On 2020-11-07 13:40:48, user kdrl nakle wrote:

Why would you need a surrogate? You did not explain anything about the relation between this virus and SARS-CoV-2. The title is misleading.

On 2020-11-13 09:01:22, user Suneet Sood wrote:

Sir, I applaud the very well-written study. The data is valuable. I do suggest that we should be cautious with the conclusions, however. The aim of this study was "to evaluate the impact of SORT interval on clinical outcomes". It was not "to evaluate the impact of SORT interval on clinical outcomes in SORT groups <=9 vs > 9". In other words, the <= 9 and > 9 groups were not declared a priori. I think a better conclusion would be "Our study suggests that the results in these two groups are different, and should be confirmed by a trial in which patients are randomized into these two groups."

On 2020-11-16 08:49:06, user Mike Maglothin wrote:

I've seen several studies attributing all excess deaths to CoVid. I agree... BUT.. what they show in their modeling is a correlation to CoVid. The excess deaths could very easily be from delayed procedures or people being unwilling/unable to get a procedure done in a timely fashion. I know many procedures were delayed, especially during the beginning of the pandemic when hospitals were being "reserved" for CoVid. Would be interesting to see the Excess death correlation only after August.

On 2021-09-13 15:48:07, user Bennie Schut wrote:

In a followup it might be interesting to compare myocarditis requiring hospitalizations in both vaccine and covid groups. Not all myocarditis requires hospitalization and being infected now seems more of a when than an if. We already know covid causes myocarditis, so for risk assessment we would need to understand if one is better than the other. This study doesn't show this yet. But very interesting nevertheless.

On 2021-08-20 23:43:57, user Chris Raberts wrote:

Can the authors explain how they conclude that lowering the particles in the air reduce the chance of infection? Seeing the sheer amount of particles exhaled this seems like a drop in the bucket, even at 50% reduction.

If you cant swim it doesnt matter if you fall in a lake or the ocean.

On 2021-08-21 04:36:50, user Fergal Daly wrote:

This applies linear regression to cumulative cases against NPI scores. It does not specify any model that justifies this. Simple models suggest a linear relationship between NPI scores and estimated R_t or log(case-growth). No model would suggest a linear relationship between these two. In the simplest example, if NPIs bring R_t below 0.9 it leads to very few cumulative deaths, with no much difference between very strict and less-strict, as long as R_t is < 0.9. Conversely, all NPI that leave R_t above 1.1 , lead to explosive growth and very similar large numbers of cumulative deaths. The relationship is highly non-linear and applying linear regression has no justification. The statistically significant outcome must be either chance or systematic result of the mis-specification.

On 2021-08-27 04:39:32, user William Brooks wrote:

The authors use cumulative deaths from June 2020 but don't explain why they omit deaths before June 2020 (i.e., the <br /> whole first wave). Since many of the deaths during the omitted period <br /> occurred in states with strict NPIs such as Maryland (Fig.1a), this probably biases the results in favor of stricter states since they would have had smaller susceptible populations after the first wave than other states. Another study got around this problem by excluding northeastern states from the main analysis of the summer wave and including them in the analysis of the autumn/winter wave [1]. Because different NPIs were introduced/lifted at different times in different states, it would be interesting to see how consistent the correlation between NPI strictness and cases/deaths is during different waves.

Also, Fig. 3a shows that case trajectories are clearly effected by geography, so rather than directly compare two states with different NPI strictness from different regions (Maryland and Tennessee), it might be more informative to compare two states with different NPI strictness from the same region (e.g., Louisiana and Florida).

[1] https://escipub.com/Article...

On 2021-08-23 09:38:01, user Valerio Marra wrote:

Now published in Scientific Reports doi: 10.1038/s41598-021-95004-8

On 2021-08-23 23:20:52, user Toa_Greening wrote:

The said method "aspirin once daily until discharge" was not meet as only "5040 (77%) received aspirin on most days following randomisation(>=90% of the days from randomisation". Therefore the aspirin treated group data of 7351 is contaminated with patients who did NOT have "aspirin once daily until discharge".

It is recommended to redo the analysis using only the "5040 (77%) received aspirin on most days following randomisation(>=90% of the days from randomisation" as the aspirin group.

On 2021-08-24 08:23:27, user Meerwind7 wrote:

I like to praise that an assessment like this is possible only in a "No-Covid" environment where extensive contact tracing of individual cases is possible.

The conclusion about the difficulties to contain transmission even in this setting, i.e. with rare infections that allow extensive contact tracing ("individual-based interventions such as case isolation, contact tracing and quarantine"), points to the near-impossibility to contain Delta in the larger part of the world, even with more voccination.

On 2021-08-24 18:06:02, user Skeptic wrote:

23andMe has an article about this on its website, in which the company listed the WRONG reference SNP number. According to this pre-print, it's rs7688383, but 23's 6/2/21 article claims it's rs7868383. In any case apparently the v.5 chip did not include this SNP as I can't find it in the raw data for any of the five kits I manage at 23.

Kind of important to proof read, 23andMe, if you expect to develop and maintain credibility: https://you.23andme.com/p/8...

On 2021-08-25 06:23:02, user L Wong wrote:

This pre-print was submitted to the peer reviewed "Japanese Journal of Radiology" and was accepted on 6th of Jan, 2021. The content had been revised according to the reviewers suggestion and comment and the title of the article was revised as "Convolutional neural network in nasopharyngeal carcinoma: How good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?”. Readers can find the latest version of the article in the link:

https://link.springer.com/a...

.

On 2021-08-26 05:47:36, user MarcoBonechi wrote:

You assume 2-3 students being infected at the beginning. Out of 500 students. 2.5/500=0.005 i.e. 500 cases per 100k.<br /> That's 10x actual Aug-2021 US rate at 46 (https://www.nytimes.com/int... "https://www.nytimes.com/interactive/2021/world/covid-cases.html)").<br /> 18x the CA rate of 26.

Your study has <10% chance of happening?

Please explain.

You should redo the study using several scenarios using randomized chances of a student being positive from outside.

Then also randomize symptoms, as symptomatic cases will stop spreading or be caught altogether before reaching school.

Then also randomize mask failure rate, badly worn masks, ineffective masks etc..

Finally add testing with weekly or twice-weekly universal antigen with their success rate.

You got to put more work!

On 2021-08-26 16:37:49, user Larry Melniker wrote:

The issue with Dr Hoffe conjecture is connecting D Dimer results, which are nonspecific, with serious ischemic events, which require specific testing results. He may be speculating on a True-True, but unrelated phenomena; otherwise D Dimer would be a routine part of ACS rule out work-up.

On 2021-09-10 15:49:38, user skeptonomist wrote:

The paper shows very conclusively that the vaccine reduces infection rate. Because the overall death rate among those infected is small (on the order of 1-2% at most), the expected number of deaths in the placebo group is not large enough for a meaningful test of how death rate is affected.

On 2021-08-27 17:40:44, user David Wells wrote:

Table 1a shows that your 'vaccinated individuals' group exhibited higher rates of comorbidities. Comorbidities are therefore possibly correlated with vaccination. The model results show insignificant comorbidity effects, suggesting the possibility that your 'vaccination' effect is really (or partially) a case of stolen significance. Did you try removing the vaccination variable to find out if comorbidities then become significant? Or what if you matched on comorbidity rates, not just demographics?

On 2021-08-28 02:02:35, user Jonas Ferris wrote:

While it may be that natural immunity offers more protection than vaccine immunity, there seems to be some problems here:

How can you adjust for the issue that some in the previously infected group died, presumably those most susceptible to symptomatic infection while the vaccinated group likely has many of these most susceptible still in the group?

As the overall infection rate seems quite low (<2%) in the vaccinated group, though many multiples of the even lower numbers in the previously infected (and death screened) group (leading to sensationally high multiples of up to ’27-fold risk’) is it possible that many of these infected could have been deceased had they not been vaccinated?

I understand there are adjustments for comorbidities, but there is no real way to determine who would have died from a group with comorbidities yet they may not exist in the previously infected group.

Why are there so few people above 60 in the study (<5%) when this age groups is over 15% of the population over 16 and the very age group that is most likely to have serious symptomatic infection? How many went to the hospital from this group in both the vaccinated and previously infected groups?

Early seekers of vaccines were likely more at risk of death from Covid than those that were not as worried and didn’t (or couldn’t) get a vaccine in Jan/Feb.

Your two groups are basically those that were fearful of catching Covid and those that didn’t see it as much of a risk to them. These are groups that may have very different risks of testing positive for Covid even if they both received vaccines at the same time.

Those that received a vaccine after almost a year of watching out for the virus may have acted in a more risky fashion after getting vaccinated - the pendulum swung even further than the no vaccine group (who may not have known they were somewhat immune)?

Given these shortcomings, it seems like a more reasonable conclusion than natural immunity is 7 fold+ stronger than vaccine immunity after a few months, is that while both natural immunity and vaccine immunity offer similar substantial absolute protection from serious infection, for those in an age group already less likely to have serious infection, that has already made it through one infection without dying a significant population screening event of those most susceptible to serious Covid infection, symptomatic infection from Covid is less likely than for those that have self-identified as at risk and have been vaccinated for but not exposed to Covid.

As fears of wanning immunity may lead to over consumption of limited resources of Covid vaccines globally, a conclusion that is more likely to lead to the unvaccinated seeking vaccination while discouraging the already vaccinated to seek an aggressive booster timeline would be more appropriate as opposed to one that could rationalize seeking natural immunity and encourage frequent boosters to the previously vaccinated.

On 2021-08-28 14:41:37, user RC Cyberwarrior wrote:

I have read comments based on medical studies that individuals who previously had SARS COV2 were 2 -4 times more likely to suffer adverse reactions to the covid vaccines, if vaccinated post initial infection. Some speculate this reaction was related to Antibody-Dependent Enhancement.

On 2021-08-30 00:15:54, user chris amos wrote:

An important paper and carefully conducted study, but it would be useful if the authors would provide a figure or table starting with the overall cohort size, indicating the total numbers of events according to vaccination versus infection or first vaccination among infected. Given the data that are provided I do not know how to accurately calculate a positive predictive value of having been vaccinated, which is another statistic that is of interest. Also, when the authors refer to the analyses as 'multivariate', I think the more accurate way to refer to the analyses is "multivariable". Multivariate would mean that multiple outcomes (vaccinated only, infected only or vaccinated and infected) are jointly modeled, but it seems like the comparison groups are analyzed in separate analyses.

On 2021-08-30 22:42:54, user Chris Curry wrote:

You would think this would be common knowledge seeing as all a vaccine does is simulate a person getting infected in order to force their body into building immunity to the virus. If natural immunity wasn't a thing then vaccination wouldn't be a thing either, but for some reason the country has decided that you have to be either "pro vaccine" or "anti-vaccine" without entertaining any sort of nuance.

On 2021-08-31 22:30:55, user Fully wrote:

Thank you for the interesting and easy-to-understand study - and the clear results: Recovered people are actually much better protected against the now predominant delta variant of Covid-19 and thus less contagious than vaccinated people, even if the infection occurred more than 6 months ago.<br /> Policymakers in Europe, who grant recovered people the same rights as vaccinated people for only 6 months after their infection, should now remove their 6-month rule based on your study results.

Thank you for this from someone who has recovered since one year, who does not want to be vaccinated, because he did well with the disease - me.

On 2021-09-02 09:13:39, user zlmark wrote:

There are several issues with the way the cohort in this study have been formed - the most critical one is the age distribution:

The 60+ group extremely underrepresented - the cohorts contain about 5-6% of people aged 60 and above, whereas they amount to about 31% of the vaccinated people in Israel. And since their own regressions show that the age is a major factor in infectability, such underrepresentation can seriously affect the risk ratio estimates.

On 2021-10-16 15:43:33, user Alex wrote:

Oh and on natural immunity, myself, partner and two children had COVID March 2020, both antibody tests came back May 2021 positive. Currently waiting for the results of an updated one…. We have also not had anything with similar symptoms since but in two weeks I fly to Barcelona with a tonne of red tape because I’m not vaccinated and I don’t find it fair…My partner loses her job along with 40 people in Hampshire social care next month because they opted for no vaccine, a big gap in care looking after our grandparents - good luck with that!- my point is,why is natural immunity not accepted??it’s simple to test for so questions need to be raised!

On 2021-08-30 07:51:38, user Candice Chaplin wrote:

It states that the GENECUBE® HQ SARS-CoV-2 (TOYOBO Co., Ltd.) reagent was approved in October, 2021. As a layman, I don't quite understand this.

On 2021-08-30 14:40:54, user Nathan Johnson wrote:

Hi Sean, table 2 is the attention getting graph with the large drop but it mixes tests at all different ages so it's harder to read. It'd be better to see a graph by time for separate groups of 3 months old, 6 month old and 12 months old (or similar). Since table 4 shows "Overall, we note no significant reductions in development trends." taking out the older groups who didn't drop should make the drop in 2021 even more dramatic, no? Also if masking was used in first few months in children born prepandemic without a drop, could point more strongly to prenatal cause.

On 2021-10-08 05:09:07, user Anya Dunham wrote:

Hi Sean and team, as a scientist and a mom of a 2020 baby, I read your paper with interest. Similar to Pasco, I wondered about the effects of masks. I am also wondering whether babies might have exhibited some form of a 'freeze' response, as some might have not left their homes or neighborhoods much... In an exaggerated example, I would probably do okay on a cognitive test in my home or your lab, but perhaps not so well if I were abducted by aliens... which a lab setting might feel like to babies born during the pandemic.

Similarly, there could be a novelty effect. Given that babies learn by figuring out patterns and experiencing novel events, I wonder if everything in the lab visit was so new that babies who didn't 'freeze' had a harder time paying focused attention to the task at hand. (I see you already mentioned something similar below.) I imagine even following a shape with their eyes might be more challenging if baby is greatly distracted by the novelty of a visit. I can see my summer 2020 baby having this challenge, although he has amazing focus when playing independently at home. I think some measure(s) from the home environment taken by the family would be important here.

Lastly, how did the families join the study? Did they self-identify? (As a side note, I would have liked to see more details in the Methods section - perhaps I am missing an Appendix?) At least where we live, getting an appointment with a pediatrician has been much more challenging during the pandemic. So I wondered if families who had some concerns around their babies' development (even subconscious ones) could have been more likely to join.

On 2021-08-30 15:16:42, user Jeff Brender wrote:

For those wondering about the decrease in PhD respondents from the last version<br /> From the Methods section<br /> "To be included in the analysis sample, participants had to complete the questions on vaccine uptake and intent, and report a gender other than “prefer to self-describe.”. This exclusion was made after discovering that the majority of fill-in responses for self-described gender were political/discriminatory statements or otherwise questionable answers (e.g. Apache Helicopter or Unicorn), and that as a group, those who selected self-described gender (<1% of the sample) had a high frequency of uncommon responses (e.g., Hispanic ethnicity [41.4%], the oldest age group [23.2% >=75 years] and highest education level [28.1% Doctorate]), suggesting the survey was not completed in good faith. "

On 2021-08-30 16:11:49, user Eduardo Amorim ????????? wrote:

Can you please explain how mf is calculated? You ms says "Mf was calculated as described previously [3]." But ref. #3 doesn't explain how mf is calculated -- at least I can't see it.

On 2021-08-31 10:15:07, user Isatou Sarr wrote:

Excellent paper,

the route of therapeutic administration usually plays a pivotal role in immune cells activation, type as well as robustness. Mucosally induced immunological tolerance has become an attractive strategy for diagnostics and treatment of diseases, although there is a need to fully understand the dynamics of mucosal-tolerance immunotherapy as well as efficient antigen delivery and adjuvant systems.

Additionally, the genetically diverse human subjects who also differ significantly in their mucosal flora, nutritional status and previous immunological/environmental exposure, all of which are factors that can been affect mucosal vaccine efficacy.

On the brighter side of life :)))), if practical assays for assessing mucosal immune cells reactivity in research settings are developed as well as methods for predicting efficacy of candidate mucosal immunotherapeutics, harnessing the therapeutic potentials of the<br /> mucosal immune pathway can be a reality.

Thank you.

On 2021-09-01 04:18:17, user John Smith wrote:

Surgical face masks at best have a 3.4 fold decrease in aerosols if worn perfectly, but in this case the typical imperfect fit would drop this down to about a 1 fold decrease. The math in this simulation is far off the mark compared to detailed peer reviewed experiments. Too many incorrect assumptions made in the simulation.

https://www.sciencedirect.c...

On 2021-09-01 17:28:59, user Elle Tigre wrote:

What was the specific time-frame for the 4-fold increase in evolutionary rate?

On 2021-09-04 19:24:55, user melanoficus wrote:

Very encouraging results. I wish these investigators great success in their endeavours to find and implement beneficial treatment protocols that will save lives of those severely effected.

On 2023-01-15 02:42:48, user Peter lange wrote:

I agree with the other commenters. The description of training is inadequate to determine if the dogs are detecting acute and chronic stress, which canines have been trained to do with high reliability. Without further information the conclusions are unsupported by evidence presented.

On 2022-01-13 17:30:19, user jetbundle wrote:

How were the dogs trained? Were they trained on the sweat of infected (symtomatic or asymptomatic?) people or on isolated viruses?

The authors should answer this. That makes the difference whether the dogs simply identify sick patients or whether it has anything to do with the virus.

On 2023-08-08 19:34:44, user Xiaoping Liu wrote:

The author has published this paper in PLoS One with a revised title: "Analytical solution of l-i SEIR model – Comparison of l-i SEIR model with conventional SEIR model in simulation of epidemic curves". PLoS One. 2023; 18(6): e0287196.<br /> Published online 2023 Jun 14. doi: 10.1371/journal.pone.0287196

On 2021-12-25 16:37:09, user Markus wrote:

In the light of the negative vaccine efficiency, why do they conclude that there is the need for massive rollout of vaccinations and booster vaccinations? The vaccines appear to undermine the natural immunity.

On 2022-01-09 17:05:04, user rubenroa wrote:

Any reason for the increased Odd in vaccinated people against other studies in Israel which conclude: "Vaccination with at least two doses of COVID-19 vaccine was associated <br /> with a substantial decrease in reporting the most common post-acute <br /> COVID19 symptoms."https://www.medrxiv.org/con...

On 2022-01-10 23:20:22, user Litawor wrote:

The previous version of this preprint additionally described adjusted <br /> analysis with important covariates related to vaccination status and <br /> vaccination timing. Why is that analysis omitted in this version? <br /> Matching does not remove the need for statistical adjustment.

On 2022-01-13 09:48:09, user zlmark wrote:

There seems to be some discrepancy between the actual calculations and the conclusions drawn in the Discussion section.

Assuming that Copenhagen data provides us with a more reliable estimate of the gatherings size distribution, as the authors themselves seem to suggest, limiting the gatherings of 100+ gives us about 40% reduction in the number of infections in a single infection cycle.

And given that Omicron mean serial interval is estimated to be around 2.2, this means that about 3 infection cycle happen in a week, and 40% reduction in single cycle leads to about 80% reduction in a week.

On 2022-01-13 14:50:32, user Erik Petersen wrote:

One of the findings that is going to be predominantly taken from this study is that, "vaccinated individuals have significantly lower IVTs." However, upon looking at the data in Figure 4A specifically, we see just under 3 (2.9?) FFU/ml in unvaccinated individuals compared to ~2 FFU/ml in vaccinated individuals. Would you please explain how this constitutes a "significant" reduction?

On 2022-01-17 19:49:07, user AW wrote:

Some errors in text and tables I’m afraid. In text you report the IRR for men <40 years as “7.60 (2.44 - 4.78)” for 3rd dose for Pfizer which clearly is nonsensical -looks you have used the 95%CI for second dose repeated in error. And you have reported the number of events as * for 3rd dose Pfizer in men under 40 years in table rather than number - should have a numerical value.

Given these are probably the most important impactful data you present it’s a bit embarrassing to not get this right - but shows why peer -review is needed (and makes me wonder what else might be incorrect)

On 2022-01-19 16:21:44, user xavier wrote:

Hi, fig 4/inset d, shouldn't line one of the first line read "infection WA1" instead of "infection B1"? <br /> Thanks

On 2022-01-23 21:31:37, user maa jdl wrote:

This paper is a total nonsense!<br /> Why applying the Benford law?<br /> There is no reason. And the paper does not contradict that!<br /> On the contrary.<br /> You just need to look at the data to understand WHY the Benford law doesn't apply!<br /> This is what I did and ONE simple picture can reveal it in a much clearer way than a long paper with a lot of references. This can be done with no references at all! The chi² test is useful there only to give numbers on what is obvious from the picture.

On 2021-10-13 17:03:08, user constantinos schinas wrote:

very interesting article. can you breakdown the calculation for the ie. <br /> 13,080 tests, 100 positives, 20% FNR and 0,8%FPR, in a way we can replicate it in an excel document? In two cases, stable 20%FNR and variable 0-40% FNR.

thank you in advance

On 2022-01-27 21:22:51, user Michael Klar wrote:

They have NOT done their homework:

This investigation uses no suitable surrugate for human aerosols. These consist mostly of mucin5 and this is a hydrogel. Hydrogels behave differently than the one used Serum. This is reflected in the Shrinkage factor of 2.5 versus 4-5 in humans.

The results of the preprint should not be evaluated, as another previously published study shows that the liquid composition is crucial for the inactivation rate:

https://www.pnas.org/conten...

On 2022-01-28 20:26:50, user Dylan Arroyo wrote:

What happens to the patient with a suicidal ideation while they wait for sobriety? Are they restrained/sedated? Do they wait in the waiting room until they have sobered up before they can be seen by a social worker?

On 2022-02-02 06:38:43, user Marcel Zwahlen wrote:

The fulll paper is now out here on Ann Int Medicine

https://www.acpjournals.org...

On 2022-02-02 19:32:41, user Eric D wrote:

This is on Sky News as<br /> BA.2 "More likely to infect vaccinated people"!

SSI report is ambiguous<br /> https://en.ssi.dk/news/news...

The headline<br /> "BA.2 is more transmissible than BA.1 but vaccinated persons are less likely to be infected and to pass on infection"<br /> contradicts a sentence that looks badly-written or edited<br /> "In addition, comparing the risk of household members being infected in BA.2 relative to BA.1 infected households, was higher in vaccinated and booster vaccinated than in unvaccinated, which suggests immune evasive properties of the BA.2 variant."

On 2022-02-08 07:24:12, user Ole Stein wrote:

Misleading and biased conclusions based on wrongfully datatreatment, where they have mixed vaxed with unvaxed, and so unvaxed included all vaxed less than 14 days since last shot and all vaxed include unvased post illness. Such mix is not just unetical, but makes the conclusion completely useless as it does not say anything about contamination between vaxed and unvaxed as they are mixed in their data input. The report should be discarded and removed as fraudulent science.

On 2022-02-07 07:06:22, user kdrl nakle wrote:

5 days after sympton onset? Apparently flawed sampling. You showed nothing as Omicron has faster clearance anyway.

On 2022-02-07 23:20:52, user A440 wrote:

The report says: "The analyses were adjusted for [...] booster dose and time since last dose among the vaccinated."

For those of us wondering whether to get a booster dose, it would be good to know more about how this adjustment was done.

On 2022-02-17 10:51:48, user Sandeep Sharma wrote:

where do I find the latest on COVAXIN approval in Germany?

On 2022-02-22 02:12:34, user Juliet French wrote:

Nice paper. You may want to check out one of our papers. Moradi Marjaneh et al, Genome Biology 2020. PMID: 31910864. Some similarities between yours and ours.

On 2022-02-23 03:43:25, user Sam Wigginton wrote:

Deaths in South Africa are still climbing steadily three months after the Omicron infection peak (according to Worldometer). The case fatality rate (assuming 3 week lag) appears to have risen from 0.7% three months ago to about 8% now. What's going on?

On 2022-03-23 16:58:16, user Stefan Baeuml wrote:

It would be interesting to have a follow up study in the presence of Omicron. In particular, given the increased likelihood of breakthrough infections, it would be interesting to see if the likelihood of the symptoms mentioned in the 'Results' section still remains within the background of people without SARS-CoV-2 infection.

On 2022-04-08 12:13:33, user Tommy Brothers wrote:

The peer-reviewed version of this manuscript is now published online in Drug and Alcohol Dependence

https://doi.org/10.1016/j.drugalcdep.2022.109440

On 2022-04-11 18:32:10, user ReviewNinja wrote:

Thanks you for this fast publication. This publication confirms:<br /> - that people can be reinfected with BA.1 after delta infection<br /> - that people can be reinfected with BA.2 after BA.1 (but that this seems rather a rare event)

However, this publication shows some clear limitations that would need some discussion:<br /> - This publication gives an advice on testing policy, but does not discuss the testing policies at the moment of the study. This is important as this policy changed over the period of the study and was different during some periods for vaccinated and non-vaccinated individuals. Also a correction for testing behavior over time per age group would be useful. <br /> - The publication compares the number of reinfections (01/12 to 10/03) to the vaccinated population on 10/03. As the advice for vaccination for children 5-11 only came out on 15/12, this is an overestimation for the whole study period. The same is true for boosters in the younger age groups. <br /> Vaccination % at the different periods in the study: <br /> %For each age group (age in 2021) on: 01/12, 01/01, 07/02 and 10/03<br /> 5-11y (2 doses): 9 (probably most already 12y), 10, 20, 41<br /> 12-17y (3 doses): 0.5, 2, 11, 33<br /> 18-44y (3 doses): 7, 25, 70, 75<br /> 45-64y (3 doses): 13, 56, 88, 89<br /> The changing vaccination rate over time should be taken into account, or this comparison should not be made. Furthermore, most measured reinfections were in the first study period (<feb 7:="" 91="" of="" the="" 96="" reinfections).="" some="" other="" points="" to="" discuss:="" -="" the="" conclusions="" (and="" abstract)="" are="" rather="" strong.="" to="" advise="" a="" change="" in="" (pcr-)testing="" policy,="" at="" least="" reinfection="" versus="" residual="" pcr-detection="" should="" be="" compared="" discussed.="" reinfection="" during="" this="" short="" period="" measured="" in="" this="" paper="" is="" 0.16="" and="" 0.01%="" (with="" off="" course="" all="" biases="" and="" limitations).="" we="" know="" from="" a="" challenge="" study="" that="" 1="" 3="" young="" people="" (in="" these="" conditions="" in="" this="" small="" study)="" still="" test="" (low)="" positive="" after="" 28="" days="" for="" example="" (https:="" <a href="www.nature.com" title="www.nature.com">www.nature.com="" articles="" s41591-022-01780-9).="" -="" how="" was="" the="" n-gene="" cut="" off="" determined="" here?="" (it="" would="" be="" of="" added="" value="" to="" also="" confirm="" which="" percentage="" really="" resulted="" in="" detectable="" virus="" (specially="" for="" study="" period="" 2).)="" additionally,="" a="" look="" at="" the="" viral="" loads="" might="" be="" of="" added="" value,="" as="" done="" by="" the="" study="" by="" stegger="" (ref="" 9).="" they="" suggest="" a="" more="" transient="" infection="" upon="" reinfection="" with="" ba.2="" after="" ba.1.="" (would="" be="" nice="" to="" know="" the="" testing="" indications="" for="" these="" people="" as="" well.)="">

On 2022-05-11 01:52:14, user bioRxiv wrote:

This preprint is participating in the Comment-a-thon pilot initiative by bioRxiv/medRxiv at the Biology of Genomes CSHL meeting. You can enter the competition if you are registered for this conference by signing up using the link provided at the meeting. Remember to add #BoG22 to your comments.

On 2022-06-14 13:31:27, user Peter J. Yim wrote:

This comment is to clarify that the study showed an unequivocal benefit from ivermectin in COVID-19. From the abstract, the primary outcome considered in the study was: "...time to sustained recovery, defined as achieving at least 3 consecutive days without symptoms." The outcome did not reach statistical significance for that outcome. However, for the related secondary outcome "mean time unwell" the outcome was statistically significant and favored ivermectin.

MTU was estimated "...from a Bayesian, longitudinal, ordinal regression model with covariates age (as restricted cubic spline) and calendar time." The principal finding of the study was that there was a statistically significant difference in MTU between the treatment and control groups: -0.49 (95% CrI: -0.82, -0.15) where CrI refers to "credible interval". The negative range of the 95% credible interval indicates that MTU was lower for the treatment group than the control group.

The authors conclude that the trial "...did not identify a clinically relevant treatment effect ...". The magnitude of the treatment effect found in this trial may or may not be clinically relevant, but clinical relevance is not a statistical quantity and establishing it was not a goal of the trial.

On 2022-06-18 09:09:00, user David Escors wrote:

The preprint is still a work in progress before submitting it for publication. It has an error in the definition of the cohort and in Table 1. The correct statement defining the cohort previous to the correction of the manuscript would be :"The majority of patients were smokers, 75% male and the mutational status of the tumors was not evaluated in 96.4% of the patients".

On 2022-08-01 00:35:38, user JJ wrote:

Looks like some numbers are inconsistent, eg 146 vs 158 and 303 vs 301 in the unmasked group.

On 2025-11-11 14:07:07, user Evolutionary Health Group wrote:

We at the Evolutionary Health Group ( https://evoheal.github.io/) "https://evoheal.github.io/)") really enjoyed this paper.

Here are our highlights:

The authors applied metagenomic sequencing to samples from multiple wastewater treatment plants to characterize the diversity and abundance of antibiotic resistance genes. Using a standardized bioinformatics pipeline, they quantified ARG classes relative to total microbial DNA, and compared treatment efficiency across plants.

They observed that water leaving the treatment plant still harbored a broad spectrum of ARGs, including multidrug-resistance genes.

The authors describe wastewater treatment plants as both sources and potential intervention points for antibiotic resistance by emphasizing that improved engineering and coordinated antibiotic-management strategies could limit the spread of resistance genes in urban systems.

These findings indicate that monitoring of municipal wastewater may serve as a real-time surveillance tool for community-level antibiotic resistance burden and inform outbreak preparedness.