, so it's a bit hard to talk about any "fact" there. The disease evolves, treatment protocols change (early venting was a terrible mistake), and susceptibility may vary widely from community to community. Still, the most recent CDC estimate for this model parameter is 0.26%. The third is a prediction, not an established fact. Right now there is no way to know what the long-term effects of our policy response will be. I have cited many anecdotal "bad" effects which (together with others) I believe will outweigh the "good" effects, but we will have to wait and see.