Frosted Flake posted:

I went for a light nordic ski, I planned for about 3 hours, yesterday after work. About 2 hours in I felt nauseous, then clumsy, then weak, and then I could barely get out of my bindings and stay conscious while I sat down and propped myself up against a tree. It took me about 20 minutes to recover.

I know I didn’t have hypothermia, and I wasn’t pushing nearly hard enough to have overexerted myself. What was the guidance for sports after covid?

e: Back when I used to push myself into the black I would use smelling salts to get back into it but there’s a shortage right now, and if this is an after effect of covid, I’m assuming they won’t work?

silicone thrills posted:

i just have to try my best to make sure i can get to a safe place to sit and wait it out.

https://www.science.org/doi/10.1126/scitranslmed.adk1599 posted:

Editor’s summary
Interrogating Infection in Immunosuppression. Individuals who are immunosuppressed remain at increased risk of severe COVID-19, but this heterogenous patient pool should not be considered a monolith. Here, Li et al. asked whether the extent of immunosuppression a person has influences their ability to develop immunity and clear SARS-CoV-2 infections. The authors found that severe immunosuppression due to hematologic malignancy or transplant resulted in the longest time to viral clearance. These individuals also had evidence of increased intrahost viral evolution associated with resistance to antibody therapy and were marked by impaired humoral and T cell responses. Individuals with severe immunosuppression due to autoimmunity or B cell deficiency had, expectedly, impaired humoral responses but intact T cell responses, and those with nonsevere immunodeficiency had intact SARS-CoV-2–specific immunity mostly comparable to control participants. Together, these results highlight the importance of considering the type and severity of immunosuppression an individual is experiencing when considering their antiviral immunity. —Courtney Malo

Abstract
Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but the immune defects that predispose an individual to persistent coronavirus disease 2019 (COVID-19) remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median times to nasal viral RNA and culture clearance in individuals with severe immunosuppression due to hematologic malignancy or transplant (S-HT) were 72 and 40 days, respectively, both of which were significantly longer than clearance rates in individuals with severe immunosuppression due to autoimmunity or B cell deficiency (S-A), individuals with nonsevere immunodeficiency, and nonimmunocompromised groups (P < 0.01). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing resistance against therapeutic monoclonal antibodies. Both S-HT and S-A participants had diminished SARS-CoV-2–specific humoral responses, whereas only the S-HT group had reduced T cell–mediated responses. This highlights the varied risk of persistent COVID-19 across distinct immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.
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Delayed viral clearance was observed in participants in the S-HT cohort
We first aimed to characterize viral dynamics in the upper respiratory tract in participants with different categories of immunocompromising conditions. Immunocompromised and nonimmunocompromised participants had similar peak viral RNA loads (5.1, 5.1, 4.9, and 5.7 log10 SARS-CoV-2 copies/ml in S-HT, S-A, NS, and nonimmunocompromised groups; P = 0.5). However, the rates of nasal viral RNA decay were different between the immunocompromising categories, with the S-HT group demonstrating slower viral clearance compared with other groups (Fig. 1, A and B). Median time to nasal viral RNA clearance in the S-HT group was 72 days [95% confidence interval (CI): 5, not available (NA)] compared with 10 (7, NA) days for the S-A group, 12 (9, 17) days for the NS group and 13 (13, 15) days for the nonimmunocompromised group (log-rank, P = 0.002; Fig. 1B). Similarly, the S-HT group experienced a delay in the clearance of culturable virus (Fig. 1, C and D). Median time to viral culture clearance in the S-HT group was 40 days (95% CI: 5, NA) compared with 6.5 (5, NA) days for the S-A group, 6 days (5, 7) for the NS group, and 7 days (6, 7) for the nonimmunocompromised group (log-rank, P < 0.001; Fig. 1D). At or after 30 days from symptom onset or first positive test, 50, 15, and 6.5% of participants from S-HT, S-A, and NS groups had detectable viral RNA compared with 0% in the nonimmunocompromised group (P < 0.0001; fig. S1A). In addition, 50% of S-HT and 8.3% of S-A participants still had culturable virus compared with 0% in the NS and nonimmunocompromised groups after 30 days (P < 0.0001; fig. S1B). Viral dynamics for participants who did not clear viral RNA after 30 days (table S3) are shown in fig. S1C. Compared with the nonimmunocompromised group, the S-HT group was significantly associated with delayed viral RNA clearance [adjusted hazard ratio (aHR) for viral clearance of 0.29, 95% CI: 0.11 to 0.74, P = 0.009) and culturable virus clearance (aHR of 0.27 for viral clearance, 95% CI: 0.12 to 0.62, P = 0.002), after adjusting for demographics, number of vaccinations, and antiviral use (Table 2). To validate this finding, we also performed restricted mean survival time (RMST) analysis that does not require proportional hazard assumptions. Similarly, the S-HT group required significantly longer times to clear nasal SARS-CoV-2 viral RNA (adjusted RMST ratio of 3.09, 95% CI: 2.16 to 4.40, P < 0.0001) and culturable virus (adjusted RMST ratio of 3.33, 95% CI: 2.16 to 5.14, P < 0.0001) (Table 2).


Fig. 1. Kinetics of SARS-CoV-2 viral RNA and culturable virus varied among the immunocompromised groups.
(A) Upper respiratory viral RNA decay is shown. The lower level of quantification (LLOQ) is 10 copies/ml. (B) Kaplan-Meier estimates of upper respiratory viral clearance are shown (viral load below LLOQ), and global log-rank P values were shown. For (A) and (B), n = 12, 13, 31, and 184 for S-HT, S-A, NS, and nonimmunocompromised groups, respectively. (C) Upper respiratory culturable virus dynamics were quantified as TCID50 values. (D) Kaplan-Meier estimates of upper respiratory culturable virus clearance were shown, and global log-rank P values were shown. For (C) and (D), n = 12, 12, 31, and 184 for S-HT, S-A, NS, and nonimmunocompromised groups, respectively.
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Increased SARS-CoV-2 evolution and genetic diversity were observed in immunocompromised participants
We used a gene-specific next-generation sequencing approach to quantify the number of unique intrahost single-nucleotide variants (iSNVs) in the S gene, encoding the spike protein, present at >3% frequency of the total viral population within each sample. This analysis was limited to participants with a viral genome available both at baseline and at a minimum of one follow-up time point. Severely immunocompromised (S-HT and S-A) participants harbored a greater number of emergent iSNVs over time compared with NS and nonimmunocompromised group participants (Fig. 2A). To evaluate viral diversity, we calculated the average pairwise distance both at the nucleotide and at the amino acid level per day. Nucleotide average pairwise distance per day was significantly higher in the severe immunocompromised (S-HT and S-A) groups compared with either nonsevere (P = 0.001 using Dunn’s test with Benjamini-Hochberg adjustment) or nonimmunocompromised groups (P < 0.001 using Dunn’s test with Benjamini-Hochberg adjustment; Fig. 2B). Similar results were obtained when the average pairwise distances were calculated for amino acids (fig. S2A). Among participants with longitudinal sequences available, 39% of the participants in immunocompromised group versus 12% in the nonimmunocompromised group had evidence of viral nucleotide changes (Fisher’s exact P < 0.001; Fig. 2C and fig. S2B). These nucleotide changes were distributed across the entire length of the S gene (fig. S2B).


Fig. 2. SARS-CoV-2 intrahost mutations vary among different immunocompromised groups.
(A) Numbers of iSNVs among severe (S-HT in red and S-A in green), nonsevere immunocompromised, and nonimmunocompromised (none) groups that emerged after the baseline time point are shown. (B) Nucleotide average pairwise distance (APD) are shown among the severe (S-HT in red and S-A in green), nonsevere immunocompromised (NS), and nonimmunocompromised (none) groups. (C) Percent of participants with any nucleotide changes during follow-up is shown. IC, immunocompromised. (D) Proportion of individuals with evidence of mAb resistance, categorized by those with severe or nonsevere/no immunosuppression, is shown. (E) Heatmap showing distribution of spike protein polymorphisms from participants receiving mAb treatment longitudinally. In the heatmap, the y axis indicates participants’ IDs (PID) followed by sequential numbers of sample collection, and the x axis shows amino acid positions in the spike protein. Different domains of the spike protein are shown at the top. Colors indicate frequency of polymorphisms, with blue indicating the lowest value and red indicating the highest value on the scale. Participants in different study groups are separated by a red horizontal line. mAb resistance mutations are shown by red dotted boxes. Comparisons of iSNV and APD between groups in (A) and (B) were done using Dunn’s test with Benjamini-Hochberg P value adjustment. Fisher’s exact test was used in (C) and (D) to calculate significance between participants with and without viral evolution and in participants with and without mAb treatment–specific resistance mutations. Only significant P values are shown. NTD, N-terminal domain; RBD, receptor binding domain; RBM, receptor binding motif; S1, subunit 1; S2, subunit 2. Data in (A) and (B) are presented as Tukey’s boxplots, with box indicating median and interquartile ranges and whiskers indicating 1.5× interquartile range.

Severely immunocompromised individuals had increased risk of resistance to anti–SARS-CoV-2 mAb therapy
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Five of nine (56%) severely immunocompromised participants (S-HT and S-A) developed mAb-specific resistance mutations (Fig. 2, D and E). This was a significantly higher rate than that found in the nonsevere or nonimmunocompromised groups [0/11 (0%) combined, Fisher’s exact, P = 0.008; Fig. 2D]. In addition, a longer infection duration was associated with increasing accumulation of mutations (fig. S2C).

Suboptimal humoral responses were elicited by infection in severely immunocompromised participants
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The nonimmunocompromised group exhibited an increase in anti-ancestral and anti-variant spike protein–specific nAb titers during follow-up, whereas we did not observe a significant increase in antibody titers in the immunocompromised groups (Fig. 3, A and B). However, after excluding individuals with exposure to mAb therapies, the nonsevere immunocompromised group demonstrated a moderate increase in spike protein–specific nAb titers, whereas the severe immunocompromised group showed no changes; the nonimmunocompromised group demonstrated the greatest increase in nAb titers, plateauing between days 25 and 30 (Fig. 3, C and D).


Fig. 3. Differences in nAb and nucleocapsid-binding Ab titers were observed among the different immunocompromised groups.
(A and B) nAb titers were quantified as the ID50 against ancestral spike protein (A) and variant spike proteins (B). Variant-specific nAb titers were generated using a pseudoviral assay with the same spike protein variant (e.g., Delta, BA.1, BA.2, and BA.4/5) as that infecting the participant. (C and D) Longitudinal trajectories of nAb titers are shown for the different immunocompromised groups, including (C) or excluding (D) mAb use. For (A to C), n = 5, 7, 17, and 65 for S-HT, S-A, NS, and nonimmunocompromised groups, respectively. For (D), n = 4, 3, 13, and 57 in the S-HT, S-A, NS, and nonimmunocompromised groups after excluding mAb use. (E) Binding Ab titers against nucleocapsid protein were quantified for the indicated groups at the indicated time points. (F) Longitudinal trajectory of binding Ab titers is shown for the different immunocompromised groups. For (E) and (F), n = 7, 8, 18, and 111 for S-HT, S-A, NS, and nonimmunocompromised groups, respectively. Comparisons between different immunocompromised groups at the same time point in (A), (B), and (E) were performed using Dunn’s test with Benjamini-Hochberg P value adjustment. Comparison of longitudinal Ab changes for participants with two blood draws were performed using the pairwise Wilcoxon rank sum test with Benjamini-Hochberg P value adjustment. Only significant P values are shown. Tukey boxplots were used to summarize Ab titers in (A), (B), and (E). A generalized additive model was used to evaluate the trend of Ab development in (C), (D), and (F), with 95% CIs in the shaded area. Lines between two time points indicate the same participants with two blood draws. The severe group included both S-HT and S-A, because they had comparable Ab titers at multiple time points.
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Diminished T cell responses to spike protein were observed in the S-HT group
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DISCUSSION
Understanding viral and immune control characteristics of COVID-19 infection is crucial to our ability to care for immunocompromised individuals at the greatest risk of persistent and severe infection. Moreover, it can guide public health interventions and shed light on vaccine development that protects immunocompromised individuals. In this study, we performed an in-depth virologic and immunologic evaluation of a cohort of immunocompromised and nonimmunocompromised individuals. We demonstrated a hierarchy of immunocompromised conditions that increase the risk of delayed viral clearance and SARS-CoV-2 evolution, especially in those where both B and T cell responses are suppressed. Specifically, we found that individuals with a history of hematological malignancy and organ transplant demonstrated the greatest delay in viral clearance that may be mediated by suppression of both B and T cell responses. In contrast, those with B cell immunodeficiency had an intermediate risk of chronic infection in the setting of an immune response, showing the likely protective effect of a heightened SARS-CoV-2–specific T cell function.
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In this study, we used S gene–specific deep sequencing to assess longitudinal viral evolution and diversity. Our results show that severe immunosuppression is associated with increased viral evolution and diversification. In addition, severely immunocompromised hosts had a greater risk of developing treatment-emergent resistance mutations to mAb therapy when compared with nonimmunocompromised participants. These findings highlight the potential for immunocompromised individuals to serve as a source for SARS-CoV-2 evolution and drug resistance, consistent with isolated reports of immunocompromised hosts implicated in the emergence of highly mutated SARS-CoV-2 variants. It should be noted that, even within the category of severe immunocompromise, participants demonstrated a range of viral diversification and evolution patterns, and additional studies are needed to fully assess the drivers of accelerated viral evolution.
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In conclusion, in this prospective cohort of well-characterized individuals with acute COVID-19, we demonstrated a correlation between a hierarchy of immunocompromised conditions and SARS-CoV-2 viral shedding, viral evolution, and adaptive immunity. Our results highlight the finding that the risk of chronic SARS-CoV-2 infection is not uniform across immunosuppressive conditions and provide clarity on which immunosuppression conditions predispose individuals to delayed SARS-CoV-2 RNA and culture clearance as well as viral evolution. The high-risk populations identified in this study may benefit from targeted public health and additional therapeutic interventions. In addition, the results provide further insights on the humoral and cell-mediated immune correlates of viral clearance, which is crucial for the development of improved vaccines and future therapies.
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https://www.statnews.com/2024/01/24/covid-research-chronic-infection-immunocompromised-patients/ posted:

New chronic Covid study offers insight into which immunocompromised patients are most at risk

Animal-Mother posted:

Olympic Judo Wrestler Maricet Espinosa González Dead at 34 After Heart Attack

Okay, I'm absolutely going to write a will now. If this poo poo is taking out Judo champs, it will definitely take out this Jewish chef.

https://www.ajicjournal.org/article/S0196-6553(23)00820-9/fulltext#%20 posted:

Highlights
• Viral aerosols from toilet flushing pose a possible route of pathogen transmission.
• Toilet lid closure prior to flushing is believed to mitigate cross-contamination.
• We show toilet lid closure prior to flushing does not mitigate cross-contamination.
• Brushing toilet bowl without disinfectant results in contamination of surfaces.
• The use of a disinfectant during bowl cleaning reduces cross-contamination of surfaces.

Background
Viral aerosols generated during toilet flushing represent a potential route of pathogen transmission. The goal of this study was to determine the impact of toilet lid closure prior to flushing on the generation of viral aerosols and cross-contamination of restroom fomites.

Methods
A surrogate for human enteric viruses (bacteriophage MS2) was added to household and public toilet bowls and flushed. The resulting viral contamination of the toilet and other restroom surfaces was then determined.

Results
After flushing the inoculated toilets, toilet seat bottoms averaged >107 PFU/100 cm2. Viral contamination of restroom surfaces did not depend on toilet lid position (up or down). After toilet bowls were cleaned using a bowl brush with or without a commercial product (hydrochloric acid), a >4 log10 (>99.99%) reduction in contamination of the toilet bowl water was observed versus no product. Bowl brush contamination was reduced by 1.6 log10 (97.64%) when the product was used versus no product.

Conclusions
These results demonstrate that closing the toilet lid prior to flushing does not mitigate the risk of contaminating bathroom surfaces and that disinfection of all restroom surfaces (ie, toilet rim, floors) may be necessary after flushing or after toilet brush used for the reduction of virus cross-contamination.

https://www.cidrap.umn.edu/covid-19/closing-toilet-lid-flushing-doesnt-keep-viral-spray-inside-study-suggests posted:

Closing toilet lid before flushing doesn't keep viral spray inside, study suggests

Pingui posted:

"Impacts of lid closure during toilet flushing and of toilet bowl cleaning on viral contamination of surfaces in United States restrooms"

News article on the matter:

Pingui posted:

Has anyone in the thread received free Paxlovid that looks like this?


And if so: how and where?

bred posted:

Our boxes have been the same and match the google image search for paxlovid. My wife is on her second box for the 10 day treatment. First was from CVS and second from T2T. She notes an obvious change in the degree of paxlovid mouth. The CVS box had a very strong taste and reminded her of the moment immediately after vomiting, leading to some nausea. The T2T box had a much weaker flavor and is manageable. I don't have the info but I think T2T was several months older. It had an expiration extension paper with it.

My wife has been testing negative since day 6. We were talking about how I probably got her infected when we ended isolation in the days before my cytokine storm/paxlovid rebound. If the second phase is a function of ending paxlovid, than she is also at risk of having a similar result on a similar timeline and exposing us so she'll isolate through day 13 or 14. We originally planned to end her isolation Friday night Day 11 if things continued to go well so this only adds a couple more nights on the couch. I'm glad she's having such a mild time.

Our symptoms now are just higher HR and easy exhaustion. Today is day 9 for her and 19 for me. My daily activities are normal except for running the dog. I'm walking the dog about a mile a day. Usually we're running 2-4 miles every other day. I'm not even trying to run until March. Energy wise, I only hit the wall a handful of times. I remember at one point walking home from my daughter's school and there is a slight incline that got my heart going and I started sweating and thinking this might be too much but made it home. I haven't noticed any brain issues but I'm not in the best position to judge. My daughter is still testing negative and has had no symptoms.

I printed a calendar at the beginning and am reviewing the numbers: symptoms and isolation for the household has lasted 21 days and is on track to last 24 or 25. We've used 3 boxes of paxlovid and 67 tests so far. Mostly RATS and 1 Luciera and 3 or 4 Metrix. Maybe 10-12 masks? I don't really track them. Thank you thread for the links to mask reviews and deals. We've each found the best mask for us and get them in bulk. And thank you for the deals on RATs. I had some 25EA boxes that came out to a few dollars per test.

Pingui posted:

"Impacts of lid closure during toilet flushing and of toilet bowl cleaning on viral contamination of surfaces in United States restrooms"

News article on the matter:

fosborb posted:

it is

Petey runs marathons and had ridiculously rigorous testing and bespoke care around overall heart health after COVID while he got back into training, and it was still weeks of reduced activity

Frosted Flake posted:

Thanks, I'll dig them up.

Pingui posted:

It should be no surprise that immunodeficient have different viral kinetics, but seeing the distinction between different types as the authors demonstrate here, is pretty important.
"SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency"

News article/interview on the matter:

Pittsburgh Fentanyl Cloud posted:

https://www.wired.com/story/theres-a-huge-covid-surge-right-now-you-probably-didnt-notice/

The flu is really loving bad!! lmao

RandomBlue posted:

second biggest wave but we have good population immunity



how the gently caress does that work you dumb assholes?

Tzen posted:

lol i just learned today that several family friends households all got hit with covid last week
lol, lmao

Rescue Toaster posted:

Thanks very much for posting this. Going to take me some time to parse it all. I'm on an immunosuppressant medication that's commonly used for solid organ transplant recipients, which would presumably put me in the highest group. However in the actual PDF tables, I see one participant was on my exact medication and considered non-severe. Though dosing can vary and I'm on other immunosuppressant drugs too that are normally not considered extreme, so hard to know where I'd fall on this.

Also a lot of it was focused on mabs and not paxlovid, so some of that is less relevant now.

bizwank posted:

There's a bunch of different sources for Covid deaths broken down by age/sex online, and motorcycle deaths in the US top out at around 5500/yr, but it's probably easiest to just use this site (which uses CDC data): https://oddsofdying.com/

It's noteworthy that as a rider who 1) always wears safety gear including a full-face helmet, 2) took a rider safety course and 3) doesn't ever drink and ride, my personal odds of being in an accident and/or dying from one are significantly lower then the average rider. And yet none of those precautions stop me from enjoying riding whenever I want aka. "living my life", and it only took a small expenditure of time and money to ensure I'm partaking in that activity as safely as possible.

https://eu.usatoday.com/story/opinion/voices/2024/01/26/long-covid-paxlovid-costs-plaguing-american-healthcare/72337750007/ posted:

Bernie Sanders: US is turning its back on long COVID. We'll pay the price if we don't act.
'As millions of Americans deal with the ramifications of long COVID, how sad it would be if we learned nothing from all that we have done wrong?' Sen. Bernie Sanders writes.

https://www.theguardian.com/lifeandstyle/2024/jan/26/experience-i-woke-up-from-a-covid-coma-with-newborn-twins posted:

Experience: I woke up from a Covid coma with newborn twins

quote:

In March 2020, I was healthy and enjoying being 24 weeks pregnant with twins, which had come as a joyful surprise. Then I contracted Covid-19, probably at work. I’m a rheumatology consultant at Birmingham city hospital, and had been risk-assessed to work from home. But I have a duty of care to my patients and went to the hospital for some in-person commitments. Hospitals, including ours, were increasingly overwhelmed by Covid patients.

quote:

In all, I was in hospital for six weeks and the twins spent 116 days in the neonatal ICU. I am forever grateful that our care was managed by such excellent colleagues. The NHS doesn’t always blow its own trumpet when it does great work like this.

https://time.com/6588624/covid-19-antiviral-treatments-us/ posted:

COVID-19 Antiviral Drugs Promise Speedier Recoveries. But They’re Not Available in the U.S.
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A study published in the New England Journal of Medicine in January showed promising results associated with the drug simnotrelvir, which is made by Simcere Pharmaceutical and is currently available in China under the brand name Xiannuoxin.
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It’s unclear whether Simcere is seeking FDA approval; representatives from the company did not respond to TIME’s requests for comment about if and when it may apply.
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At the moment, the drug with perhaps the best shot at cracking the U.S. market seems to be the antiviral ensitrelvir, which is made by the pharmaceutical company Shionogi & Co., Ltd., and has been approved in Japan under the brand name Xocova since 2022. In April 2023, the drug received “Fast Track” designation from the FDA, a status meant to expedite the agency’s review process.
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Portsmouth declined to comment on ensitrelvir’s regulatory timeline, saying only that Shionogi needs to complete additional clinical trials before anything else can happen. (Last year, the CEO of Shiongi & Co., Ltd., estimated the drug could be approved in the U.S. at some point in 2024.) The company has also signed a licensing agreement that will allow ensitrelvir to be manufactured and distributed in 117 countries, pending appropriate regulatory approvals, to boost access in low- and middle-income nations.

In a statement provided to TIME, an FDA spokesperson said the agency “remains committed to providing product-specific advice to drug developers to facilitate the development of new drug products to treat or prevent COVID-19.” But it did not comment on the likelihood or timing of simnotrelvir, ensitrelvir, or other COVID-19 antivirals receiving approval.

It would be good for Americans to have antiviral choices, Topol says, but the regulatory process for new drugs can be long and winding. “If [other antivirals] do come here,” he says, “it’s probably not going to be imminent.”

Pingui posted:

New long COVID just dropped:

quote:

Even when I saw the babies, I thought it was a dream and they weren’t mine

https://www.reuters.com/business/healthcare-pharmaceuticals/covid-beyond-labs-unite-boost-genomic-surveillance-globally-2024-01-25/ posted:

COVID and beyond: labs unite to boost genomic surveillance globally
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But Sillitoe said he feared assets needed for the process - like sequencing machines bought in the pandemic - were now "sitting idle" in some countries, which would be a missed opportunity.

"We have a lot of blind spots, both on pathogens and on regions," said Tulio de Oliveira, director of the Centre for Epidemic Response and Innovation at Stellenbosch University, the other lab in the partnership. During COVID, his team confirmed the discovery of the Beta and Omicron variants.

De Oliveira, who will also join the GSU as a deputy director, said the potential for other diseases was huge.

For example, work by the two labs, as well as a global climate-related disease consortium, has doubled the number of sequences available for dengue, chikungunya, and malaria-carrying mosquitoes in just the last year, he said.
(..)

quote:

The ongoing coronavirus disease 2019 (Covid-19) pandemic continues to inflict an important burden on global health and health care systems worldwide.1 Vaccination can lessen the effect of the disease in high-risk groups but is less effective in preventing infections caused by emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with strong immune evasion.2,3

quote:

A total of 1208 patients were enrolled at 35 sites in China; 603 were assigned to receive simnotrelvir and 605 to receive placebo.

quote:

We initiated this trial on August 19, 2022, in China.

https://www.theatlantic.com/health/archive/2024/01/long-covid-exercise-post-exertional-malaise/677242/ posted:

‘If Exercise Could Cure This, I Would Have Been Cured So Quickly’
Striving for fitness is usually healing. But for most people with long COVID, it can be toxic.
(..)
Those interventions are still experimental—and Putrino said that no single one is likely to work for everyone. That only adds to the challenge of studying PEM, which has been shrouded in disbelief for decades. Despite years of research on ME/CFS, Chu, of the IACFS/ME, told me that many people with the condition have encountered medical professionals who suggest that they’re just anxious, even lazy. It doesn’t help that there’s not yet a blood test for PEM; to diagnose it, doctors must ask their patients questions and trust the answers. Just two decades ago, researchers and physicians speculated that PEM stemmed from an irrational fear of activity; some routinely prescribed therapy, antidepressants, and just pushing through, Chu said. One highly publicized 2011 study, since widely criticized as shoddy science, appeared to support those claims—influencing treatment recommendations from top health authorities such as the CDC.

The CDC and other organizations have since reversed their position on exercise and cognitive behavioral therapy as PEM treatments. Even so, many people with long COVID and ME/CFS are still routinely told to blow past their limits. All of the long-haulers I spoke with have encountered this advice, and learned to ignore it. Fighting those calls to exercise can be exhausting in its own right. As Ed Yong wrote in The Atlantic last year, American society has long stigmatized people who don’t push their way through adversity—even if that adversity is a medically documented condition that cannot be pushed through. Reconceptualizing the role of exercise in daily living is already a challenge; it is made all the more difficult when being productive—even overworked—is prized above all else.
(..)

Platystemon posted:

Some hospital administrator absolutely blew their own trumpet years before for just‐in‐time inventory that saved pence by not stocking minor niceties like FFP3 respirators for use in the event of an airborne pandemic.

https://www.theguardian.com/politics/2024/jan/25/uk-government-wasted-nearly-10bn-on-unused-covid-ppe-figures-show posted:

UK government wasted nearly £10bn on unused Covid PPE, figures show
Accounts reveal £9.9bn of the £13.6bn spent on PPE during pandemic has been written off

https://thehill.com/opinion/finance/4427204-removing-draconian-budget-cuts-isnt-enough-bring-back-the-covid-safety-net/ posted:

Removing draconian budget cuts isn’t enough: Bring back the COVID safety net
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With COVID-19 cases rising again, public health programs and health research could get a cut. After Republican lawsuits blocked debt relief for student borrowers, Pell Grants for low-income students may get a cut. Amid rising poverty after pandemic-era aid programs were cut back, food assistance, rental assistance, support for infants and children and other help for low-income people are subject to the freeze and possible cuts.

This is simply bad policymaking. Vital pandemic assistance programs in the 2021 American Rescue Plan grew the economy, reduced overall poverty by 20 percent and cut child poverty in half. But when Congress failed to renew them, 2022 saw a historic spike in poverty. Millions more Americans lost health care last year as Medicaid “unwound,” and homelessness hit a record high just last month.

This fall, Biden sent an emergency $1.4 billion domestic spending request to fill an increased need for childcare assistance and the critical Women, Infants and Children Program, or WIC. WIC helps pregnant, postpartum and nursing parents and their babies with groceries, breastfeeding, health care and other critical assistance. Thus far, it has not been included in any spending bill or stop-gap funding bill.

One huge successful pandemic-era program, the expanded Child Tax Credit, may return in limited form — though Congress unnecessarily links helping struggling children to helping wealthy corporations. The package contains an insufficient but necessary $33 billion Child Tax Credit expansion but hooks it to a $35 billion tax giveaway for businesses.

The new Child Tax Credit expansion would help some 400,000 children out of poverty and make 3 million children less poor in its first year. By contrast, the Institute on Taxation and Economic Policy estimates that the fully expanded Child Tax Credit from the American Rescue Plan would help 60 million children in the first year alone if enacted again.

Skewing national priorities away from the well-being of our nation’s families isn’t the only thing wrong with the budget. That $886.3 billion for the Pentagon is only part of the militarization of our federal budget.
(..)

Steve Yun posted:

anyone know what the CADR of a 10” corsi cube is

https://www.massgeneral.org/news/press-release/mgh-facing-unprecedented-capacity-crisis posted:

JAN | 19 | 2024
Massachusetts General Hospital Facing Unprecedented Capacity Crisis

Almost four years after the start of the COVID-19 pandemic, Massachusetts General Hospital (MGH), a founding member of the Mass General Brigham health care system, continues to struggle daily with unprecedented overcrowding – particularly in its Emergency Department (ED). For the past 16 months, the MGH ED has operated nearly every day in “Code Help” or “Capacity Disaster” status, which represents critical levels of ED crowding.

As patient volume grows, the ED’s status can change from “Normal Operations” to “Pre-Code Help” to “Code Help” and finally to “Capacity Disaster”. “Code Help” occurs when inpatient beds and monitored hallway stretchers are full, and “Capacity Disaster” is triggered when the ED is full, all hallway stretchers are being used and there are more than 45 inpatients boarding in the ED awaiting a hospital bed.

A patient “boarding” in the ED is a patient who is sick enough to be admitted to the hospital but must remain in the ED because there are no available hospital beds – and this wait time is in addition to the time the patient spent waiting in the ED to be seen initially to receive treatment. For the 12 months spanning October 2022 to September 2023, patients boarded in the MGH ED for a total of 381,228 hours, a 32% increase from the previous 12-month period. In September 2023, patients admitted to the hospital boarded for a median of 14.1 hours per patient, and 26% of admitted patients boarded in the ED for more than 24 hours. These patients are often waiting in stretchers or chairs in hallways or in other temporary spaces. On January 11, there were 103 patients boarding in the ED, marking one of the most crowded days MGH has experienced in its two centuries caring for Boston and its surrounding communities.

“While hospital overcrowding has significantly affected patient care for many years, COVID-19 and the post-pandemic demand for care has escalated this challenge into a full-blown crisis – for patients seeking necessary emergency care, as well as for staff who are required to work under these increasingly stressful conditions,” said David F.M. Brown, MD, the current President of MGH and former Department Chair of Emergency Medicine at MGH. “This crisis is most acutely felt in our ED, where patients wait hours for an inpatient bed. Put simply, every day between 50 and 80 patients spend the first night of their hospitalization in the ED, which is not an appropriate or therapeutic environment for anyone and contributes significantly to clinician burnout and frustration.”
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https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(24)00013-0/fulltext posted:

Summary
Background
COVID-19 survivors may experience a wide range of chronic cognitive symptoms for months or years as part of post-COVID-19 conditions (PCC). To date, there is no definitive objective cognitive marker for PCC. We hypothesised that a key common deficit in people with PCC might be generalised cognitive slowing.

Methods
To examine cognitive slowing, patients with PCC completed two short web-based cognitive tasks, Simple Reaction Time (SRT) and Number Vigilance Test (NVT). 270 patients diagnosed with PCC at two different clinics in UK and Germany were compared to two control groups: individuals who contracted COVID-19 before but did not experience PCC after recovery (No-PCC group) and uninfected individuals (No-COVID group). All patients with PCC completed the study between May 18, 2021 and July 4, 2023 in Jena University Hospital, Jena, Germany and Long COVID clinic, Oxford, UK.

Findings
We identified pronounced cognitive slowing in patients with PCC, which distinguished them from age-matched healthy individuals who previously had symptomatic COVID-19 but did not manifest PCC. Cognitive slowing was evident even on a 30-s task measuring simple reaction time (SRT), with patients with PCC responding to stimuli ∼3 standard deviations slower than healthy controls. 53.5% of patients with PCC's response speed was slower than 2 standard deviations from the control mean, indicating a high prevalence of cognitive slowing in PCC. This finding was replicated across two clinic samples in Germany and the UK. Comorbidities such as fatigue, depression, anxiety, sleep disturbance, and post-traumatic stress disorder did not account for the extent of cognitive slowing in patients with PCC. Furthermore, cognitive slowing on the SRT was highly correlated with the poor performance of patients with PCC on the NVT measure of sustained attention.

Interpretation
Together, these results robustly demonstrate pronounced cognitive slowing in people with PCC, which distinguishes them from age-matched healthy individuals who previously had symptomatic COVID-19 but did not manifest PCC. This might be an important factor contributing to some of the cognitive impairments reported in patients with PCC.
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Fig. 1 Patients with PCC were slower than people without PCC, including those who had previously contracted COVID-19. (A) Simple Reaction Time (SRT) task contained a total of 16 trials. The mean RT for each group is shown in (B) with each dot representing individual data and the error bar showing ± 1 SD. Except for the first two trials, which were exceptionally noisy and sluggish, the mean RT was calculated from all trials for each participant. PCC Ox indicates the PCC Oxford group. The value at the bottom of each bar indicates the mean of that group. (C) To account for the effect of age on response speed, all participants' speed were adjusted based on the No-COVID controls in the same age. Z-score indicates the number of standard deviations from the age-matched normative population. The coloured circles indicate individual results and the black solid line marks the group mean. The horizontal dash black line indicates the threshold for severe impairment (2 SD). (D) Throughout the SRT, PCC participants (pink curve) reacted significantly slower than the other two groups. RT was computed for every trial in SRT across participants and plotted against the trial index. The shaded area shows ±1 SEM and the horizontal lines at the bottom indicate time intervals where bootstrap statistics confirmed significant differences between two groups (P < 0.05). While there was no difference between No-COVID (grey) and No-PCC (blue), PCC (pink) was significantly slower than No-COVID throughout the SRT task (pink-grey stripy horizontal line at bottom) as well as No-PCC (pink-blue stripy horizontal line). (E) To replicate the result seen in SRT, all participants completed the same task again after the second task. (E) The group mean for both sessions of SRT is plotted with group as separate lines. No-COVID (grey line) and No-PCC (blue line) showed a normal performance in both sessions (below the threshold for moderate impairment (>1 SD). In contrast, PCC (pink line) showed severe impairment (>2 SD) in both sessions. The error bar indicates 1 standard error of mean. (F) On the individual level, most of No-COVID and No-PCC controls had a normal speed (<1 SD) while most of patients with PCC showed significant impairment.
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Is cognitive slowing associated with mental health?
Depression and sleep deprivation may increase RT. Patients with PCC exhibited moderate to severe depressive symptoms and substantially less restful sleep compared with the two control groups (Table 1), consistent with previous reports of high prevalence of mood and sleep dysregulation after COVID-19 infection.29 However, age-adjusted RT in SRT showed no relationship with self-reported depression (PHQ-9 and HADS), anxiety (HADS), fatigue (FAS and BFI), sleep disturbance (PSQI and ESS), or post-traumatic stress disorder (PTSS-14) (all r values < 0.27, P values > 0.087). The relationships between cognitive slowing and all questionnaire-derived mental phenotypes are visualised as a network plot in Fig. 2, in which the strength of the relationship is represented by the distance between the metrics. RT, located at the top of Fig. 2, showed a clear dissociation from the mental health phenotypes which were closely related to each other, clustering on the right side of the figure.


Fig. 2 Network plot of relationships between the cognitive slowing (age-adjusted RT in SRT, highlighted with pink dashed rectangle) and all self-reported metrics (bottom cluster) amongst the patients with PCC. All depicted relationships are associated with a positive correlation and are rendered in blue. The shorter the distance between two metrics, the stronger their relationship (the higher the correlation coefficient). PHQ-9: Patient Health Questionnaire-9. HADS: Hospital Anxiety and Depression Scale. FAS: Fatigue Assessment Scale. BFI: Brief Fatigue Inventory. PSQI: Pittsburgh Sleep Quality Index. ESS: Epworth Sleepiness Scale Sleep Test Questionnaire. PTSD: Post-Traumatic Stress Disorder Test. Although depression did not predict the cognitive slowing, the combination of depression level and age-adjusted speed in SRT and number vigilance test (NVT) predicts PCC accurately.
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Patients with PCC were slow and less vigilant
Next, we asked if the PCC slowing is also present in a cognitively more demanding task than the SRT. To investigate this, we used NVT, a paced vigilance test which emphasises that participants should try to be accurate in their responses, with RT being an implicit measure (Fig. 3A). Similar to their slowness on the SRT, patients with PCC took substantially longer to react to targets compared to healthy controls (Fig. 3B), regardless of whether the controls had COVID-19 previously or not (Table 1). The slowness was maintained throughout the entire course of 9 min (Fig. 3C). Importantly, RT on the NVT was strongly associated with the slowness observed in SRT, as age-adjusted RT in SRT alone could explain 35.4% of variance in age-adjusted RT in NVT amongst patients with PCC (F (1179) = 30.7, P < 0.001). Overall, patients with PCC showed mild, yet significant, cognitive slowing (Fig. 3D) and a smaller proportion of patients with PCC showed severe impairments in this task (i.e., people whose speed was slower than 3 SD from the healthy controls in their age, Fig. 3E).


Fig. 3 Patients with PCC responded slower and worse at detecting targets in the Number Vigilance Test (NVT). (A) Following the SRT, all participants completed the NVT, in which a number between 0 and 9 was displayed at 1 Hz and it was displayed for 0.1 s while being masked by a transparent checkerboard. Participants were instructed not to press anything if the number was between 1 and 9 and press spacebar as soon as possible when seeing the target number 0. The frequency of the target “0” was low (25%) and would not happen consecutively. The mean RT over 9 min for each group is shown in (B), and the mean RT for every minute of this test was plotted against the time (C). n.s. means no significant difference. ∗ means P < 0.05, ∗∗∗ means P < 0.001 and passes multiple comparison corrections. The shaded area shows ±1 SEM and the horizontal lines at the bottom indicate time intervals where bootstrap statistics confirmed significant differences between two groups (P < 0.05). (D) To account for the effect of age on RT in the NVT, all participants' speed were age-adjusted based on the No-COVID controls in the same age. Z-score indicates the number of standard deviations from the age-matched normative population. The coloured circles indicate individual results and the black solid line marks the group mean. The two horizontal dash black lines indicate the thresholds for moderate (>1 SD) and severe impairments (>2 SD). (E) The pie charts show the proportion of individuals who had a normal speed (<1 SD, green area), moderate impairment (>1 SD, yellow area) and severe impairment (>2 SD, red area) in this test. The mean accuracy during this task is plotted in (F) and against time in (G). PCC (pink) was significantly less vigilant than No-COVID throughout the SRT task (pink-grey stripy horizontal line at bottom).

Again, cognitive slowing on this task could not be explained by depression (GLM of age-adjusted RT with normalised PHQ-9 score and group; no interaction [F (1271) = 0.24, P = 0.63], no effect of PHQ-9 [F (1271) = 0.0.04, P = 0.84], but significant effect of group [F (1271) = 18.21, P < 0.0001]) or sleep disturbance (GLM with normalised PSQI score and group; no interaction [F (1202) = 0.55, P = 0.46], no effect of PSQI [F (1202) = 0.06, P = 0.80], but significant effect of group [F (1202) = 39.45, P < 0.0001].

In addition to slowing, patients with PCC were also less vigilant to visual stimuli compared to the uninfected participants (Fig. 3D, t (305) = −3.95, P < 0.0001, BF10 = 194.7). However, the vigilance level could not distinguish if an infected individual was experiencing PCC or not (no significant difference between PCC and No-PCC groups: t (255) = −0.95, P = 0.34 BF10 = 0.24; Fig. 3F). Patients with PCC also showed good maintenance of vigilance over time (Fig. 3G). Although their accuracy significantly declined over time (t (193) = −3.5, P < 0.001, BF10 = 25.3), the decrement was minimal in magnitude (slope of accuracy over time = −0.005 ± 0.002 min−1), statistically similar to the No-PCC and No-COVID controls (Table 1).

Could patients with PCC deliberately slow down to maintain accuracy (aka, speed-accuracy trade-off, SAT)? The results showed the converse: RT negatively correlated with accuracy (Fig. 4A, r ≤ −0.54, P < 0.001 in all three groups), indicating that slower individuals actually had lower vigilance too. This pattern remained true within individuals: patients with PCC with a higher tendency for SAT (i.e., blocks with longer RT associated with higher accuracy, Fig. 4B) were poorer performers overall in both accuracy and speed (Fig. 4C).


Fig. 4 The slowness in PCC cannot be explained by speed-accuracy trade-off (SAT). (A) RT is negatively correlated with accuracy in the NVT across participants in every group. Pearson's r and P values for all participants are shown at the top right and those for each group are shown at the bottom left of the graph. The SAT index for each group is shown in (B) with each dot representing individual data and the error bar showing ± 1 SD. SAT index for every participant is computed as the correlation coefficient of RT and accuracy for every minute. On the group level, PCC didn't show any difference in the tendency to employ SAT in this test, as the SAT index is not significant above zero. (C) Comparing the objective performance within each group, between participants with high SAT index (i.e., median split of SAT index, shown in the right-hand side dark colour bars) and the rest. n.s. means no significant difference. ∗ means P < 0.05.

One possibility for the good vigilance in PCC is that in order to reach good performance, patients worked harder. To examine this, we asked participants to rate their fatigue after every minute in NVT (“on-task tiredness”). Patients with PCC with normal response speed felt substantially more tired (55.3 ± 2.2%) than other participants with normal speed (46.4 ± 2.2%, t (265) = 2.9, P = 0.004, BF = 6.4), suggesting they found sustaining attention on task more demanding.

Cognitive slowing and depression distinguish PCC from healthy infected individuals
We then analysed which factors—mental health symptoms and objective cognitive metrics—were most effective in distinguishing infected individuals with PCC from other infected individuals without PCC, i.e., sensitivity for correctly assigning group membership to PCC. We selected all the metrics that showed significant group differences in this study and ranked them according to their importance in predicting PCC in infected individuals (i.e., PCC or No-PCC, Fig. 5A). The rank represents the negative log of the P values. Depression level was the best predictor, followed by RT in the SRT and in NVT. These three were significant predictors of the group (all P < 0.0001), while PSQI and other key metrics in the NVT were not.
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Is cognitive slowing related to severity and time elapsed after acute COVID-19?
Importantly, patients with PCC without being hospitalised due to COVID-19 also showed significant cognitive slowing compared to non-hospitalised No-PCC participants (t (83) = 3.69, P < 0.0001, BF10 = 66.6). This indicates that the cognitive slowing observed in PCC was not merely due to the acute illness of COVID-19.

Fig. 6A demonstrates that patients with PCC hospitalised due to COVID-19 showed significantly lower accuracy in the NVT but no difference in RT in either task./b] Even after removing the cases with ICU admission[ (n = 4), the WHO severity scale remained significantly negatively correlated with the mean accuracy in NVT (Kendall r = −0.18, P = 0.007).


Fig. 6 How did the acute COVID-19 infection affect objective performance? (A) Although hospitalised individuals, regardless of PCC status, demonstrated no difference in RT in SRT (left) or NVT (middle), they were significantly less accurate (right). N (No PCC inpatients) = 7, N (No PCC outpatients) = 56, N (PCC inpatients) = 32, N (PCC outpatients) = 125. (B) No difference was found between patients with PCC with and without pre-existing psychiatric conditions prior to COVID-19. N (PCC with pre-existing conditions) = 31, N (PCC without pre-existing conditions) = 80. (C) In NVT, age-adjusted RT was marginally negatively correlated with time from infection in No-PCC participants, implying a gradual recovery (left). Cognitive slowing, however, was strongly positively correlated with time from infection in PCC group. n.s. means no significant difference. ∗ means P < 0.05, and ∗∗ means P < 0.01.

Pre-existing psychological or neurological conditions did not differentiate patients with PCC on objective performance neither (Fig. 6B). Given that depression was the most prevalent of the pre-existing conditions here (45%, see Supplementary Materials), this result is consistent with the absence of the aforementioned relationship between depression and cognitive slowing in PCC.

Does the cognitive impairment get better with time? Patients with PCC showed the reverse trend: prolonged duration of PCC was linked with more severe cognitive slowing (r = 0.21, P = 0.003, Fig. 6C).
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[b]Here we found that the cognitive slowing in PCC does not seem to resolve on its own. Instead of a gradual recovery (a negative relationship between time from infection and RT) an opposite trend was present amongst patients with PCC; patients who experienced PCC longer had more severe cognitive slowing. However, we must be cautious about the interpretation of the relationship with time since infection in the cross-sectional data. Specific variants of SARS-CoV-2 may be an important risk factor on cognitive slowing, as self-reported PCC symptoms are more common in the earlier waves before the Omicron variant.3,35 Thus, longitudinal studies with computerised speed tests in both patients with PCC and those without PCC are needed to further confirm the group difference in relationship with time since infection.
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Pingui posted:

Piece on PEM (just an excerpt, but it is good in its entirety):

Archived link: https://archive.vn/aMtQQ

Livo posted:

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One of my colleagues pre-Covid was teaching a Continued Professional Course overseas, and to her absolute horror, she had to explain to a large group of American physiotherapists this general concept: they were like "Huh? I've been making my ME/CFS clients do 2 hours of high intensity exercise three times a week and berating them for being lazy when they struggle to do basic tasks for the week, what do you mean I shouldn't do this?"

Livo posted:

bred posted:

Our boxes have been the same and match the google image search for paxlovid. My wife is on her second box for the 10 day treatment. First was from CVS and second from T2T. She notes an obvious change in the degree of paxlovid mouth. The CVS box had a very strong taste and reminded her of the moment immediately after vomiting, leading to some nausea. The T2T box had a much weaker flavor and is manageable. I don't have the info but I think T2T was several months older. It had an expiration extension paper with it.
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bizwank posted:

There's a bunch of different sources for Covid deaths broken down by age/sex online, and motorcycle deaths in the US top out at around 5500/yr, but it's probably easiest to just use this site (which uses CDC data): https://oddsofdying.com/

It's noteworthy that as a rider who 1) always wears safety gear including a full-face helmet, 2) took a rider safety course and 3) doesn't ever drink and ride, my personal odds of being in an accident and/or dying from one are significantly lower then the average rider. And yet none of those precautions stop me from enjoying riding whenever I want aka. "living my life", and it only took a small expenditure of time and money to ensure I'm partaking in that activity as safely as possible.

Petey posted:

bespoke care from my cardiologist, the medical director of the boston marathon, and yeah, the tldr was — minimum of a couple weeks of total rest, then a careful and graded return to play.

FWIW: in my case, I was able to return to training much more quickly than this thread would advise. looking at last january's calendar, i tested positive on jan 1, rebounded on jan 8 or 9, was antigen positive until jan 19. started short runs and lifting on the 22nd, then was doing two medium to long runs a week (extending by 1-2 miles a week) every week through the marathon in april, with hot yoga and some lifting on the other days.

but my activity was definitely "reduced" (below pre-covid infection baseline) for a month — i didn't do anything but maybe a few easy slow walks during my infection, just to get out of the house — and the grading-back-up period was 2-3 weeks. so i suppose it was basically 6 weeks before i was pushing back.

i also had the benefit of previously mentioned bespoke medical care, which included preexisting prophylactic measures to reduce my risk of heart attack or stroke (daily baby aspirin and pharmacologically keeping LDL under 40 mg/dl), and, when i had something that felt like maybe palpitations in march, cardiologist gave me a wearable ekg that i trained in for a week, during which we were able to monitor my ticket 24/7 and make sure everything was all right. all of that made me much more confident that there was nothing bad going on, but only because i could get that kind of care.

(though for most goons, you can monitor your lipids/lp(a) through your doctor or ultalabtests and then bring your risk down significantly with good old statins/ezetimibe, even if you don't qualify for pcsk9 inhibitors like i do)

lmk if you need help finding/parsing. i know it's got to be frustrating and in my case i was really worried i was not going to be able to run boston, which was pretty important to me last year. and somewhere in there i did try an easy slow walk of a distance i would have run before my infection — i think it was 6 miles two weeks in — and that knocked me out for two days. i was worried i was cooked. but a few weeks later i was fine. so don't panic, don't push it in the first month.

Livo posted:

I currently work as a sole trader who contracts out to a private company & shared clinical treatment space, so I have to buy all my PPE supplies. My situation is a little different & unusual I admit but I try to work around it:

I wear long life N95 masks whenever I see clients: the mask is hand washable and air dried, but the N95 filter is non replaceable and lasts a few months before the filter is replaced as per the instructions. It gets less hot on my face, and the ear loops are large & don't cut into my face. Yes, disposable N95 masks are better protection wise and provide more of a better seal depending on their type, but I've found that they get very uncomfortable to wear whilst physically active (mainly they get hot real fast and the disposable string ear pieces are bloody awful), since my job is much more physical demanding than an Occupational Therapist or Speech Therapist. I could wear a disposable N95 mask if I was mostly sat behind a desk all day but I can't really do that in my line of work. Plus here, buying long life N95 masks is generally cheaper than buying a disposable N95 and using a fresh one every day. My clinical space is shared with another clinician who owns it outright: they have a basic air filter set up at the moment, but I might have to bring in a very small one since if they change their mind on it. I have one at home but it's a bit too big to bring in, so a small one that I can comfortably carry in a little bag would have to do. Not that happy about it but it's not my clinic sadly.

Public Health in Australia is a mixed bag: there's N95 masks given for some clinicians, but not others depending on the health district & some EPs (my area) aren't given one, only surgical masks so they have to buy their own N95s. As for private health, it's a crap-shoot: either good N95 masks and great filtering, or stuffy air & surgical masks only, even in cancer treatment private clinics.There are some Long Covid clinics here and the current treatment guidelines given specifically for EPs since 2021 has been "Long Covid is like ME/CFS, so your treatment methods should be similar!" so it's a bit positive. This message isn't really being given to other health professionals though, which would make a big difference IMHO.

I'll try to dig up some specific Australia clinician info about the benefits of filtering (for example, a Melbourne Hospital study early in the pandemic found commercial HEPA filters were effective in reducing Covid particles, which was quite useful as a) this was during a cold Melbourne winte and b) hospitals don't have open-able windows for the most part), N95 masks & good ventilation, but I would imagine a lot of this info would have been posted already here or elsewhere in the SA forums. I would suggest that the physio have commercial air purifier(s) in the treatment/assessment bays (even ones that fit on a desk if they are very close to the patient/physio) & also in the break room and the writing up notes location they use, but especially the treatment bays.

It's currently 2am here so I'll be a while before I reply, sorry I can't be of much help at the moment.