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Category Archives: Covid-19

Andrew Cuomo Faces House Subpoena Over Covid Deaths in Nursing Homes – The New York Times

Posted: March 10, 2024 at 5:55 am

Former Gov. Andrew M. Cuomo of New York has been subpoenaed to appear before a House subcommittee to answer for his administrations handling of nursing homes during the coronavirus pandemic, reigniting a flashpoint that could further damage his chances at a political comeback.

The Republican-led Select Subcommittee on the Coronavirus Pandemic accused Mr. Cuomo of recklessly exposing nursing home residents to the virus with deadly consequence.

The subcommittee chairman, Representative Brad Wenstrup of Ohio, said in a letter sent Tuesday to Mr. Cuomo that there was troubling evidence suggesting the Cuomo administration at best downplayed the effects of its nursing home policies and at worst covered them up.

The subpoena is the latest in a multiyear saga surrounding the former governors decision to require nursing homes to accept residents who had tested positive for Covid-19 in the spring of 2020. The decision, which presaged a virus outbreak in those facilities leading to thousands of deaths, has drawn broad scrutiny from state and federal investigators.

In January 2021, the New York State attorney general, Letitia James, a Democrat, concluded that the state had severely undercounted deaths in nursing homes charges that were validated when the state later revised its figures upward some 40 percent. But while her offices report found that returning residents to their facilities may have put residents at increased risk, it stopped short of blaming the governors policy for nursing home outbreaks, acknowledging that the policy was consistent with federal guidance at the time.

The former governor, also a Democrat, has repeatedly denied that the policy led to additional deaths.

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It’s been 4 years since COVID hit Michigan. For Long COVID patients, the pandemic isn’t over. Michigan Advance – Michigan Advance

Posted: at 5:55 am

Four years have passed since Gov. Gretchen Whitmer declared a state of emergency to address the COVID-19 pandemic on March 10, 2020. But the disease remains more than a memory, especially for those whose lives are continually impacted by the illness.

Robert McCann, 46, was exposed to COVID-19 at a Lansing-area veterinary clinic which was tied to an outbreak of the disease in June 2020. About a day after testing positive, McCann, the executive director of the K-12 Alliance of Michigan, said he started to feel sick.

At the time, it wasnt anything, like, horrible and the symptoms went away probably after a week or so, McCann said. I figured, OK, that wasnt too bad, Ive moved on.

In the fall, McCanns symptoms returned and persisted, despite testing negative for the illness. More than three and a half years later, McCann says he still faces issues with severe fatigue, nerve pain and brain fog from Long COVID.

Overall, you know, I consider myself one of the more fortunate ones, McCann said.

Theres days I struggle a little more than others to be sure, but you know, Im able to function reasonably well the majority of the time and theres people out there that arent, McCann said.

But describing his fatigue symptoms to others has proved difficult.

Theres a connotation there, or at least that you worry about sometimes, that people just think youre lazy, McCann said.

There are nights where I will be so tired that I will sleep for 15 hours, and I still cant wake up in the morning. Just I have no energy and its hard to really describe that to people, McCann said. There are days where its hard to do your job. Theres days where its hard to, you know, do the things you enjoy doing.

Prior to developing Long COVID, McCann said hed done quite a bit of traveling and hiking.

Ive been fortunate to kind of get all over the world, he said. In like 2019, I did a hike through the Austrian Alps that was pretty astonishing, quite frankly.

Im still fortunate that I can do some of that, but there are days where its like, yeah, thats not going to happen today, McCann said.

As far as seeking solutions for Long COVID, You name it. Ive probably tried it, McCann said. From clinical treatments, to supplements to prescription medication, none have had a major impact on his condition.

While McCann has received his COVID-19 vaccine and boosters, he said it has not helped relieve his symptoms in the way others with Long COVID have reported.

There are some people that do seem to have found some relief from that from various things, and Im certainly glad to see that. But for me, it just wasnt the case, McCann said.

According to the World Health Organization, there have been more than 7 million reported deaths worldwide from COVID-19 since Dec. 31, 2019, with 1.2 million deaths in the United States. As of March 5, Michigan has reported 44,654 deaths from the disease.

Vaccines became widely available by spring 2021, and now 70% of the Michigan population is fully vaccinated, the same as the U.S. rate.

Visible signs of the pandemic have all but disappeared. Its been almost three years since Whitmer removed capacity limits on indoor and outdoors events and ended the states masking requirement in June 2021.

And thankfully, the number of COVID deaths has been ramping down. Although the state recorded more than 9,000 deaths among confirmed cases of COVID-19 in 2022, that number dropped to just over 2,300 in 2023.

But while the World Health Organization declared an end to the global emergency posed by the virus on May 5, 2023, the body noted this does not mean the pandemic is over.

Long COVID continues to present challenges for medical professionals working to treat the condition, despite breakthroughs in vaccines and antiviral medications since the pandemic began. An August 2022 Brookings Institution report, which analyzed Census Bureau survey information, estimated that 16 million people of working age in the U.S. suffer from Long COVID.

Arianna Perra, a psychologist for Mary Free Bed at Munson Healthcare in Traverse City who leads a Long COVID recovery group, said the tricky thing about treating the condition is that it has around 200 documented symptoms.

Everyones profile is slightly different. The most common ones that we see in the COVID rehab setting and psychology setting are related to fatigue and brain fog, like cognitive dysfunction, Perra said.

According to an article published in Nature Reviews Microbiology, many Long COVID patients experience dozens of symptoms across multiple organ systems. The condition also encompasses a number of adverse outcomes, with common new-onset conditions including Type 2 diabetes, myalgic encephalomyelitis/chronic fatigue syndrome, cardiovascular, thrombotic and cerebrovascular disease and dysautonomia, particularly POTS, a condition that can cause a fast heart rate, dizziness and fatigue while transitioning from laying down to standing up.

A 2024 University of Michigan study also found that individuals with a chronic overlapping pain condition were at greater risk for developing Long COVID conditions.

According to the National Institutes of Health (NIH), individuals who experienced severe illness from COVID-19, people who experienced multisystem inflammatory syndrome during or after their illness, and people with underlying health conditions like diabetes, asthma, autoimmune diseases or obesity are more likely to develop Long COVID. Women, people of color, sexual and gender minorities and people without college degrees are also more likely to have Long COVID.

Studies have also found that the COVID-19 vaccine dramatically lowers the risk of developing Long COVID.

In treating Long COVID, Megan Jabin, an occupational therapist for Mary Free Bed, emphasized the importance of a multidisciplinary approach.

Even if maybe the patient is coming in and then only, originally, has a referral for physical therapy, the other disciplines are always looking out for can we have speech therapy or occupational therapy or psychology involved based on what the patients main concerns are, based on what their goals are, and what their symptoms are, Jabin said.

While every Long COVID patient presents symptoms differently, one of the main attributes is that patients are often deconditioned, have a difficult time maintaining their stamina and have overall weakness, Jabin said.

In a multidisciplinary treatment, physical therapists will usually focus on strengthening and endurance as it relates to a patients mobility, while a speech-language pathologist will focus on cognition and brain fog and memory issues. An occupational therapist will focus more on helping patients achieve their day to day independence including dressing, bathing and grocery shopping, Jabin said. In some cases, getting back to driving has also been an issue.

All of these disciplines, including psychology, work together, especially when a patient is more receptive to a particular treatment, or education from their therapists, Jabin said.

For psychological treatment, Perra said Long COVID is approached from a rehabilitation perspective similar to treatment for a stroke or a major car accident.

That also includes helping patients who may be frustrated with the lifestyle changes included as part of their treatment.

Figuring out how to pace is a really important part of the rehab process. And that is tackled with [physical therapy], right, so figuring out how to find the right dose of movement so that we can get stronger and build our tolerance for exercise and our energy stores, Perra said.

From a psychological perspective, how do I deal with the fact that I might be really annoyed or irritated that I have to pace myself, or I might fall into the trap of thinking, Well, Ill just push myself through it and then Ill deal with it later, and then being in an extreme amount of fatigue and being down for the count for a few days also impacts my mental health and my relationships with other people, Perra added.

Its not just finding the right dose of movement to help people build their strength and stamina. Addressing barriers and thought processes, and looking at how treatment can impact relationships with others, and how to receive support from people when a patient may need to rest, Perra said.

The hardest thing about making any behavioral change is not the act. It is what is between our ears, right? Its our cognitive processes, its our expectations, assumptions, predictions, how we compare ourselves to our pre-COVID lives. And so psychology has a lot of skills to be able to recognize when were caught in unhelpful loops and to manage that, Perra said.

When treating brain fog, treatment focuses on strategies to address sympathetic nervous system responses, Perra said.

A lot of folks were told or given the message that it can't be that bad, or it's all in your head or you know, I had COVID too and I recovered just fine. So I think there's a lot of folks that were coming to our program feeling like they weren't believed.

Arianna Perra, psychologist for Mary Free Bed at Munson Healthcare in Traverse City

Were understanding more and more about how the nervous system is affected by COVID in the long run. Its not just that people are anxious, right? This isnt caused by anxiety. There are functional changes in how our body regulates itself. So learning strategies to downshift, how to stimulate our rest and digest response, those are really specific health psychology strategies we can learn, Perra said.

One of the most effective ways someone can counteract their bodys stress response is through controlling the rate and rhythm of their breath through breathing exercises and learning how to decrease muscle tension, Perra said.

The life-changing nature of Long COVID can also bring mental health symptoms, Perra said. Depression is fairly common in patients, as well as anxiety, in regard to symptoms getting worse or being reexposed to COVID-19.

Its also not uncommon to see traumatic responses from being hospitalized or from the active illness phase, Perra said.

From a mental health perspective, not only are we sort of mourning the loss of the life we thought we would have, at this point after COVID were also dealing with some of the mood changes, sleep changes, how we think about things changes. So psychology is an integral part to that treatment plan, Perra said.

How Long COVID has become the silent pandemic

Additionally, research suggests COVID-19 may impact serotonin production, so the illness is not only disrupting peoples lives in functional ways, but changing the way their bodies produce hormones and chemicals needed to effectively manage their mood, Perra said.

While theres still a lack of research surrounding Long COVID, Perra said one of the biggest changes that has changed since she began treating the condition in 2021 was the amount of evidence in support of symptoms reported by patients.

A lot of folks were told or given the message that it cant be that bad, or its all in your head or you know, I had COVID, too, and I recovered just fine. So I think theres a lot of folks that were coming to our program feeling like they werent believed, Perra said.

We still lack evidence. We still lack research. Theres more and more coming out. And Im really heartened by that, Perra said. Being able to tell someone, yes, this is why we think this is happening for you and theres research to support that, its really relieving and validating for patients to hear that.

Looking at the Long COVID recovery group, theres a powerful aspect to being around others who may not share the exact same story, but can understand someones frustration in not being able to get up from the couch and load a dishwasher when they were previously able to run a household, Perra said.

While we continue to understand Long COVID better, McCann said there are likely more people realizing they have some form of the illness.

As we start figuring this out, you know, I think the best thing that people can do is just have empathy for those struggling with things, McCann said.

Everybodys going through something, right? If someones just like, You know, Im not feeling like Ive got the energy for it today, they dont need a motivational speech from you. They just need, You know, I get it. No problem, McCann said.

One of the most difficult parts of treating Long COVID is the slow progression and the different impacts the condition has on people, Jabin said.

Perra also noted that the rate of improvement differs between patients because of how their symptom profile may be impacted by other health conditions.

This is what I tell folks at the beginning of our group treatments too: People get better. It takes time. Its up and down. Its different. I mean, this is a major medical event in your life, and we have to treat it as such. So its not that theres no guarantee that we can go back to being the same person that we were before you had COVID, just like theres no guarantee that youre going to get back the same level of functioning that you had before your stroke, but there could be, Perra said.

If there's a way to be any less empathetic than denying the very thing that causes so many people to be suffering right now, I don't know what that is.

In her treatment sessions, Jabin said she works with patients on what they enjoy doing before they began experiencing Long COVID symptoms, using small goals to build toward a larger goal, like walking around their neighborhood, going shopping or seeing a movie.

McCann said he is grateful he has been able to find a middle ground with his body to where he is able to travel and go hiking.

There are days where, yeah, Im not climbing a mountain, but I can at least enjoy the atmosphere of where Im at, wander around the city a little bit or something. And, you know, on a good day, I can do more, McCann said.

Its not 100% of how you used to live your life and the things you used to enjoy, but you get to still do them at a level that still makes you happy, McCann said.

McCann also shared frustration at COVID-19 denial.

If theres a way to be any less empathetic than denying the very thing that causes so many people to be suffering right now, I dont know what that is, he said.

On March 1, the Centers for Disease Control and Prevention (CDC) updated its isolation recommendations for COVID-19 and other respiratory viruses, reducing isolation to 24 hours if symptoms have improved and if a fever is no longer present without the use of fever-reducing medication.

With the decision drawing concern and criticism from medically vulnerable individuals, with Long COVID activists arguing the decision ignoring the risk of post-COVID-19 symptoms and the lack of a clear cure.

While it is a laudable goal to have guidelines that are streamlined across common respiratory viruses that are easier to understand, these new guidelines fail to accurately reflect the reality of some of the key differences between COVID, the flu, and RSV, Maria Town, president and CEO of the American Association of People with Disabilities said in a statement.

Efforts to treat COVID more like the flu fail to recognize that COVID is not the flu, COVID is COVID a virus that, per the CDCs own resources, is more contagious than the flu, can cause more severe illness than the flu, causes more post-viral illness than the flu, and is infectious to others longer than the flu, Town said.

There's days I struggle a little more than others to be sure, but you know, I'm able to function reasonably well, you know, the majority of the time and there's people out there that aren't.

As researchers continue to search for a treatment for Long COVID, McCann said another big question was the long term impact. He also called for a reevaluation of the health care system.

I cant tell you how frustrating its been to have doctors want to do various tests on me and my insurance company say, Well, you can do it, but were not paying for it because you dont have a disease that meets the criteria for that, McCann said

I am fortunate that Im in a position where I can still move forward and pay things out of pocket if I need to, but if I were to total up the bills that I pay in the last three years dealing with this, it would be shocking, McCann said.

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It's been 4 years since COVID hit Michigan. For Long COVID patients, the pandemic isn't over. Michigan Advance - Michigan Advance

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4th Anniversary of the Covid-19 Pandemic – erienewsnow.com

Posted: at 5:55 am

"If we don't have our health, we don't have anything," saidEpidemiologist Dr. Becky Dawson. "When our health is threatened, the economy shuts down, our businesses shut down, our schools shut down, our ability to interact, and our social structure shuts down because health is that important."

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Reflecting on 4 years of the COVID-19 pandemic and discussing what’s to come – WBUR News

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Four years ago this Sunday, then-Gov. Charlie Baker declared a state of emergency in Massachusetts due to the emerging COVID-19 pandemic.

The months and years that followed pushed all of us, especially our medical institutions, to the brink. What did we learn from it all? What did we get right or wrong? And how prepared are we for the next pandemic to come?

Radio Boston reflects with esteemed health care leaders and looks forward to an uncertain future.

This program aired on March 8, 2024.

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CDC shortens 5-day COVID isolation, updates guidance on masks and testing in new 2024 recommendations – CBS News

Posted: at 5:55 am

CDC shortens 5-day COVID isolation, updates guidance on masks and testing in new 2024 recommendations  CBS News

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Father, daughter convicted in fraud related to COVID-19 relief – The Cincinnati Enquirer

Posted: February 7, 2024 at 6:20 am

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Supreme Court to weigh whether Covid misinformation is protected speech – STAT

Posted: at 6:20 am

WASHINGTON As social media sites were flooded with misleading posts about vaccine safety, mask effectiveness, Covid-19s origins and federal shutdowns at the height of the pandemic, Biden officials urged platforms to pull down posts, delete accounts, and amplify correct information.

Now the Supreme Court could decide whether the government violated Americans First Amendment rights with those actions and dictate a new era for what role, if any, officials can play in combating misinformation on social media.

The Supreme Court is set to hear arguments next month in a case that could have sweeping ramifications for federal health agencies communications in particular. Murthy v. Missouri alleges that federal officials coerced social media and search giants like Facebook, Twitter, YouTube, and Google to remove or downgrade posts that questioned vaccine safety, Covids origins, or shutdown measures. Biden lawyers argue that officials made requests but never forced companies.

Government defenders say that if the Court limits the governments power, it could hamstring agencies scrambling to achieve higher vaccination rates and other critical public health initiatives. Critics argue that federal public health officials already in the throes of national distrust and apathy never should have tried to remove misleading posts in the first place.

The best way is to have a very vigorous offensive social media strategy, which we didnt have, said Paul Mango, a Trump deputy chief of staff for the Health and Human Services Department who worked closely on Operation Warp Speed, the effort to speed Covid-19 vaccines and treatments to market. Rather than trying to keep bad information off by suppression, why dont we have a strategy that really is very aggressive at propagating accurate information?

Though the Association of State and Territorial Health Officials is not taking a stance on the case or the governments argument that it can ask sites to take social media down, its chief medical officer Marcus Plescia also said the best use of federal public health resources is counter-messaging.

We really are limited to the extent that we can control misinformation, said Plescia. The number one [request from state officials] is we need good messaging thats been tested, and thats shown to be effective.

For their part, social media executives like Meta CEO Mark Zuckerberg have said in the past that they made and altered their content moderation policies on their own. But the tech executives are unlikely to weigh in now, considering they are in the midst of two other firestorms over moderation. One is a suit against a Florida law that would effectively diminish platforms abilities to moderate false and misleading posts. Another is last weeks very public battering by senators demanding more content moderation to protect childrens safety on their platforms.

The recent hearing before the Senate Judiciary Committee, which also called TikTok, Snap and Discord executives to testify, stands in stark contrast to the coronavirus misinformation lawsuit, as it conversely suggests tech companies arent doing enough to police their platforms. At one point, Sen. Josh Hawley (R-Mo.) urged Zuckerberg to stand up and apologize to families in the hearing room for damage caused by Facebook and Instagram use.

Senators from both parties seemed open to peeling back a federal protection of tech companies that host problematic or false content.

It is now time to make sure that the people who are holding up the signs can sue on behalf of their loved ones. Nothing will change until the courtroom door is open to victims of social media, South Carolina Republican Lindsay Graham said.

Bidens lawyers are set to argue that he, and his officials, can make the same type of demands.

A lower courts in this case ruled that the federal government cant put any pressure on social media platforms to censor their content. Under that ruling, even public statements by the president about the teen mental health crisis could be construed as undue pressure, Solicitor General Elizabeth Prelogar argued in a legal filing.

For instance, under that ruling, a White House statement condemning the role social media plays in teens mental health and calling for potential legislative reform might be viewed as coercion or significant encouragement under the Fifth Circuits novel understanding of those concepts, she wrote.

But this case didnt start with mental health, and much of it will likely rest on private rather than public comments from federal officials.

The lawsuit, started by then-Missouri Attorney General Eric Schmitt, reflects a growing trend of state attorneys general mounting politically divisive cases against the federal government. Another state, Louisiana, joined the suit along with three doctors who co-signed a paper on herd immunity, an anti-lockdown activist in Louisiana, and a conservative news site, The Gateway Pundit.

Federal officials began communicating with the social platforms in early 2021, according to court documents. Those communications included White House messages to one site saying to take a post down ASAP and keep an eye out for tweets that fall in the same genre or instructions to another platform to remove [an] account immediately. CDC officials also regularly flagged posts to the companies and in one instance asked what [was] being done on the amplification-side to promote official messaging on coronavirus information.

Later, according to court documents, government officials began asking Facebook and others for data and the details of their moderation policies and standards. They held regular meetings, suggested changes and at least one company created a portal for government requests to be prioritized. After a Washington Post article detailing Facebooks moderation struggle, an official wrote to the company that they felt Facebook was not trying to solve the problem and the White House was [i]nternally considering our options on what to do about it.

In July 2021, federal officials took their frustrations to the public. Surgeon General Vivek Murthy said in a press briefing that modern technology companies have enabled misinformation to poison our information environment, with little accountability to their users.

He added, Were asking them to operate with greater transparency and accountability. Were asking them to monitor misinformation more closely. The same day, he issued his first formal advisory as surgeon general on confronting health misinformation.

Despite a lower court ruling that those statements could be inappropriate pressure, experts who spoke to STAT said its hard to imagine the Supreme Court going that far.

The government does, and should, have the ability to communicate with private entities about the dangers that exist, said Clay Calvert, a senior fellow on technology policy at the American Enterprise Institute. Why this case is so controversial is the inherently political divisiveness of the content in question that divided Republicans and Democrats on matters like mask mandates and Covid vaccines.

The overarching question before the court is whether these actions count as government coercion of a private company, which would be an overstep of its authority. Justice Department lawyers argue that while officials frequently suggested removal or downgrade of posts, they didnt force companies nor did companies always oblige.

An appeals court deemed some officials actions particularly those of the White House potentially coercive, but vastly whittled down a district courts broad prohibition of government officials correspondence with social media companies. In doing so, they laid the groundwork for some communications particularly the CDCs alerts on changing recommendations and explainers on true vs. false information as valid dispatches.

But that does not mean the CDC is in the clear when the Supreme Court considers the case in March. Justice Samuel Alito already signaled some of his apprehension when he dissented from other justices on lifting the ban before they hear arguments.

At this time in the history of our country, what the Court has done, I fear, will be seen by some as giving the Government a green light to use heavy-handed tactics to skew the presentation of views on the medium that increasingly dominates the dissemination of news, Alito wrote.

Even if the court rejects broader controls on federal communications with social media sites, the case could have extensive implications for effective messaging from federal health officials, legal experts say.

It will have a chilling effect on the government especially for the CDC, said Dorit Reiss, a professor at UC Law San Francisco. Because the line is fuzzy and because they dont want to be accused of coercion, theyre not going to be sure when they can talk to social media.

Correction: A previous version of this article misstated Marcus Plescias title.

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Oklahoma leads country in long Covid – 2 News Oklahoma KJRH Tulsa

Posted: at 6:20 am

TULSA, Okla. Oklahoma leads the country in long Covid, having the highest rate of adults suffering from it.

That's according to data from the latest U.S. Census Bureau Household Pulse Survey.

Dr. Jason Lepak from Ascension Medical Group St. John defined it as, Long Covid is, [a] long time after you've had the illness and you've recovered from the acute things and immediate things, and you're developing many long-term complications and consequences from Covid.

Researchers have gradually learned more about it. Some things, however, they don't know yet. Even still, long Covid is hard to diagnose.

Lepak told 2 News Oklahoma, "It can be chronic lung conditions, weakness, fatigue, vascular disease many different problems, even a longer brain fog. So, it's a whole constellation of different symptoms that is different by individual, but clearly is associated with having the Covid illness previously."

"It can manifest differently in different people, and some people never get it, and they fully recover," Lepak also said. "But we've clearly seen this group of individuals who had Covid and then they've had symptoms of a variety of other problems that have existed well beyond when they should have normally recovered."

Most people who come down with Covid-19 symptoms are back on their feet within a week or two. However, the Household Pulse Survey in November found nearly a quarter (24.4%) of American adults who got Covid-19 reported symptoms lasting three months or longer.

That's about one third (34.1%) in Oklahoma, the highest rate of any state.

The survey demonstrates long Covid having a real-world impact.

A guide from HelpAdvisor about the survey cites one 2022 study showing long Covid possibly keeping up to 3.7 million people out of work. It references another 2022 study that found long Covid cost the U.S. economy nearly four trillion dollars, 17% of the 2019 U.S. gross domestic product.

The survey also found long Covid is also impacting the day-to-day life of these people, saying 31.1% percent of U.S. adults who reported having it said their symptoms lowered "their ability to carry out daily activities."

At 29.5%, the Sooner State fell slightly below the national average, putting it 35th place.

If you or anybody you know suffers from long Covid or symptoms of it, Lepak said, Dont just suffer at home. Go ahead and seek attention first by your primary care physician, and if they can't take care of you long term for that, they may refer you out either to a sub-specialist or to a couple of physicians in the community who deal specifically with patients who suffer with long Covid.

Stay in touch with us anytime, anywhere --

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MCFR firefighter dies after battle with COVID-19 – WCJB

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MCFR firefighter dies after battle with COVID-19  WCJB

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Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers – Nature.com

Posted: at 6:20 am

Dataset and study design

This section contains an overview of how the dataset was collected, its characteristics and its underlying study design. More in-depth descriptions are provided in two accompanying papers: Budd and co-workers23 report a detailed description of the full dataset, whereas Pigoli et al.30 present the rationale for and full details of the statistical design of our study.

Our main sources of recruitment were the REACT study and the NHS T+T system. REACT is a prevalence survey of SARS-CoV-2 that is based on repeated cross-sectional samples from a representative subpopulation defined via (stratified) random sampling from Englands NHS patient register31. The NHS T+T service was a key part of the UK governments COVID-19 recovery strategy for England. It ensured that anyone developing COVID-19 symptoms could be swab tested, followed by the tracing of recent close contacts of any individuals testing positive for SARS-CoV-2 (ref. 25).

Enrolment for both the REACT and NHS T+T recruitment channels was performed on an opt-in basis. Individuals participating in the REACT study were presented with the option to volunteer for this study. For the NHS T+T recruitment channel, individuals receiving a PCR test from the NHS T+T pillar 2 scheme were invited to take part in research (pillar 1 tests refer to all swab tests performed in Public Health England laboratories and NHS hospitals for those with a clinical need, and health and care workers, whereas pillar 2 comprises swab testing for the wider population25). The guidance provided to potential participants was that they should be at least 18 years old, had taken a recent swab test (initially no more than 48h, changing to 72h on 14 May 2021), agree to our data privacy statement and have their PCR barcode identifier available, which was then internally validated.

Participants were directed to the Speak up and help beat coronavirus web page24. Here, after agreeing to the privacy statement and completing the survey questions, participants were asked to record four audio clips. The first involved the participant reading out the sentence: I love nothing more than an afternoon cream tea, which was designed to contain a range of different vowel and nasal sounds. This was followed by three successive sharp exhalations, taking the form of a ha sound. The final two recordings involved the participant performing volitional/forced coughs, once, and then three times in succession. Recordings were saved in .wav format. Smart phones, tablets, laptops and desktops were all permitted. The audio recording protocol was homogenized across platforms to reduce the risk of bias due to device types.

Existing metadata such as age, gender, ethnicity and location were transferred from linked T+T/REACT records. Participants were not asked to repeat this information to avoid survey fatigue. An additional set of attributeshypothesized to pose the most utility for evaluating the possibility for COVID-19 detection from audiowas collected in the digital survey. This was in line with General Data Protection Regulation requirements that only the personal data necessary to the task should be collected and processed. This set included the symptoms currently on display (the full set of which are detailed in Fig. 1e,f), and long-term respiratory conditions such as asthma. The participants first language was also collected to control for different dialects/accents, and complement location and ethnicity. Finally, the test centre at which the PCR was conducted was recorded. This enabled the removal of submissions when cases were linked to faulty test centre results. A full set of the dataset attributes can be found in Budd and colleagues23.

The final dataset is downstream of a quality control filter (see Fig. 1g), in which a total of 5,157 records were removed, each with one or more of the following characteristics: (1) missing response data (missing a PCR test); (2) missing predictor data (any missing audio files or missing demographic/symptoms metadata); (3) audio submission delays exceeding ten days post test result; (4) self-inconsistent symptoms data; (5) a PCR testing laboratory under investigation for unreliable results; (6) a participant age of under 18; and (7) sensitive personal information detected in the audio signal (see Fig. 3d of ref. 23). Pigoli et al.30 present these implemented filters in full, and the rationale behind each one. The final collected dataset, after data filtration, comprised 23,514 COVID+ and 44,328 COVID individuals recruited between March 2021 and March 2022. Please note that the sample size here differs to that in our accompanying papers, in which Budd et al.23 reported numbers before the data quality filter was applied, whereas our statistical study design considerations, detailed in a work by Pigoli and colleagues30, focused on data from the restricted date range spanning March to November 2021. We note the step-like profile of the COVID count is due to the six REACT rounds, where a higher proportion of COVID participants were recruited than in the T+T channel. As detailed in the geo-plots in Fig. 1a,b, the dataset achieves a good coverage across England, with some areas yielding more recruited individuals than others. We are pleased to see no major correlation between geographical location and COVID-19 status, (Fig. 1c), with Cornwall displaying the highest level of COVID-19 imbalance, with a 0.8% difference in percentage proportion of COVID+ and COVID cases.

In our pre-specified analysis plan, we defined three training sets and five test sets to define a range of analyses in which we investigate, characterize and control for the effects of enrolment bias in our data:

Randomized train and test sets. A participant-disjoint train and test set was randomly created from the whole dataset, similar to methods in previous works.

Standard train and test set. Designed to be a challenging, out-of-distribution evaluation procedure. Carefully selected attributes such as geographical location, ethnicity and first language are held out for the test set. The standard test set was also engineered to over represent sparse combinations of categories such as older COVID+ participants30. The samples included in this split exclusively consist of recordings made prior to 29 November 2021.

Matched train and test sets. The numbers of COVID and COVID+ participants are balanced within each of several key strata. Each stratum is defined by a unique combination of measured confounders, including binned age, gender and a number of binary symptoms (for example, cough, sore throat, shortness of breath; see Methods for a full description). The samples included in this split exclusively consist of recordings made prior to 29 November 2021.

Longitudinal test set. To examine how classifiers generalized out-of-sample over time, the longitudinal test set was constructed only from participants joining the study after 29 November 2021.

Matched longitudinal test set. Within the longitudinal test set, the numbers of COVID and COVID+ participants are balanced within each of several key strata, similarly as in the matched test set above.

The supports for each of these splits are detailed in Fig. 1h.

Three separate models were implemented for the task of COVID-19 detection from audio, each representing an independent machine learning pipeline. These three models collectively span the machine learning research space thoroughlyranging from the established baseline to the current state of the art in audio classification technologiesand are visually represented in Extended Data Fig. 7. We also fitted an RF classifier to predict COVID-19 status from self-reported symptoms and demographic data. The outcome used to train and test each of the prediction models was a participants SARS-CoV-2 PCR test result. Each models inputs and predictors, and the details on how they are handled, can be found below. Wherever applicable, we have reported our studys findings in accordance with TRIPOD statement guidelines32. The following measures were used to assess model performance: ROCAUC, area under the precisionrecall curve (PRAUC), and UAR (also known as balanced accuracy). Confidence intervals for ROCAUC, PRAUC and UAR are based on the normal approximation method33, unless otherwise stated to be calculated by the DeLong method34.

We defaulted to the widely used openSMILESVM approach35 for our baseline model. Here, 6,373 handcrafted features (the ComParE 2016 set)including the zero-crossing rate and shimmer, which have been shown to represent human paralinguistics wellare extracted from the raw audio form. These features are then concatenated to form a 6,373-dimensional vector, fopenSMILE(w)v, where the raw waveform, ({{{bf{w}}}}in {{mathbb{R}}}^{n}) (n=clip duration in secondssample rate) is transformed to ({{{bf{v}}}}in {{mathbb{R}}}^{6,373}); v is then normalized prior to training and inference. A linear SVM is fitted to this space and tasked with binary classification. We select the optimal SVM configuration on the basis of the validation set before then retraining on the combined trainvalidation set.

Bayesian neural networks provide estimates of uncertainty, alongside strong supervised classification performance, which is desirable for real-world use cases, especially those involving clinical use. Bayesian neural networks are naturally suited to Bayesian decision theory, which benefits decision-making applications with different costs on error types (for example, assigning unequal weighting to errors in different COVID-19 outcome classifications)36,37. We thus supply a ResNet-50 (ref. 38) BNN model. The base ResNet-50 model showed initial strong promise for ABCS5, further motivating its inclusion in this comparison. We achieve estimates of uncertainty through Monte-Carlo Dropout to achieve approximate Bayesian inference over the posterior, as in ref. 39. We opt to use the pre-trained model for a warm start to the weight approximations, and allow full retraining of layers.

The features used to create an intermediate representation, as input to the convolutional layers, are Mel filterbank features with default configuration from the VGGish GitHub (ref. 40): ({{{{bf{X}}}}}_{i}in {{mathbb{R}}}^{96times 64}), 64 log-mel spectrogram coefficients using 96 feature frames of 10ms duration, taken from a resampled signal at 16kHz. Each input signal was divided into these two-dimensional windows, such that a 2,880ms clip would produce three training examples with the label assigned to each clip (COVID+ or COVID). Incomplete frames at edges were discarded. As with the openSMILESVM, silence was not removed. For evaluation, the mean prediction over feature windows was taken per audio recording, to produce a single decision per participant. To make use of the available uncertainty metrics, Supplementary Note 3 details an uncertainty analysis over all audio modalities for a range of traintest partitions.

In recent years, transformers41 have started to perform well in high-dimensional settings such as audio42,43. This is particularly the case when models are first trained in a self-supervised manner on unlabelled audio data. We adopt the SSAST44, which is on a par with the current state of the art for audio event classification. Raw audio is first resampled to 16kHz and normalized before being transformed into Mel filter banks. Strided convolutional neural layers are used to project the Mel filter bank to a series of patch level representations. During self-supervised pretraining, random patches are masked before all of the patches are passed to a transformer encoder. The model is trained to jointly reconstruct the masked audio and to classify the order of which the masked audio occurs. The transformer is made up of 12 multihead attention blocks. The model is trained end to end, with gradients being passed all of the way back to the convolutional feature extractors. The model is pre-trained on a combined set of AudioSet-2M (ref. 45) and Librispeech46, representing over two million audio clips for a total of ten epochs. The model is then fine-tuned in a supervised manner on the task of COVID-19 detection from audio. Silent sections of audio recordings are removed before then being resampled to 16kHz and normalized. Clips are cut/zero-padded to a fixed length of 5.12s, which corresponds to approximately the mean length of the audio clip. For cases in which the signal length exceeds 5.12s (after silence is removed), the first 5.12s are taken. At the training time, the signal is augmented through applying SpecAugment47 along with the addition of Gaussian noise. The output representations are mean pooled before being fed through a linear projection head. No layers are frozen and again the model is trained end-to-end. The model is fine-tuned for a total of 20 epochs. The model is evaluated on the validation set at the end of each epoch and its weights are saved. At the end of training the best performing model, over all epochs, is chosen.

To predict SARS-CoV-2 infection status from self-reported symptoms and demographic data, we applied an RF classifier with default settings (having self-reported symptoms and demographic data as inputs). In our dataset, predictor variables for the symptoms RF classifier on our dataset comprised: cough; sore throat; asthma; shortness of breath; runny/blocked nose; a new continuous cough; Chronic obstructive pulmonary disease (COPD) or emphysema; another respiratory condition; age; gender; smoker status; and ethnicity. In Han and colleagues dataset18, predictor variables for the symptoms RF classifier comprised: tightness of chest; dry cough; wet cough; runny/blocked nose; chills; smell/taste loss; muscle ache; headache; sore throat; short breath; dizziness; fever; runny/blocked nose; age; gender; smoker status; language; and location. Prior to training, categorical attributes were one-hot encoded. No hyperparameter tuning was performed, and models were trained on the combined Standard train and validation sets. For the hybrid symptoms+audio RF classifier, the outputted predicted COVID+ probability from an audio-trained SSAST is appended as an additional input variable to the self-reported symptoms and demographic variables listed above.

The matched test set was constructed by exactly balancing the numbers of individuals with COVID+ and COVID in each stratum where, to be in the same stratum, individuals must be matched on all of (recruitment channel)(10-year-wide age bins)(gender)(all of six binary symptoms covariates). The six binary symptoms matched on in the matched test set were: cough; sore throat; asthma; shortness of breath; runny/blocked nose; and at least one symptom.

Our matching algorithm proceeds as follows. First, each participant is mapped to exactly one stratum. Second, the following matching procedure is applied separately in each stratum: in stratum s (of a total of S strata) let ns,+ and ns, denote the number of individuals with COVID+ and COVID, respectively, and let ({{{{mathscr{A}}}}}_{s,+}) and ({{{{mathscr{A}}}}}_{s,-}) be the corresponding sets of individuals. Use ({{{{mathscr{M}}}}}_{s,+}) and ({{{{mathscr{M}}}}}_{s,-}) to denote random samples without replacement of size (min {{n}_{s,+},{n}_{s,-}}) from ({{{{mathscr{A}}}}}_{s,+}) and ({{{{mathscr{A}}}}}_{s,-}) respectively. Finally we combine matched individuals across all strata into the matched dataset ({{{mathscr{M}}}}) defined as:

$${{{mathscr{M}}}}:= {cup }_{s = 1}^{S}({{{{mathscr{M}}}}}_{s,+}cup {{{{mathscr{M}}}}}_{s,-}).$$

The resulting matched test set comprised 907 participants who were COVID positive and 907 who were COVID negative. The matched training set was constructed similarly to the matched test set, though with slightly different strata, so as to increase available sample size. For the matched training set, individuals were matched on all of: (10-year-wide age bins)(gender)(all of seven binary covariates). The seven binary covariates used for the matched training set were: cough; sore throat; asthma; shortness of breath; runny/blocked nose; COPD or emphysema; and smoker status. The resulting matched training set comprised 2,599 participants who were COVID positive and 2,599 who were COVID negative.

We consider the action of applying a particular testing protocol to an individual randomly selected from a population. The four possible outcomes ({O}_{hat{y},y}) are

$${O}_{hat{y},y}:= [,{{mbox{Predict COVID{{mbox{-}19}} status as}}},,hat{y}],{{{rm{AND}}}},[,{{mbox{True COVID{{mbox{-}19}} status is}}},,y]$$

(2)

for predicted COVID-19 status (hat{y}in {0,1}) and true COVID-19 status y{0,1}. We denote the probability of outcome ({O}_{hat{y},y}) by

$${p}_{hat{y},y}:= {mathbb{P}}({O}_{hat{y},y})$$

(3)

and use ({u}_{hat{y},y}) to denote the combined utility of the consequences of outcome ({O}_{hat{y},y}). For a particular population prevalence proportion, , the ({p}_{hat{y},y}) are subject to the constraints

$${p}_{0,1}+{p}_{1,1}=uppi$$

(4)

$${p}_{0,0}+{p}_{1,0}=1-uppi ,$$

(5)

leading to the following relationships, valid for (0,1), involving the sensitivity and specificity of the testing protocol:

$${{{rm{sensitivity}}}}equiv frac{{p}_{1,1}}{{p}_{1,1}+{p}_{0,1}}=frac{{p}_{1,1}}{uppi }$$

(6)

$${{{rm{specificity}}}}equiv frac{{p}_{0,0}}{{p}_{0,0}+{p}_{1,0}}=frac{{p}_{0,0}}{1-uppi }.$$

(7)

The expected utility is:

$${{{rm{EU}}}}=mathop{sum}limits_{hat{y}in {0,1}}mathop{sum}limits_{yin {0,1}}{u}_{hat{y},y}{p}_{hat{y},y}$$

(8)

$$={u}_{1,1}{p}_{1,1}+{u}_{0,1}(uppi -{p}_{1,1})+{u}_{0,0}{p}_{0,0}+{u}_{1,0}(1-uppi -{p}_{0,0})$$

(9)

$$begin{array}{l}=uppi [({u}_{1,1}-{u}_{0,1})times {{{rm{sensitivity}}}}+{u}_{0,1}]\+(1-uppi )[({u}_{0,0}-{u}_{1,0})times {{{rm{specificity}}}}+{u}_{1,0}],end{array}$$

(10)

where equations (4) and (5) are substituted into equation (8) to obtain equation (9), and equations (6) and (7) are substituted into equation (9) to obtain equation (10).

To provide researchers easy access to running the code, we have created a demonstration notebook where the participant is invited to record their own sentence, cough, three cough or exhalation sounds and evaluate our COVID-19 detection machine learning models on it. The model outputs a COVID-19 prediction, along with some explainable AI analysis, for example, enabling the user to listen back to the parts of the signal which the model allocated the most attention to. In the demonstration, we detail that this is not a clinical diagnostic test for COVID-19, but that it is instead for research purposes and does not provide any medical recommendation, nor should any action be taken following its use. The demonstration file is detailed on the main repository page and can be accessed at https://colab.research.google.com/drive/1Hdy2H6lrfEocUBfz3LoC5EDJrJr2GXpu?usp=sharing.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers - Nature.com

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