CharonY

As Studiot pointed out, different countries have different reporting systems. The US specifically was potentially hobbled by the last administration. Normally you will find details on their respective websites how they do it. However, the data is generally submitted on the local level, e.g. coded by a hospital and then may go through local health authorities or even submitted simultaneously to local and federal reporting systems. As example here are reporting instructions from the US-CDC: https://www.cdc.gov/coronavirus/2019-ncov/downloads/php/COVID19-CSV-Case-Reporting-Instructions.pdf With regard to asymptomatic spread, there is of course no way you can test that in laboratory directly as it involved to actually make someone sick. Rather, folks will depend on retrospective analyses or other measures, including antibody and wastewater testing. However, tests of folks who are asymptomatic but turned out to be positive found that even without symptoms, the viral titer can be fairly high, which makes spread very likely. Likewise, asymptomatic spread is also the best explanation for high levels of community spread, where infected folks could not be linked to positive cases. Also you need to define "accurate case estimates". The most accurate number are of course people tested positive, which forms the baseline. If you want to figure out how many may be underreported, that requires additional research. As the pandemic is still ongoing, the estimates will continue to change so I am not sure to what accuracy would refer to here (a specific timeframe, for example?).

No, as asymptomatic cases can still produce enough viral titer to be tested positive and spread the infection. The massive spread and susceptibility in the population is the reason why we have so many deaths ( as I have mentioned above). Perfect data is a challenge for any disease. However for this one we do have a ton of data with a range of supporting estimates. But note that death rate is heavily influenced by a lot of parameters, such as availability and access to emergency treatment, oxygen, ventilators and so on. As such there is a wide range of estimates, depending on where you are. I.e. there is not a singular estimate satisfying all criteria or uses. In other words, it depends on what you want to figure out. If the goal is to compare to, say influenza, it is going to be difficult as influenza is usually highly underreported and often relying on indirect measures (e.g. absence from work) to estimate the actual outbreak numbers. There are also different measures that one need to distinguish- the case fatality rate. I.e. how many of folks tested positive ultimately die. That, of course depends on how well we test the population. The infection fatality rate relies much more on estimating the the total rate of infections. The ranges even for established diseases such as influenza have several order of magnitude differences in range (again, because the actual known infected proportion is generally not known).But COVID-19 makes things even worse- there is also the risk of long-term damages, i.e. folks might indirectly die from the disease quite a bit off in the future. As it turns out, case of infection mortality alone is probably not a great measure to characterize a disease- it ignores for example the proportion of susceptible people. This is why in the USA alone we have more COVID-19 linked deaths than in the whole world for the H1N1 pandemic. Moreover, I see mortality rates frequently misused in the media (one way or a another). But as mentioned above, we now have a single disease which has been verified to cause as much deaths as all other lower respiratory infections combined. It is a single virus that worldwide ranks somewhere in the top 5 of causes of deaths. In the USA, COVID-19 is the third leading cause (or higher) of death for folk above 45. Between 35-44 it is about as lethal as transport accidents (but double as high as homicide). Influenza an pneumonia generally is only around the top 9 and only for groups older than 65. Again, it is a single disease that significantly alters the death statistic of the population. With regard to the response, I think at this point it is clear that countries that fail to have a centralized, updated pandemic plan or, if they have one did not act on it (recent reports have highlighted the issues in Italy) suffered more excess deaths and have resulted in higher circulation of viruses. The latter is also the cause for the emergency of new variants, and which makes it more likely that COVID-19 might become an endemic disease.

I think some folks, including many students, are under the assumption that as long someone cites something, it somehow becomes more credible. That of course is not true. Assuming the citation was done correctly, it only points out to a fact or observation made by some other group. It does not mean that it follows the argument that one wants to make. I can, for example, correctly cite a paper that shows similarities of SARS-CoV-2 to existing bat coronaviruses, but if the main thrust of my paper is about how lizardmen have released the virus in order to overthrow their pangolin overlords, it does not actually add credibility. It is more that if no citations (or mainly self-citations) are given, that one should be even more skeptical.

The issue is if you make things up, there is no reference point to assess whether something is correct. At best one can check for internal consistency. However, if the made-up concept is not well described either (especially if deliberately so), then even that can be challenging or impossible.

Oh no, this study did not look at cultural factors. The goal was to figure out the high death rates and found a strong association with a) being infected in the first place and b) a strong effect of SES. Other studies have looked at reasons for higher infection rates among black and Hispanic folks and the conclusion from those is that it seems to be strongly correlated with jobs. 75% of frontline workers are POC, they are overrepresented in high-risk jobs such as meat factories and so on. While there might be cultural aspects, the economic ones (i.e. jobs) seem to explain most of the variance on their own, if looking at larger patterns. There are specific communities in which have high infection rates that could be based on cultural aspects, such as among orthodox Jews which appear overrepresented. But they tend to be pockets rather than larger patterns.

Isn't it true for a vast swath of capitalist markets, though? I mean you can buy and sell debts, bet on increase/decrease of values and so on. Compared to that, a blockchain is almost physical.

! Moderator Note The topic does not seem to be related to evolution but potentially about how bodies can be preserved? Could be an engineering challenge.

Pump it up and ring my bell cause I want to ride my bicycle, bicycle, bicycle.

The fundamental question is rather simple: "when does human life begin?". The issue is that answers are a tad more complicated. While most proponents of fertilization as the starting point are likely religious, it is not always the case. Also, it is not really an US-specific issue. It pretty much is aligned with the issue of abortion rights and the connected ethical dilemma, where you will find polarized views across the globe. The concept that one might start defining something as human and therefore worthy of protection later in the development cycle (though precise boundaries are not really forthcoming) has higher acceptance (I think) now than it was in 90s or early 2000s, so we may be seeing a shift in attitude. But as a whole it is one of the questions that operates in an ethical grey zone as biology escapes simple binary classifications.

SARS (if that is what you referring to) killed much fewer folks than H1N1 (less than 1000). It should also be noted that spread (as in pandemic) does not equal to lethality. Seasonal influenza for example claims a lot of deaths each year, and it is annoying (to put it mildly) that folks just assume that it is fine. In addition, how folks deal with a disease (i.e. the medical system) highly influences how deadly a disease ultimately is. More as a side note "new" is quite a bit of an issue with diseases. The issue being that many have been around for quite a long time. However, many viruses (but also bacteria) can exchange genetic material and merge to various degrees resulting in pathogens that are either originally non-infectious to humans or are unable to spread between humans, suddenly become able to do so. These recombinations as well as regular mutations can happen anywhere with a disease reservoir (e.g. human populations, wildlife and/or farm animals). In fact, human reservoirs are where new SARS-CoV-2 strains are emerging in the UK, South Africa, Brazil, USA and so on. I.e. areas where the virus is circulating. There is no good reason to assume that any place on Earth is safe from the rise or development of new diseases. No, most influenza deaths are among the elderly. H1N1 had an uncharacteristic high level of deaths among younger folks. Silly me, of course it is just because of ideology and attitudes and not the fact that all had a friggen pandemic plan in place and acted on it, which mitigated issues. It also is news to me that the listed countries don't have capitalism. So it appears that only countries which are antagonistic to China can implement measures within their own borders, such as aggressive contact tracing programs or ramping up on critical supplies (and note, Taiwan never enacted a blanket ban on travel from China, they restricted travel from affected provinces, such as Hubei instead). Seriously, read up on it, there is not a lot of reason to wildly speculate. China did not even play a seriously role in their respective mitigation strategies. Of course it is all yours then, after all you promoted indefinite travel restriction while at the same time claiming that, contrary to all evidence, contact tracing won't work. Or how else should one interpret: And it does not really explain why it failed in Europe, either. Also, the argument does not seem to be internally consistent. Assuming that free marker and/or capitalist concerns are overriding pandemic plans, one would assume that travel restrictions would be less likely to be enforced than, say contact tracing. The former could disrupt a range of business, whereas the latter (if successful, as we have seen elsewhere) can keep businesses open. Let me summarize. On the one hand there are numerous studies tackling the pandemic from perspectives ranging from health services, policy and economy. There is almost an universal consensus that the most effective measures are strong, ideally centralized eradications strategies (see e.g. Baker et al. Med J Aust 2020). We have empirical evidence that the outcome were much better than in other countries, regardless of their economic system. Likewise, travel restrictions have shown to have a moderate effect at best (see Russell et al. Lancet 2021 6:1) Meanwhile, do you have any evidence that what you propose would have any effect beyond hand waving? Do you think Europe and the US have a very different economic system than Taiwan or South Korea that would impact responses? If so, how? If you cannot substantiate any of your claims, I can only assume that you just want to peddle your personal hypotheses without critically dealing with the matter at hand. And rather obviously, any conclusion based on evidence-free assumptions are unlikely to be useful.

! Moderator Note It does not seem that the discussion is progressing, mostly because there seems to be a lack of understanding of basic principles. As I suspect that a discussing or reading up on said basics are more beneficial than wild speculations and off-topic tangents, I am going to lock the thread for now.

It is stupid to assume that outbreaks will only happen in China. In fact, the assumption that outbreaks are limited to elsewhere is one of the reason we are in this mess. While most pandemic in recent times had low death tolls (well, H1N1 is estimated to have killed between 100 and over 500k people, which is not precisely low...) , it is a matter of chance until a more deadly one (like COVID-19) arises, with just the right combination of traits that also make them difficult to detect, especially in the early phase. The only effective strategy would be to restrict all travel. You'd be using the same logic. Why should convenience of, say, US travelers be more important than anyone's safety? Also it was lack of a pandemic plan and lack of political will, not capitalism that led to poor results. You should read up on how other countries responded. Also I reiterate that looking outward as the main or sole preparation for disease outbreaks and pandemic preparedness is a special type of short-sighted and annoys me to no end. Everyone with a little bit of background in infectious diseases observing the situation could tell where things were going early last year. Sure, there were a lot of uncertainties (the risk of asymptomatic spread being one important bit), but a lot of professionals in the field raised alarm (the early timeline could have been shifted by maybe few weeks at best). And then, while some countries activated their plans, plenty others did not (I am sparing you the details less MigL gets annoyed by reading it over and over again). There were plenty of measures to take and saying that it is capitalism, individualism, desire for freedom or culture (I have heard it all at this point) are just a piss-poor excuses for not taking the right measures. Most economists at this point agree that even hard lockdowns at the beginning would have been less costly then the reactive responses that were eventually implemented. Travel restrictions can slow things down but then you have to take measures in your own friggen country just as others have done in order to control spread. Yes it is annoying, but if you are unwillingly to be inconvenienced in a deadly pandemic then I do not know what to tell you.

I think the broadest term would be bias of some sorts- the intention might not be willful misrepresentation. To be maybe a bit clearer in an example. If a graduate student performs an experiment, e.g. looking at growth differences between bacterial strains, at the beginning you often have huge variation in the data. This is often caused by mistakes, such as inoculating varying amounts of cells at the beginning, contaminating your sample or making mistakes in media composition. With practice, the variance typically narrows and then one might detect significant differences. If one reports every growth data, the what we consider "better ones" will be drowned out by the rest. Even if you just dump the data without highlighting it in the paper much, the reviewer would have a hard time going through all of them only to come to the conclusion that, yes trainees probably did not did a good job. Given the time constraints that we operate in, it would make the process really cumbersome. But I do understand the larger point- data scientists are more comfortable in dealing with big data set and at least in theory, if everything is on the table, perhaps not during the peer-review process but at some later point, those folks could extract the data and maybe see other patterns in there. But the really big issue from an experimental viewpoint is that the largest set will be simply low-quality data. If you ask any grad student, they will all tell you that the most significant data usually is generate toward the end of their degree, when they a) built up the skill to perform the experiments reliably and b) figured out all the ways they should not run the experiment. As you can probably read, I am a bit torn regarding the best way to report complex data. However, I do think that to make a case of fraud it is necessary that the one committing it knows that the form of reporting distorts the findings. I.e. if deliberate deception is involved. Traditionally, we use controls to account for bias (rather than offering all data sets, including those that we deem failed experiments), of course this is not fool-proof, either. From an outside view, it is difficult to tell, of course. There is also the issue that much of it depends ultimately on trust. I trust that my students are reporting data the way they performed it, for example. This is certainly an issue and especially the high competition makes it worse. I am not sure whether there are short-term solutions for it. However, one should keep in mind that ultimately the system is (slowly) self-correcting. Obviously if you publish something interesting, but biased, others will have difficulties to build upon that data. Eventually newer findings will indicate that what has been published before is probably not accurate or is missing some key criteria. Cases of outright fraud are often that far off from the base that it could trigger retractions or even more serious sanctions. Biased data on the other hand are often more borderline.

It can be, if the full reporting substantially changes the outcome. There are borderline cases which can on either side of the issue. For example, some data sets might be selective due to their nature. Examples include microscopic images which are qualitative in nature (e.g. showing co-localization as a random example). Now if you have taken hundreds or thousands of pictures you generally are unable to provide all of them (and likely, no reviewer would want to go through all of them). So as a consequence you provide images that are supposedly representative. But this criterion can be highly subjective and biased. In other cases it is not uncommon that difficult experiments need to be repeated fairly often until the assay works (remember that most research is actually done by trainees). So here the issue becomes whether a particular data set that might be just botched should be added to the final analysis or not. Fundamentally there is a big move to have all data sets, including supposedly bad data published, which in principle makes sense. However, it has a lot of practical limitations.

The only studies i am aware of are looking whether immunization of one sibling helps prevent other siblings from getting sick (e.g. If they are too young). You won't have a lot of other cases as folks who deliberately don't vaccinate, usually do so for all kids. There of course you see a lot of preventable disease outbreaks.

namegoeshere decided to hurl abuses by way of introduction. Therefore, he has been shown the door.

! Moderator Note I think that is enough information to determine that a fruitful discussion is not to be had here. Locked.

! Moderator Note I am sorry for any hardships you have encountered but a) we cannot dispense medical advice on this forum and b) I do not see actual science or politics to be discussed. However, as you are exclusively talking about a series of personal experiences, I do not see a lot to be discussed here. So perhaps try to figure out what you would like to discuss that ideally goes beyond unverifiable personal anecdotes.

And did you mention the fact that the virus may have circulated before anyone (including China) realized that there was a new respiratory disease going around? In France there is some evidence based on stored blood analyses that positive cases might have been present around as early as November. Of course tests did not exist at that point and no one knew that there was a risk for asymptomatic spread. The first confirmed cases in France were two months later- in January. In Spain and Italy wastewater analysis indicated presence of the virus early December and January. Over a month before the first case was detected. In other words, even in those countries there was a significant delay before Covid-19 was diagnosed and there are good reasons for that. Symptoms are not specific and can be easily confused with other forms of pneumonia and we have got many asymptomatic or mild conditions that could spread but would not ring any bells. China reacted too late after clusters have formed. A part of it was because their monitoring system was too rigid. They had literally a form that included testing results for SARS. If that had been activated the full pandemic system would have reacted. But since folks were not flexible enough to account for diseases that need new testing methods, officials decided that it could not be something real (and as we learned elsewhere, once idiots in power decide on something stupid, a lot of people have to suffer, just so that those in power are proven right). While quarantine and contact might have worked (but if the study is right there would have been two months of potential community transmission already), most Western countries did a sloppy job with that. They either did not have a pandemic plan or it just never kicked into high gear in time (again, as opposed to several other countries who did just that). I mean, we are a year in and some countries only now start to levy fines for breaking self-quarantine. In Canada last year snowbirds came back from the US and straight waltzed into the nearest Wal-Mart. So yeah, no the response has not inspired me with a lot of confidence. Just to be clear, there is nothing wrong with having additional institutions and collaborations (and frankly, the US CDC always has been something of a reference point for EU responses). But none of those will be able replace a global platform. if anything, those should be strengthened.

While I agree that there has been a shift from self-improvement to a financial transaction, I disagree to some degree with the motivation. I do not think cheaters feel that they need to cheat is the only way to advance. Most of the cheaters I found were folks that generally did not even put minimal effort into class. I.e. frequently absent (I do not take attendance), rarely ask questions (beyond "what will the questions in the exam be" and "do I need to know what is written on all the slides"), I doubt that they have read a single page of any of the textbooks (all open access). I would understand cases if those folks e.g. had to work to finance their degree. But actually most seem to be fairly well off, wanting go to medical school as their parents are physicians. Or threatening faculty with their big lawyer daddy if they do not raise their scores. Others have basically flat out mentioned that the additional time they want because of their "learning disability" must be provided in a way that gives her benefits over others (I offered to give everyone more time to finish their assignment). And of course I provide folks months of time to prepare and ask about an assignment and obviously all questions only come in during the week it needs to be finished. Again, I think there is societal-wide change in the attitude of learning for its own benefit and in part that is likely to be driven by economic concerns. At the same time I also think that the personal enjoyment of learning new things has gone. I feel in part it is the way we consume information nowadays (tons of small bites, but never in-depth). Folks confuse hearing about a subject with mastery of it. And often I think that many students nowadays do not feel the excitement when things suddenly come together in ones mind. Every now and then I have a grad student where I see the lights go on during their work. But again, I feel it has been much rarer now than even 10 years ago. Reading a paper is for many not about the new and cool things that someone has done. It is almost just a thing you do and then immediately forget (i.e. shallow reading).

Yes sorry, I understood it as such, but I also wanted to comment on the fact on accountability which is also vulnerable in democracies. I kind of conflated the issues in my mind, sorry for the confusion. Or animals (birds, for example) or food. And considering how connected the world has become it is silly to assume that we can effectively control outbreaks, especially those with long incubation periods via border control. Unless of course you can see a way to lock borders the moment someone on the planet sneezes. I mean for Christ sake, most infections from the US came from Europe. Your arguments are basically undoing all the lessons we learned from this very ongoing pandemic. What chance do we have in a few years from now if the next one hit?

Well neither does the US. There are reports of at least attempts to manipulate data and one data scientist was allegedly removed for refusing to do so. But that is not the only issue. Whether you trust info from a particular region or not, global collaboration is absolutely needed to have any chance of combating outbreaks. Dictatorship are of course suspect but it does not mean that we can ignore them in the face of global threats. Again, it is based on the erroneous assumption that catastrophe somehow care for political borders. I will add that many African nations seem to be coping surprisingly well. Not fantastic in some cases, but at least most took serious efforts and until recently they outperformed expectations. A part of it is actually having some pan-African responses and plans, which curbed the first wave but has shown to become brittle during the sustained onslaught.

There is literally nothing that prevents some countries to form medical or other alliances (and they exist). But you forget the whole point of it. Many diseases are global problems. Just caring and coordinating in your neighborhood alone cannot control them. I mean, just look at the freaking situation right now. You are basically saying that without info from China somehow the West would have magically responded better. We have empirical evidence that the world needs to work more together on this matter not less.

I have not checked literature, but my own experience would suggest that cheating might be increasing and it is also dependent on the system. In North America, studying is viewed by most students as a financial decision. Especially among medical students there is a strong incentive to achieve high grades by whatever means. Students are also better informed than they used to be. They are much less afraid of potential repercussions by their profs and have developed strategies to maximize grades with the least effort. They are also more cynical and have less qualms of finding ways to (in their minds) beat the system. You have the weird situation where based on performance you might think that a student is lazy or stupid, but has the surprising ability to play the system to their advantage. It is incredible how many for example file doctor's note claiming to have ADHD, dyslexia or other conditions requiring them to have more time than their peers. And most are premeds!

I do not think that you made a lot of things clear, to be honest. For the most part it just read like a stream of thoughts that may be obvious to you but at least to me it is at best cryptic. Specifically in science there is a big risk if someone is found to be falsifying data. Once trust is lost in a researcher, their career is over. And also competition is fierce. The only folks who might have it easier are bigshots who already have a distinguished career and thereby may ultimately be given a bit more leeway. But again, actual fraud would be a career ender in either case. It seems we have to do more hammering, especially in undergrad given the massive spike in cheating related to online classes.