Jeremy Faust is editor-in-chief of , an emergency medicine physician at Brigham and Women's Hospital in Boston, and a public health researcher. He is author of the Substack column Inside Medicine. Follow
California has a new COVID-19 isolation guideline that differs from the CDC's. Under its new policy, California residents with confirmed COVID-19 can end their isolation once they have not had a fever (without fever-reducing medication) for 24 hours and other symptoms are improving. In addition, asymptomatic patients do not need to isolate at all. Masking for 10 days is deemed sufficient.
Many of you have been asking me about this. Including The Boston Globe. First, I'll share my quotes from an article on this in the Globe earlier this week. Then we'll go deeper.
What Didn't Make It Into the Globe (and the Headline Nobody Is Picking Up On...)
I had more to say to the Globe's health journalist Adam Piore, but not everything can fit into the paper. So, here are some further thoughts I have that we touched on during our conversation earlier this week:
More on harm reduction. People who are truly asymptomatic are probably less contagious, but they still may be contagious at times. People who no longer have a fever are less contagious than those with fever; but they still may be contagious. Yes, something is better than nothing; I am just not sure where they got this particular "something."
To be fair, the California guidance is all based on true things. The question is whether this policy effectively decreases spread or not. It might -- and if the scientists have modeling for this, I'd love to see the results. But I'm worried that any modeling they performed may have badly misunderstood the distinction between asymptomatic and pre-symptomatic cases, and the unique implications that these situations carry.
Why you tested matters. It's one thing if you get a positive test after a couple days of symptoms. In that context, California's guidance is based on data that show that decreasing viral loads often (but not always) correlate to reductions in symptoms. But if you tested positive because your roommate has COVID-19 and you're worried you might have caught it from them, this guidance misses the mark and potentially lets you become a superspreader. For example, if you test positive a couple days after an exposure but do not have symptoms, you don't know when your viral load will start going exponential (the time when you're at highest risk of spreading the virus) and whether symptoms will appear just before, during, after that phase, or never.
Context matters. Some degree of spread of COVID-19 on a college campus is a lot more tolerable than some degree of spread in healthcare facilities like nursing homes or acute rehab facilities where your dad goes after that hip replacement. Which leads to...
This next one should have been a headline. (In fairness, I hadn't fully noticed this myself when I spoke to the Globe.) The California guidance actually implies, but does not explicitly state, that many or most healthcare workers should not go to work for 10 days after a positive COVID-19 test. It says, "Avoid contact with those who are at higher risk for severe COVID-19 for 10 days." To me, that says that healthcare workers should not see many of their patients during that time. I wholeheartedly agree.
If there is any thing we 100% must be doing, it is preventing the spread of this virus to the highest-risk individuals. Healthcare workers and others who work closely with high-risk populations need to get paid sick leave to cover their contagious windows (ideally, as determined by two negative rapid antigen tests, taken a day apart). If California were to enforce this part of its guidance (will they?) I would actually be far more willing to accept the rest of the guidance's gambles. But I doubt they will, nor is it feasible given the lack of financial support to (and therefore by) healthcare institutions at this point in the pandemic.
Concluding Thoughts
Look around. Everywhere you go, people are not doing much to prevent the spread of COVID-19. It's year five of the pandemic and deaths and hospitalizations are a lot lower. I get it. Still, I wish people would mask in some situations. (Like, why not mask in super crowded spaces where nobody is talking anyway?) But it is not happening on a large scale. Nor are most people abiding by the CDC's isolation guidelines at this point.
So, we want to find a way to maximally reduce spread -- especially to key populations -- with minimal disruption. The fever rule may help; but it could backfire if too many afebrile people now go out and spread this thing. The asymptomatic rule may turn out to be not too hazardous (though, again, I worry about the pre-symptomatics); but really, I hope infected asymptomatic people who choose not to isolate will wear N95 masks when they go out. (And for concerned readers: one-way N95 masking drastically reduces your chances of getting COVID-19.)
More than that, though, that California (and Oregon) are going rogue from the CDC's guidelines reflects something larger: Times have changed, and so should the guidelines. Yes, harm reduction is indeed a better strategy than making unrealistic requests; I get that this informed California policymakers' choices when they drew up this new protocol. But could we see the science, please?
This piece originally appeared in Faust's newsletter, Inside Medicine.
The Centers for Disease Control and Prevention (CDC) announced this week that nearly 86 percent of new COVID-19 cases are the result of this latest mutation, known as JN.1. This makes it the most widely-circulating version of the virus not just in the U.S., but circulating in the world.
The virus continues to evolve so rapidly that our immune systems have not been able to keep up, says one expert.
It is basically the newest mutant variation of Omicron. The World Health Organization first reported it in August 2023, but it wasnt multiplying very fast. The weather changed, the Northern Hemisphere is in winter cold, people are inside, and the number of cases is growing rapidly.
In mid-October, the CDC reported that the JN.1 mutation was only about 0.1 percent of all COVID-19 cases around the country. But by their latest update on Jan. 20, the CDC estimates thats now up to approximately 86 percent.
The variants symptoms look like a lot of other respiratory viruses now circulating, but it is evolving so rapidly that our immune systems cant keep up.
Most likely, if youre getting COVID right now, youre getting this particular variant mutation, said San Diego State University School of Public Health Director and Professor of Epidemiology Eyal Oren, speaking with National Public Radio this week.
Image courtesy of NBC News.
COVD-19 vaccination rates havent kept up, making the viral spread of this variant even worse. The rates are concerning:
Demographic COVID-19 vaccination rate
Children 11 percent
Adults 21 percent
Adults 65+ 40 percent
It should be noted that adults 65+ are the highest risk group for the virus.
Not only are the rates for COVD-19 vaccinations low, but so are vaccination rates for influenza and respiratory syncytial virus (RSV). This has caused the CDC to issue an alert to healthcare workers about the combination of rising flu, RSV and COVID cases. This could lead to more severe disease and increased healthcare capacity strain in the coming weeks, predicted the agency.
WASHINGTON (AP) When IRS Commissioner Danny Werfel met privately with senators recently, the chairman of the Senate Finance Committee asked for his assessment of a startling report: A whistleblower estimated that 95% of claims now being made by businesses for a COVID-era tax break were fraudulent.
He looked at his shoes and he basically said, Yeah, recalled the lawmaker who posed that question, Sen. Ron Wyden, D-Ore.
The answer explains why Congress is racing to wind down what is known as the employee retention tax credit. Congress established the program during the coronavirus pandemic as an incentive for businesses to keep workers on the payroll.
Demand for the credit soared as Congress extended the tax break and made it available to more companies. Aggressive marketers dangled the prospect of enormous refunds to business owners if they would just apply. As a result, what was expected to cost the federal government $55 billion has instead ballooned to nearly five times that amount as of July. Meanwhile, new claims are still pouring into the IRS each week, ensuring a growing price tag that lawmakers are anxious to cap.
Lawmakers across the political spectrum who rarely agree on little else from liberal Sen. Elizabeth Warren, D-Mass., to conservative Sen. Ron Johnson, R-Wis. agree it's time to close down the program.
I dont have the exact number, but its like almost universal fraud in the program. It should be ended, Johnson said. I dont see how anybody could support it.
Warren added: The standards were too loose and the oversight was too thin."
The Joint Committee on Taxation estimates that winding down the program more quickly and increasing penalties for those companies promoting improper claims would generate about $79 billion over 10 years.
Lawmakers aim to use the savings to offset the cost of three business tax breaks and a more generous child tax credit for many low-income families. Households benefiting from the changes in the child tax credit would see an average tax cut of $680 in the first year, according to an estimate from the nonpartisan Tax Policy Center.
That tax credit is $2,000 per child, but only $1,600 is refundable, which makes it available to parents who owe little to nothing in federal income taxes. An agreement reached earlier this month by congressional tax-writers would increase the maximum refundable child tax credit to $1,800 for 2023 tax returns, $1,900 for the following year and $2,000 for 2025 tax returns. The Center on Budget and Policy Priorities, a liberal think tank and advocacy group, projected that about 16 million children in low-income families would benefit from the child tax credit expansion.
The package was overwhelmingly approved by a House committee last week, 40-3, showing it has broad, bipartisan support.
But passage through Congress is not assured because many key senators have concerns about aspects of the bill. Wyden said a strong vote in the House could spur the Senate into quicker action. Still, passing major legislation in an election year is generally a heavy lift.
Under current law, taxpayers have until April 15, 2025, to claim the employee retention credit. The bill would bars new claims after Jan. 31 of this year. It also would impose stiff penalties on those who are promoting the employer retention tax credit if they know or have reason to know their advice will lead to an underreporting of tax liabilities.
When Congress created the tax break for employers at the pandemics onset, it proved so popular that lawmakers extended and amended the program three times. The credit, worth up to $26,000 per employee, can be claimed on wages paid through 2021.
To qualify, generally businesses must show that a local or state government order related to the COVID-19 pandemic resulted in their business having to close or partially suspend operations. Or the businesses must show they experienced a significant decline in revenues.
Larry Gray, a certified public accountant from Rolla, Missouri, said he had concerns early on about how the program could be abused.
There was no documentation really to speak" and the IRS just sent out the checks, Gray said. They just started printing the checks and I believe Congress was wanting them to print the checks.
His hunch has proven correct, judging by the filings that he has reviewed. He has even lost clients who didnt want to hear that they did not qualify when others were telling them they did. Generally, he said, the businesses that dont qualify are failing to cite the government order that resulted in their closure or partial suspension. They are also routinely citing reasons for reimbursement that dont meet the programs criteria. For example, one company said it was struggling to find employees and had to raise wages as a justification for qualifying.
If I go through the narratives on the filings that Im looking at, every business in America qualifies, Gray said.
The IRS paused accepting claims for the tax credit in September last year, until 2024 due to rising concerns that an influx of applications are fraudulent. At that point, it had received 3.6 million claims.
Some fraud has been prolific. For instance, a New Jersey tax preparer was arrested in July on charges related to fraudulently seeking over $124 million from the IRS when he filed more than 1,000 tax returns claiming the employment tax credits.
In an update issued Thursday about the program, the IRS said that it has thousands of audit in the pipeline and that as of Dec. 31, it has initiated 352 criminal investigations involving more than $2.9 billion in potentially fraudulent claims. Separately, it has opened nine civil investigations of marketers that potentially misled employers on eligibility to file claims.
Werfel briefed the Senate Finance Committee recently on the measures that have been put into place to address the fraud, including developing a special withdrawal program for those with unprocessed claims and a voluntary disclosure program for those who believed they were improperly paid. Since then, the IRS has seen an immediate 40% decline in average weekly claims, he said.
Lawmakers emphasize that cutting down on the fraudulent claims should also help the IRS more quickly resolve the legitimate claims that businesses have filed and are still awaiting resolution. In early December, the IRS had a backlog of about 1 million claims.
Congress routinely has difficulty finding offsets to pay for new spending or tax cuts. But in this case, the employee retention tax credit appears to have few friends left on Capitol Hill.
Well-intentioned, but boy oh boy, said Sen. Mark Warner, D-Va., in summing up the program.
WASHINGTON -- When IRS Commissioner Danny Werfel met privately with senators recently, the chairman of the Senate Finance Committee asked for his assessment of a startling report: A whistleblower estimated that 95% of claims now being made by businesses for a COVID-era tax break were fraudulent.
He looked at his shoes and he basically said, Yeah, recalled the lawmaker who posed that question, Sen. Ron Wyden, D-Ore.
The answer explains why Congress is racing to wind down what is known as the employee retention tax credit. Congress established the program during the coronavirus pandemic as an incentive for businesses to keep workers on the payroll.
Demand for the credit soared as Congress extended the tax break and made it available to more companies. Aggressive marketers dangled the prospect of enormous refunds to business owners if they would just apply. As a result, what was expected to cost the federal government $55 billion has instead ballooned to nearly five times that amount as of July. Meanwhile, new claims are still pouring into the IRS each week, ensuring a growing price tag that lawmakers are anxious to cap.
Lawmakers across the political spectrum who rarely agree on little else from liberal Sen. Elizabeth Warren, D-Mass., to conservative Sen. Ron Johnson, R-Wis. agree it's time to close down the program.
I dont have the exact number, but its like almost universal fraud in the program. It should be ended, Johnson said. I dont see how anybody could support it.
Warren added: The standards were too loose and the oversight was too thin."
The Joint Committee on Taxation estimates that winding down the program more quickly and increasing penalties for those companies promoting improper claims would generate about $79 billion over 10 years.
Lawmakers aim to use the savings to offset the cost of three business tax breaks and a more generous child tax credit for many low-income families. Households benefiting from the changes in the child tax credit would see an average tax cut of $680 in the first year, according to an estimate from the nonpartisan Tax Policy Center.
That tax credit is $2,000 per child, but only $1,600 is refundable, which makes it available to parents who owe little to nothing in federal income taxes. An agreement reached earlier this month by congressional tax-writers would increase the maximum refundable child tax credit to $1,800 for 2023 tax returns, $1,900 for the following year and $2,000 for 2025 tax returns. The Center on Budget and Policy Priorities, a liberal think tank and advocacy group, projected that about 16 million children in low-income families would benefit from the child tax credit expansion.
The package was overwhelmingly approved by a House committee last week, 40-3, showing it has broad, bipartisan support.
But passage through Congress is not assured because many key senators have concerns about aspects of the bill. Wyden said a strong vote in the House could spur the Senate into quicker action. Still, passing major legislation in an election year is generally a heavy lift.
Under current law, taxpayers have until April 15, 2025, to claim the employee retention credit. The bill would bars new claims after Jan. 31 of this year. It also would impose stiff penalties on those who are promoting the employer retention tax credit if they know or have reason to know their advice will lead to an underreporting of tax liabilities.
When Congress created the tax break for employers at the pandemics onset, it proved so popular that lawmakers extended and amended the program three times. The credit, worth up to $26,000 per employee, can be claimed on wages paid through 2021.
To qualify, generally businesses must show that a local or state government order related to the COVID-19 pandemic resulted in their business having to close or partially suspend operations. Or the businesses must show they experienced a significant decline in revenues.
Larry Gray, a certified public accountant from Rolla, Missouri, said he had concerns early on about how the program could be abused.
There was no documentation really to speak" and the IRS just sent out the checks, Gray said. They just started printing the checks and I believe Congress was wanting them to print the checks.
His hunch has proven correct, judging by the filings that he has reviewed. He has even lost clients who didnt want to hear that they did not qualify when others were telling them they did. Generally, he said, the businesses that dont qualify are failing to cite the government order that resulted in their closure or partial suspension. They are also routinely citing reasons for reimbursement that dont meet the programs criteria. For example, one company said it was struggling to find employees and had to raise wages as a justification for qualifying.
If I go through the narratives on the filings that Im looking at, every business in America qualifies, Gray said.
The IRS paused accepting claims for the tax credit in September last year, until 2024 due to rising concerns that an influx of applications are fraudulent. At that point, it had received 3.6 million claims.
Some fraud has been prolific. For instance, a New Jersey tax preparer was arrested in July on charges related to fraudulently seeking over $124 million from the IRS when he filed more than 1,000 tax returns claiming the employment tax credits.
In an update issued Thursday about the program, the IRS said that it has thousands of audit in the pipeline and that as of Dec. 31, it has initiated 352 criminal investigations involving more than $2.9 billion in potentially fraudulent claims. Separately, it has opened nine civil investigations of marketers that potentially misled employers on eligibility to file claims.
Werfel briefed the Senate Finance Committee recently on the measures that have been put into place to address the fraud, including developing a special withdrawal program for those with unprocessed claims and a voluntary disclosure program for those who believed they were improperly paid. Since then, the IRS has seen an immediate 40% decline in average weekly claims, he said.
Lawmakers emphasize that cutting down on the fraudulent claims should also help the IRS more quickly resolve the legitimate claims that businesses have filed and are still awaiting resolution. In early December, the IRS had a backlog of about 1 million claims.
Congress routinely has difficulty finding offsets to pay for new spending or tax cuts. But in this case, the employee retention tax credit appears to have few friends left on Capitol Hill.
Well-intentioned, but boy oh boy, said Sen. Mark Warner, D-Va., in summing up the program.
The Library of Congress and StoryCorps announced this week that they have created a website for people to record for posterity their experiences with the covid-19 pandemic.
Stories or interviews with others who were touched by the pandemic can be recorded online. They will be preserved in the librarys American Folklife Center and made accessible at archive.StoryCorps.org.
Our goal for the COVID-19 Archive Activation page is to honor those who experienced this tumultuous moment in our nations history, commemorate those who were lost ... and to educate future generations about what life was like during the pandemic, Nicole Saylor, director of the American Folklife Center, said in a statement.
We are particularly interested in doing this work through peoples stories, as storytelling is a crucial medium of communication, she said.
Librarian of Congress Carla Hayden said in the statement: Recording the voices and stories of Americans experiences with the COVID-19 pandemic for our national collections will ... ensure these stories will not be forgotten.
Since the start of the pandemic in early 2020, more than 1 million Americans have lost their lives and 6 million have been hospitalized, according to the Centers for Disease Control and Prevention.
Variants of the disease continue to sicken people, although effective vaccines have reduced serious illness.
In 2021, the library acquired a collection of audio diaries from more than 200 health-care workers compiled by the Nocturnists, a San Francisco-based independent medical storytelling community and podcast.
And it has gathered an array of covid-related artifacts, including art, data, photographs and posters to illustrate the impact of the disease.
Our goal is that, centuries from now, people looking through these online archives will know that, amidst the darkness of the global pandemic, America discovered its strength in unity, resilience, and innovation, library spokeswoman Maria Pea said in an email.
Unvaccinated pregnant people who contracted COVID-19 were more likely to have babies who suffered from respiratory distress, a new study published this week found.
A team of researchers led by the University of California, Los Angeles, looked at 221 pregnant people for the study, including 151 who were unvaccinated before they were infected with COVID, which was confirmed with a laboratory test.
All of the 151 unvaccinated pregnant people met the National Institutes of Health criteria for severe or critical COVID-19 whereas only 4% of the 70 vaccinated pregnant people met the criteria.
MORE: Pregnant people have higher risk of breakthrough COVID-19, data shows
Researchers were able to examine 199 babies, all of whom were born between April 2020 and August 2022, and none of whom tested positive for the virus. The remaining 28 fetuses either resulted in a miscarriage, abortion or fetal demise, or could not be followed up with.
The team found that being exposed to COVID-19 in utero "may activate an inflammatory cascade" in the airways of newborns, resulting in respiratory distress. One of the main pathways appear to be associated with the function of cilia, the tiny, hair-like structures found on the surface of cells that typically help push germs, mucus and other particles towards the mouth so they can be coughed or sneezed out.
Results, published in the journal Nature Communications, found the odds of respiratory distress were up to three times greater in babies born in those who were unvaccinated versus those who were vaccinated.
"We found unusually high rates of respiratory distress shortly after birth in the full-term babies born to mothers who had COVID-19 during pregnancy," Dr. Karin Nielsen, a professor of pediatrics in the division of pediatric infectious diseases at UCLA's David Geffen School of Medicine, said in a statement. "The mothers had not been vaccinated prior to acquiring COVID, indicating that vaccination protects against this complication."
Further research is needed to determine if COVID-19 still impacts respiratory distress when accounting for other factors that lead to respiratory distress syndrome
Respiratory distress in infants is defined as difficulty breathing or working harder to breathe within the first 24 hours. Signs can include wheezing, sweating, changes in breathing rate or color changes around the lips or mouth, according to Johns Hopkins Medicine.
Research has shown that pregnant people with COVID-19 are at increased risk of becoming seriously ill leading to hospitalization, intensive care, the use of a ventilator or even death. COVID-19 during pregnancy also raises the risk of a premature or stillborn baby.
MORE: CDC strengthens recommendation that pregnant women get vaccinated
"Our results demonstrate that maternal vaccination against COVID-19 not only protects against maternal disease severity, but also reduces the likelihood of neonatal [respiratory distress]," the authors wrote.
The study had several limitations, such as a small and homogenous sample size and a wide estimate range, which impacted generalizability. More research is needed to validate these findings.
The Centers for Disease Control and Prevention (CDC) currently recommends that all pregnant people get vaccinated against COVID-19 and that studies have shown there are no safety concerns for babies born to those who have been vaccinated.
Babies born to unvaccinated people who had COVID-19 may be at greater risk of respiratory distress: Study originally appeared on abcnews.go.com
FILE - The exterior of the Internal Revenue Service (IRS) building is seen in Washington, on March 22, 2013. Congress is racing to wind down a tax break meant to encourage businesses to keep workers on the payroll during the COVID-19 pandemic. What was expected to cost the government $55 billion has instead cost it nearly five times that amount as of July. Meanwhile, new claims pour into the IRS each week. (AP Photo/Susan Walsh, File)
WASHINGTON When IRS Commissioner Danny Werfel met privately with senators recently, the chairman of the Senate Finance Committee asked for his assessment of a startling report: A whistleblower estimated that 95% of claims now being made by businesses for a COVID-era tax break werefraudulent.
He looked at his shoes and he basically said, Yeah, recalled the lawmaker who posed that question, Sen. Ron Wyden, D-Ore.
The answer explains why Congress is racing to wind down what is known as theemployee retention tax credit. Congress established the program during the coronavirus pandemic as an incentive for businesses to keep workers on the payroll.
Demand for the credit soared as Congress extended the tax break and made it available to more companies.Aggressive marketersdangled the prospect of enormous refunds to business owners if they would just apply. As a result, what was expected to cost the federal government $55 billion has instead ballooned to nearly five times that amount as of July. Meanwhile, new claims are still pouring into the IRS each week, ensuring a growing price tag that lawmakers are anxious to cap.
Lawmakers across the political spectrum who rarely agree on little else from liberal Sen. Elizabeth Warren, D-Mass., to conservative Sen. Ron Johnson, R-Wis. agree its time to close down the program.
I dont have the exact number, but its like almost universal fraud in the program. It should be ended, Johnson said. I dont see how anybody could support it.
Warren added: The standards were too loose and the oversight was too thin.
The Joint Committee on Taxation estimates that winding down the program more quickly and increasing penalties for those companies promoting improper claims would generate about $79 billion over 10 years.
Lawmakers aim to use the savings to offset the cost of three business tax breaks and a more generous child tax credit for many low-income families. Households benefiting from the changes in the child tax credit would see an average tax cut of $680 in the first year, according to an estimate from the nonpartisan Tax Policy Center.
That tax credit is $2,000 per child, but only $1,600 is refundable, which makes it available to parents who owe little to nothing in federal income taxes. An agreement reached earlier this month by congressional tax-writers would increase the maximum refundable child tax credit to $1,800 for 2023 tax returns, $1,900 for the following year and $2,000 for 2025 tax returns. The Center on Budget and Policy Priorities, a liberal think tank and advocacy group, projected that about 16 million children in low-income families would benefit from the child tax credit expansion.
The packagewas overwhelmingly approved by a House committee last week, 40-3, showing it has broad, bipartisan support.
But passage through Congress is not assured because many key senators have concerns about aspects of the bill. Wyden said a strong vote in the House could spur the Senate into quicker action. Still, passing major legislation in an election year is generally a heavy lift.
Under current law, taxpayers have until April 15, 2025, to claim the employee retention credit. The bill would bars new claims after Jan. 31 of this year. It also would impose stiff penalties on those who are promoting the employer retention tax credit if they know or have reason to know their advice will lead to an underreporting of tax liabilities.
When Congress created the tax break for employers at the pandemics onset, it proved so popular that lawmakers extended and amended the program three times. The credit, worth up to $26,000 per employee, can be claimed on wages paid through 2021.
To qualify, generally businesses must show that a local or state government order related to the COVID-19 pandemic resulted in their business having to close or partially suspend operations. Or the businesses must show they experienced a significant decline in revenues.
Larry Gray, a certified public accountant from Rolla, Missouri, said he had concerns early on about how the program could be abused.
There was no documentation really to speak and the IRS just sent out the checks, Gray said. They just started printing the checks and I believe Congress was wanting them to print the checks.
His hunch has proven correct, judging by the filings that he has reviewed. He has even lost clients who didnt want to hear that they did not qualify when others were telling them they did. Generally, he said, the businesses that dont qualify are failing to cite the government order that resulted in their closure or partial suspension. They are also routinely citing reasons for reimbursement that dont meet the programs criteria. For example, one company said it was struggling to find employees and had to raise wages as a justification for qualifying.
If I go through the narratives on the filings that Im looking at, every business in America qualifies, Gray said.
The IRSpaused accepting claimsfor the tax credit in September last year, until 2024 due to rising concerns that an influx of applications are fraudulent. At that point, it had received 3.6 million claims.
Some fraud has been prolific. For instance, a New Jersey tax preparerwas arrested in July on chargesrelated to fraudulently seeking over $124 million from the IRS when he filed more than 1,000 tax returns claiming the employment tax credits.
In an update issued Thursday about the program, the IRS said that it has thousands of audit in the pipeline and that as of Dec. 31, it has initiated 352 criminal investigations involving more than $2.9 billion in potentially fraudulent claims. Separately, it has opened nine civil investigations of marketers that potentially misled employers on eligibility to file claims.
Werfelbriefed the Senate Finance Committeerecently on the measures that have been put into place to address the fraud, including developing a special withdrawal program for those with unprocessed claims and a voluntary disclosure program for those who believed they were improperly paid. Since then, the IRS has seen an immediate 40% decline in average weekly claims, he said.
Lawmakers emphasize that cutting down on the fraudulent claims should also help the IRS more quickly resolve the legitimate claims that businesses have filed and are still awaiting resolution. In early December, the IRS had a backlog of about 1 million claims.
Congress routinely has difficulty finding offsets to pay for new spending or tax cuts. But in this case, the employee retention tax credit appears to have few friends left on Capitol Hill.
Well-intentioned, but boy oh boy, said Sen. Mark Warner, D-Va., in summing up the program.
Network based word-embedding (mpDisNet)
The OMIM database was used to collect 394 disease types to be used in mpDisNet models. Results from the reproduced model show that, majority of the high-scoring disorders are cancer-related phrases, as can be observed in the reproduction score distribution (Fig.1). The distribution indicates that, MpDisNet scores are highly biased towards the cancer related terms. (Supplementary doc: Similarity mpdisnet.xlsx), We discovered 10,563 disease-disease associations with a score higher than 0.9, which is computed using vector cosine similarities. 6838 out of 10,593 disease similarities contain at least one cancer related term, which constitutes nearly %65 of the scores higher than 0.9.
Score distribution of the mpDisNet (reproduction model) that represents the effect of the cancer-term dominance in the disease interaction scores. (a) Reproduced model score distribution of all disease scores from the mpDisNet trial. (b) Score distributions of cancer-terms in the range between 0.9 and 0.95. (c) Score distributions of the remaining (non-cancer) disease interactions.
Scores of cancer-related phrases, as shown in Fig.1a, are likewise the main reason for the higher score accumulation between 0.95 and 1. This has a significant impact on the overall distribution of scores for diseases other than cancer. Because of the large amount of cancer-related research and the disease's complications, cancer is strongly linked to all other diseases, resulting in higher comorbidity ratings. Removal of the cancer-related elements from the disease similarity scores reduces the score accumulation on the high score range, as seen in Fig.1c.
When cancer terms and their linked miRNAs are removed from the training data, significant changes in the score distribution is observed. This change in the distribution also indicates that, the number of highly connected elements such as cancer terms also leads to a reduction in the occurrence of other disease representations in the model. Since multiple pathway dysfunctions emerge in cancers, a larger number of related miRNAs were reported in literature. Indeed, as it shown in Table 2, number of discovered miRNAs for cancer terms are large in comparison to median number of miRNAs (Fig.2) per disease used in this study. Cancer related miRNAs constitute the outlier points in Fig.3a and lead to high number of occurrences of cancers in training data as shown in Fig.3bd. The imbalance in number of miRNAs in cancer and non-cancer diseases lead to dominant occurrence of cancer terms over other diseases, which increases the possibility of random selection of cancers in different sub-networks in the corpus and causes over-training of their vectors.
Comparison of the medians of the number of miRNAs are related with cancer-type diseases and the rest of the OMIM disease dataset.
Effects of variations of miRNA counts in diseases and the disease frequencies in the training data. (a) Boxplot of the number of the miRNAs of each diseases indicate a narrow IQR range (box) and high number of outliers (circles). (b) Occurrence frequencies of each disease in training data in non-modified version. c Scatter plot of mean score of each disease and its frequency in the training data. (d) Positive correlation between the disease frequencies and number of miRNAs.
Further, unbalanced occurrence of words (diseases) causes instabilities such as vector update rate disparities between high and low frequency words (Fig.3). The degree of learning for each condition will eventually be affected by differences in the number of updates of the individual diseasevectors17. As a result, there will be differences between reliability of disease interaction scores for relatively rare disorders and high frequency disorders. In NLP models, this property can be used to classify the words by their semantic information importance. However, in disease representations, there is no difference between the diseases in terms of information values i.e., diseases cannot be classified as more important or less important in our context as in other NLP problems. This is the main difference between the real words and word-like representations. By removing highly connected diseases, we would like to increase the score reliability of the rest of the diseases and consequently increase the prediction performance.
Prior to applying the approach to the COVID-19 disease to find possible comorbidities, we aimed to increase the disease interaction identification performance. Use of heterogeneous miRNA-gene-disease network approach is mostly conserved in our analysis, which is based on data from miR2Disease and HMDD miRNA-disease interactions9,18. The random walk method based on meta-paths has also been preserved. However, changes have been made to increase the accuracy of the network method. In contrast to the original architecture, we used a TF-TF interaction network rather than the PPI to be able to represent the regulatory mechanisms in a more precise manner. The cosine similarity of the disease vectors, which is one of the distance metrics used for quantifying the word similarities in NLP applications, was utilized to analyze disease similarities (comorbidities) for performance evaluation of the method.
miRNA expression profiles of SARS-CoV-2 infected cells have been collected from Wyler dataset19. 24-h mock-infected samples were used as control samples. Infected Calu3 cell samples have been analyzed for identification of differentially expressed miRNAs (Calu3 4h12h24h). 39 significant and differentially expressed miRNAs have been identified (adj.p-value<0.05) which includes hsa-mir-4485, hsa-mir-483 and has-mir-155.
The score distribution in the reproduced version and in our version with improvements in the disease list and transcription-factor implementation has been shown as a heatmap for all disease scores (Fig.4).
Heatmaps representing the similarity scores in reproduction and TF integrated network. All diseases are placed into x and y axis and they are colored based on their similarity scores as green (1) and blue (0). (a) Heatmap of the reproduction scores. (b) Scores after cancer-associated diseases are removed (sub-frame of part A that matches with diseases in part E). (c) Scores of Transcription-factor integrated model instead of Human PPI with cancer terms. (d) TF model without cancer terms (sub-frame of part B that matches with diseases in part F). (e) Updated training without cancer terms, with Human PPI, and (f) updated training with TF interaction network without cancer terms. Black color represents the zero score that indicates that no association between diseases was found. The region between the black ticks on the x and y axes in (a) and (c) indicate the cancer (right) and non-cancer (left) diseases.
Excluding cancer terms and their related miRNAs from the heatmap data resulted in higher scores on non-cancer disease relationships. Figure4a depicts the reproduction score distribution, with cancer-related phrases gathered in the top-right side of the graph, which alsohas the highest scores. It was transformed into Fig.4b by deleting cancer-related rows and columns from the heatmap, resulting in a clear distinction between the effect of cancer-related terms on the score distribution. Figure4e, on the other hand, was produced by retraining disease pair scores after removing cancer diseases and their corresponding miRNA set from the training dataset of themodel, it can be seen that the overall score profile for non-cancer diseases has improved. Figure4c demonstrates the distribution of disease similarity scores including cancer terms when TF-TF interaction data is utilized instead of Human-PPI. In this case, some disease relationships were lost, and the majority of disease scores were reduced. However, scores of the some of the rare disease interactions were increased that may be of significance. Figure4f demonstrates that when cancer terms are omitted from the TF-TF included trials, the effect on the scores is similar with the upper row, again demonstrating the cancer domination in models where cancer interactions were included. Score distribution differences between the TF-TF regulatory map implementation and PPI can be seen when Fig.4c and f are compared. Although the scores of the TF network models are lower than the PPI network models, the training time of the models has been greatly decreased due to the smaller vocabulary when TF network is used.
Several diseases were found to have no comorbidity with the rest of the diseases (Table 3). All of these diseases have quite a limited number of miRNA connections in the disease-miRNA data in the network. In the Reproduction and Cancerless models, most of them only have one miRNA interaction. When the TF-TF interaction data was used, the non-comorbid disease list was expanded to include some of two miRNA-connected disorders that are not linked to the transcription factor interactions in the network.
ROC (Receiver Operator Characteristic) curves are often used to evaluate the performances of prediction algorithms by presenting true positive rate and false positive rate of predictions as a curve. For this evaluation, information on true positives and true negatives is needed. Compilation of True Positives (comorbidities) from literature is relatively easy despite the scarcity of verified disease-disease interactions in the literature. However, finding the True Negatives is far more challenging as there is no literature data that directly reports non-comorbid pairs of diseases. One way is designating disease pairs with a low RR score or no interaction information as non-comorbid. This technique classifies comorbidities not yet reported in the literature as False Positives (FP) in ROC curve calculations. As a result, True-positive (TP) scores are hampered when each disease has a small number of known comorbidities. To address this negative bias on AUROC, more comorbidity data is needed to increase the TP/FP ratio. We expanded the amount of clinical data in the validation set to be used in mpDisNet., as a result, the AUROC performance was greatly improved over the original implementation.
The performance of original implementation of mpDisNet in terms of AUROC (Area Under ROC) was 0.65, which was higher when compared to the AUROC of the overlap method (0.58), a simpler methodology that finds comorbidities by comparing shared miRNA ratios between two disorders, The key drawback of the ROC analysis in the original implementation is the high number of predicted Disease-Disease interactions, which is around 90.000 [n*(n1)], compared to a small number of known disease interactions which is 81. To be able to expand this list, the disease pairs with RR higher than 1.5 in MediCare dataset and the comorbid disease list of 81 pairs were merged, after all disease names were converted to ICD-9. Generated final Disease-Disease scores (Supplementary file: rev_over_15.xlsx) were converted to pivot table by using pandas python package20. The compiled data visualized as heatmap (Fig.5) with matplotlib v3.4 seaborn python package21. Disease similarity scores were used to calculate TP and FP rates when compared to compiled list of comorbidities and ROC curves were drawn for all cases (Fig.6). The main objective of this improvement is to maximize TPR to better understand the algorithm's true discovery performance. However, since the algorithm's False Discovery Rate cannot be changed, as previously stated, and all disease interactions that have not yet been documented in the literature ought to be labeled as 0, leading to false positives.
Diseases that have at least 1.5 Relative-Risk (RR) score from US Medicare data visualized as heatmap with matplotlib seaborn python package v3.4. Full sized heatmap can be found in Supplementary Fig. 1 (disease_heatmap.pdf) and full list of disease comorbidity scores from MediCare data can be found in material rev_over_15.xlsx).
Receiver-Operator Curve (ROC) curve of all models. (a) ROC score for reproduced model with same setup in the original MpDisNet implementation. (b) ROC curve of cancer removed model scored compared to limited known disease interactions (81 pairs). (c) TF-TF substituted model scores compared to limited disease data. (d) Reproduction of the original model with extended known disease pairs. (e) Cancer removed model with extended disease pairs. (f) Cancer removed and TF integrated model with extended disease pairs.
To determine whether the implementation of the TF-TF regulation mechanism has a beneficial effect on the discovery of comorbidities, a comparison between the PPI network and the transcription factor-implemented network was made.
Figure6a presents the reproduction of the original implementation, and the same AUROC is reproduced as expected. The modifications on the model (removal of cancer terms and using TF-TF instead of PPI) did not improve the results as seen in Fig.6b and c, when they were evaluated using limited clinical data. However, in the second row of Fig.6, use of extended clinical data significantly improves the AUROC when compared to its counterpart on the first row.
We further hypothesized that correlation between scores of disease pairs may be a more accurate measure of similarity or comorbidity between them. A high positive correlation of scores indicates that the pair of diseases have similar scores with other diseases, hence has a common profile of similarities in their mechanisms. This approach also mitigates the impact of low-frequency disorders having low scores due to lack of miRNA connections.
We tested two alternative correlation metrics; Pearson and Spearman correlations are calculated between similarity scores of each disease pair using our mpDisNet results as shown in Fig.7. Although both metrics produced similar results, to reduce the effect of possible methodological bias, both Pearson and Spearman correlation score-based performances were kept in the ROC curves. When correlations are used for evaluation of performances, we find that cancer-term included model scores also have slightly improved AUROC performance. There is more obvious improvement in Cancerless model than other models. We could say that the similarity between diseases is more prominent when we keep PPI and remove cancer terms as seen in Fig.7b. In addition, concordance of the Spearman and Person correlations in Cancerless model could be evidence of improved score reliability when compared to the other models. But in order to keep taking into consideration the non-normal distribution of the similarity scores between disease pairs, the non-parametric Spearman correlation coefficients may be more appropriate to keep. Therefore, only Spearman correlation of vector similarity scores were used to determine possible COVID comorbidities in the following section.
Updated ROC representations of three main approaches (a) Reproduction data with No correction (blue), Pearson correlated scores (gold), Spearman correlation (green), (b) cancer removed, and correlation implemented. (c) Cancer removed and TF integrated network with correlation tunings.
Although our modifications on the algorithm reduced the scores in general, we have observed that low scores of some disease pairs in reproduction model are increased in the modified models. For example, there is an increase in Rheumatoid Arthritis and Depression comorbidity score from 0.79 to 0.90, which is one of the known comorbidities in the literature22. Another elevated score is between epilepsy and chronic hepatitis, clinical evidence suggests that these two disorders are strongly comorbid and should be further examined23. The algorithm cannot provide any direction information between disease comorbidities, therefore it is not possible to assume causality such as one disease being the cause of another disease, since the direction of the comorbidities cannot be implemented into the network structure yet. However, these findings could indicate that, patients with one disease could have a higher genetic and regulatory inclination to another disease which have high similarity score to the first disease24.
We have used our results to investigate comorbidity of COVID-19 with other diseases as a case study. Highly scored diseases that are potentially comorbid with COVID-19 have been retrieved from cancer-removed network training results with Spearman correlation of scores. The threshold has been chosen as 0.9 since it was found as the optimum threshold for the Cancerless model in the ROC curve performance analysis. The algorithm found 156 diseases (Supplementary table: COVID_comorbs.xlsx) with a similarity score of more than 0.9 and correlation of more than 0.95, indicating a strong link to COVID-19 with associated genes and miRNAs. There are also 57 disorders with a score of 0.8 to 0.9, it can be suggested that a moderate link between thesediseases and COVID-19 exists. We have identified high-scored associations with disorders that had clinical evidence of increased risk with COVID-19 on the CDC website, such as Diabetes (0.996), Heart Diseases (0.989), Schizophrenia (0.994), and Hypertension (0.994) (https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/underlying-evidence-table.html) (Supplementary Dat: CDC_Diseases.xlsx). When the Spearman correlation is applied to the result file, the number of probable COVID disease interactions (Scores over 0.95) increases (From 97 to 210). Also, the overall score of CDC diseases increased from 0.92 (stdev0.054) to 0.98 (stdev0.012).
Encouragingly, we have further found that there are strong links between immune response and infection in diseases such as Hepatitis, Infectious Disorders, and several lung-related diseases. High-scores were also found for vessel and artery-related disorders, such as coronary artery disease, aortic aneurysm, and renal-related diseases. Additionally, various neurological and psychological disorders, such as Alzheimers, Parkinsons, Depression, and Schizophrenia, may raise the impact of COVID-19 according to our results. Indeed, recently this link was shown for Parkinson's Disease in the literature25.
While application of disease similarity networks to the NLP models is a promising approach, there are some challenges that should be tackled. The first of them is biases in data, as stated in the first part of the Results and Discussion, over-representation of diseases such as cancer and subtypes can substantially skew the disease representations as shown in Fig.1. The choice of network also has an impact on the outcome. Since the final goal is to trace back the disease similarities and identify the potential genes/metabolic activities that mediate the similarities, it is important to keep only the interactions that are mechanistically meaningful. The original reliance on human PPI may not have offered the mechanistic precision that TF-TF interaction network could. While the benefits of integrating TF-TF were not immediately obvious, exploring specific subtypes of regulatory mechanisms in future models could augment performance further. A critical limitation in the initial approach was the scant validation data, confining the model's evaluative robustness. Diseases, influenced by factors like genetics and environment, require a model that captures this complexity. Word2vec and similar embeddings, while powerful, have the risk of oversimplifying these complexities. A holistic view, potentially achievable by assimilating diverse data sources like clinical records and genomic databases, is desirable. While the introduction of correlation metrics illuminates aspects of disease similarity, it is paramount to distinguish between mere correlation and actual causation. Lastly, presented model could provide a quick and broad perspective on disease comorbidities by offering easy implementation. However, while this quick glimpse is valuable in such cases as pandemics, a deeper dive into the underlying causes and intricacies of these disease connections is essential. As we forge ahead, it becomes evident that continuous refinement and validation are not just beneficial but crucial on these applications.
The commercials make it sound so simple: If its COVID, Paxlovid.
But the slogan, catchy though it may be, belies a harsher reality that some public health and elected officials have long acknowledged and worked to rectify: For many, getting access to the therapeutic should be much easier than it has been.
The issue is not one of scarcity, as the antiviral is widely abundant. Nor is pricing a major barrier, as Paxlovid is cheap or even free for many. Nor even is it an issue of how well it works, as studies have shown it to be highly effective.
The drugs biggest impediment has been, and remains, the simple fact that a number of doctors are still declining to prescribe it.
Some healthcare providers hinge their reluctance on outdated arguments, such as the idea of Paxlovid rebound the chance that people who take the drug have a chance of developing COVID symptoms again, generally about two to eight days after they recover.
As it turns out, anyone who gets COVID-19 has a similar rare chance of rebound.
COVID rebound can occur with or without [Paxlovid] treatment, scientists with the Food and Drug Administration wrote in a study published in December. Viral RNA rebound was not restricted to [Paxlovid] recipients, and rebound rates were generally similar to those in placebo recipients.
When told about one patient who was declined a prescription to Paxlovid because of concern about Paxlovid rebound, UC San Francisco infectious-diseases expert Dr. Peter Chin-Hong groaned.
Oh my God, thats so, like, bogus, Chin-Hong said. Clinicians having this weird idea about rebounds, its just dumb.
Data indicate that most people dont get COVID rebound, Chin-Hong said. And while rebound can occur, the possibility should not dissuade people who might really need it from taking an antiviral.
Even if COVID rebound happens, and symptoms do occur, they tend to be mild and do not require repeating the treatment, according to the California Department of Public Health.
Officials at both the federal and state level have implored healthcare providers to properly prescribe Paxlovid and other antivirals when indicated.
Antivirals are underused, the Centers for Disease Control and Prevention said in a statement Thursday. Dont wait for symptoms to worsen.
In its own advisory, the California Department of Public Health said, Most adults and some children with symptomatic COVID-19 are eligible for treatments ... Providers should have a low threshold for prescribing COVID-19 therapeutics.
Aside from Paxlovid, one alternative oral antiviral treatment is known as molnupiravir. Theres also remdesivir, which is administered intravenously.
The CDC says Paxlovid and remdesivir are the preferred treatments for eligible COVID-19 patients.
Dont delay: Treatment must be started within five to seven days of when you first develop symptoms, the CDC says.
A reference to Paxlovid and other antivirals is even in a musical radio ad from California health authorities that has been broadcast throughout the state: Test it. Treat it. You can beat it, with the ditty later continuing: Medication is key / To slow the virus in your body.
Yet there is wide documentation of the low frequency of prescribing Paxlovid and other antivirals, and that can have significant consequences for higher-risk COVID-19 patients. A report published by the CDC Thursday reviewed 110 COVID-19 patients considered high-risk and found that 80% of them were not offered antiviral treatment.
A big reason given by the patients providers, all of whom were under the Veterans Health Administration, was that their patients COVID symptoms were mild.
But as officials note, thats exactly what antivirals are for.
There is strong scientific evidence that antiviral treatment of persons with mild-to-moderate illness, who are at risk for severe COVID-19, reduces their risk of hospitalization and death, the CDC says.
Risk factors for severe COVID-19 include being age 50 and up; not being current on COVID vaccinations; and a wide array of medical conditions, such as diabetes, asthma, kidney disease, heart disease, having anxiety or depression, and being overweight. Other factors that influence health, such as limited access to healthcare and having a low income, can also heighten someones risk.
Another reason providers may cite to not prescribe COVID antivirals, California officials said, is the chance of serious side effects. But that fear is largely erroneous, as most people have little-to-no side effects, the California Department of Public Health says. Some of the more common side effects after taking Paxlovid are developing a temporary metallic taste in the mouth, which occurs in about 6% of recipients, and diarrhea (3%).
However, some people who do take Paxlovid may need to have other medications adjusted, according to the agency.
The other antiviral pill option, molnupiravir, has very few side effects, but you cannot take it if you are pregnant, the state agency said.
Clinicians may also be reluctant to prescribe Paxlovid for younger adults, not because it causes harm, but because it in some studies doesnt show as much benefit, Chin-Hong said. Younger, healthy people are generally unlikely to die from COVID or become ill enough to require hospitalization even without antiviral treatment.
But some data do suggest that patients who take Paxlovid clear out coronavirus from their bodies faster.
What were finding is that people are turning negative very quickly with Paxlovid, Chin-Hong said.
And one report, published in the journal Emerging Infectious Diseases, suggests widespread use of Paxlovid would not only improve outcomes in treated patients but also ... reduce risks of onward transmission.
So if an initial clinician turns you down for a Paxlovid prescription, and you think you qualify, what other options are there?
One possibility is reaching out to another healthcare provider who might be either more knowledgeable about Paxlovid and other antiviral medications or more open to prescribing them.
Los Angeles County residents can call the countys public health info line, (833) 540-0473, to discuss treatment options with a health provider.
Californians who dont have insurance or have a hard time getting anti-COVID-19 medication can schedule a free telehealth appointment by calling (833) 686-5051 or visiting sesamecare.com/covidca. Medication costs may be subject to a copay, depending on your insurance.
A program funded by the National Institutes of Health, featured at test2treat.org, gives adults who test positive for COVID-19 or flu free access to telehealth care and treatment.
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