CharonY

It highly depends on how the respective health authorities collect their data. Some do not actually record symptoms and only provide hospitalizations rates, for example. Also note that you can asymptomatic when tested, but develop symptoms after. Recording these things accurately is difficult unless you have identifiers for each person (which is generally not the case).

The data are also only partially help to establish that. In almost all countries tests are administered after indication, which could include symptoms but also e.g. contact with positive persons. In conjunction with the fact that a positive person may exhibit not symptoms the data will mostly show bias in sampling procedure or of the cohort.

I suspect an easier explanation is a mix of volume of travel from infected areas and potentially incomplete testing. In Russia the number of detected cases are rising rapidly.

They are generally reported by each country's health agency (e.g. CDC, Health Canada, etc.).

In short, they identified a singular (monoclonal) antibody that binds to a conserved area in coronaviruses and found that if it binds, it interrupts the ability of the viruses to invade cells. It is at this point more a mechanical/functional study showing that presence of antibodies could at least fundamentally disrupt invasion by viruses. This gives hope to convalescent serum treatment for example. Of course it is not ensured that folks producing antibodies (they are always a mix, or polyclonal) will develop something similar. It is unlikely to influence vaccination development much I think, most target the spike protein anyway. It does increase the likelihood that immunization is feasible though (I think).

I vaguely remember that someone was looking into outcomes of folks with seasonal influenza co-infection but I just cannot remember the author. The only thing that I took away is that there was no indication that co-infections had a significant impact on outcome per se. Once the cases become severe, however complications from other infections become more problematic. That being said, I doubt that we have enough information to have definite answers- many of these studies were small in scale and quickly published (for obvious reasons) so conclusion may change once new findings pop up rather rapidly.

Basically that would not work. Adaptive responses react to specific antigen presented by a given causative agent of disease. The only possible scenario would be e.g. another coronavirus that has an antigen that is very similar to one from SARS-CoV-2. But that would be highly unlikely as a whole. Also co-infection is a bad idea, immunity (if it happens) is built during later stages of the response. Theoretically having multiple diseases is not a good situation especially if they can make things worse for the patient. I.e. you would want the immunization happen before getting the disease (which is the idea of vaccines and why vaccines cannot be used as a treatmen).

Most studies focus on COVID-19 but looking at the papers it does not appear to be common at all. The reason mostly being that in mildly symptomatic cases the person still would be positive, though one can probably not be absolutely certain which virus is the actual cause (or their relative contribution). After all symptoms for infections of lower respiratory tracts are very similar. The only other thing I can think of are infection with bacteria, which often indicates treatment with antibiotics. But at this point we are looking at more serious symptoms.

It is hard to watch that so many folks approve of Trump's flailing response. https://projects.fivethirtyeight.com/coronavirus-polls/ Considering that much of what worked out was more despite the interference of the WH rather than because of it. And with regard to the consultant:

I suspect the question is aimed at respiratory disease. I believe it has been asked and answered a few times, though knowledge is of course evolving. There are handful of studies who have tested COVID-19 positive patients for e.g. influenza, other coronaviruses an so on. In one study from Wuhan the co-infection rate was about 20%. In other regions such as Italy I have seen some higher estimates but with fewer tests. The general consensus seems to be that it co-testing does not change clinical practice and is probably not terribly helpful with few exemptions.

Yes there is a high prevalence of obese folks among the hospitalized folks. It is likely that obesity puts a strain on the cardiovascular system. However, there are also reports of many folks just being overweight, here it is a bit more difficult as in many countries there are a lot of overweight folks and it may be difficult to figure out whether the connection is spurious or not.

There is an interesting background to that, though. Throughout the years, certainly at least since Bush the response to outbreaks (I am talking about the US here, but one could exchange dates and it would somewhat also apply to many other countries) the common reaction is to have an outbreak, build up response capacities, then forget about them and slowly defund them up until the next one occurs. The playbook was one (possibly the most comprehensive) attempt to solidify these measures. But it is also true that when Obama came into office he initially disbanded an office for global health security (which was first disbanded by Bush but re-instated sometime after 9/11). So in a way Trump is doing the same mistakes as his predecessors (there is more nuance to it, but leave it a that). What seems to be massively different is that in this case there is no indication that there will be any lessons this time around. So basically the classic way is that we forget the lessons learned, get surprised by it blowing up, learn something from it and then over time forget again. This time we forget things, refuse to learn and double-down on ignorance. Can't wait to see what happens after that (ideally from the inside of my locked lab).

It has been employed against different viral diseases, incl. SARS, MERS Ebola and a few others. Don't recall respective efficacy, though. You are also correct that recovery time was the major effect.

To some degree. But unless you have quantitative coverage, you generally want to design your cohort so that they are representative in terms of your research questions (e.g. in terms of age, gender, area etc.).

Ehem: https://www.vox.com/2020/4/30/21243117/trump-blames-obama-coronavirus-broken-tests-jim-acosta

We cannot have one without the other. Test should not be random either. In the perfect scenario, everyone gets tested and has follow ups. If that is not possible one should prioritize likely cases as it is done in most areas, but it has to ramp up to capture those that may be unknown spreaders. Without that knowledge, containment plans have to be overkill to work, as you do not have a clear view of the spread if your test happens to be biased towards known cases. In turn that means that we need the ability to ramp up testing capacity as needed (the situation in the US is quite ridiculous, where states are competing with each other in a dystopian bidding war), have a centralized knowledge gathering and distribution system as well as means to conduct contact tracing. There are also specifics to this outbreak that need tweaks in methodology. For example, the worry about asymptomatic spread might need to be addressed via supplementary immunoassays, if direct testing for viral particles cannot be ramped up. Again, COVID-19 is one of many outbreak test runs we already had (in this century alone) and the common lesson is that a) we need to improve our response and b) periods of no outbreaks cannot allows us to reduce preparedness. Epidemics and pandemics will keep occurring, it is just a matter of when and where.

One issue is that Japan is severely undertested. I.e. the number of cases is probably not accurate.

I am not sure whether that is the right way to look at it. Pathogens do not need to overwhelm the immune system by force (though it is one strategy employed by some bacteria). It is sufficient that particles evade detection and start multiplying. The overwhelming part is then from the inside rather than the outside. So far it is not clear whether a higher initial dose would result in worse outcome under physiological conditions (there is only indirect evidence so far). And conversely it is unclear whether healthy patients can withstand higher doses than sick ones.

There are studies looking for viability- the data you might have seen where the number of infectious particles reduce under certain condition are conducted with in vitro testing. It is more difficult to try to recover under non-laboratory condition, of course and especially indirect contact is different to assess as there are a lot of variables going into it. That all being said, the overall pattern is consistent with mostly direct contact exposure, perhaps with additional indirect exposure when folks are not washing their hands, for example. I am not sure about that one. If you test positive, there are already detectable amount of viral particles in your blood stream at this point you are likely infected. You may be asymptomatic, but your body is already producing particles. If you are just exposed to a few thousand particles indirectly but are not actively producing it is unlikely to identify them (for reference the limit of detection of many kits is around 6 genomic copies of the virus in 1 ul of sample). While larger exposure is correlated with worse outcomes, it does not mean that only high exposure create serious outcomes. Especially in older folks as well as folks with comorbidities the prediction is worse. While it does not exclude a dose effect, we cannot conclude that it is indeed predominantly (or even significantly) does dependent.

It is independent of that, but most biosafety areas are under net negative pressure, as it is more important to make ensure that biohazards are less likely to escape. Conversely, a clean room (or operating theatre could run under positive pressure in order to keep contaminants out.

Yes, though for larger areas, maintaining true laminar flow can be difficult in terms of inlet-outlet configuration for the ducts to avoid turbulence. Other systems, such as clean benches do the opposite, they maintain horizontal (mostly) laminar flow, in order to move particles away from items to be protected, but that would be exactly what we would want to avoid here.

It would most likely damage lung tissue more. Remember, in the lung all the lining are living cells, unlike skin, which has a protective layer of dead cells. As such physical treatment has an immediate effect on tissue health and integrity. In case of cancer, the goal is to introduce tissue damage, with the hope that cancerous tissue is destroyed faster than the rest. In case of viral particles the issue is more whether you do more damage to the tissue than to the viral particles, which in turn might continue to proliferate and penetrate more as lung tissue degrades.

In biosafety facilities the workspace usually has a laminar air flow (top down) to minimize circulation of droplets or aerosols. Horizontal flows would in most cases result in broader distribution. I would think that a similar circulation (i.e. top down) could theoretically reduce spread, but are probably difficult to employ at scale.

The most common element is more extensive contact tracing and follow-ups with testing at the beginning of the infection cycle. I.e. getting ahead of the curve.

Technically, it would be the effective reproduction number (or R sometimes referred to as Rt) as R0 refers to the basic reproduction number which is absent of any intervention of disease transmission and where no immunity exists (though in press I see the terms used rather liberally). In case of SARS-CoV-2 it is even a bit more complicated as both numbers would be the same at the beginning of the infection process as there was no immunity and also no intervention. But aside the nitpick, the idea is indeed to surf the number close to one and hope to keep new cases low(ish). In some areas this does not seem feasible with still relatively high (or unknown) transmission rates.