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Wuhan disease spread by bats, animals: expert | Article – Asia Times

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The unknown pneumonia-like disease outbreak in Wuhan in Hubei province probably originated from bats and spread through wild animals to humans, said a Hong Kong-based microbiologist and specialist of the severe acute respiratory syndrome (SARS).

Yuen Kwok-Jung, a Hong Kong-based microbiologist. Photo: RTHK

It was likely the Wuhan disease was a new kind of coronavirus similar to SARS, Yuen Kwok-Jung, the Chair of Infectious Disease at the Department of Microbiology of the University of Hong Kong, said Wednesday.

It would not be difficult for mainland authorities to identify the coronavirus as China had accumulated a lot of experience about virus testing since the SARS outbreak in 2003, Yuen said, adding that he would not speculate why the mainland had not released more information about the disease in the past two days.

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There were six kinds of coronaviruses that could infect humans, as well as 24 other kinds that could infect animals including bats, birds, rats and cows, Yuen said.

As most Wuhan patients had connections with the Huanan Seafood Market, there was a high chance the unknown coronavirus was transmitted to wild animals from bats and became mutated before it spread to humans, he said.

Severe acute respiratory syndrome. Credit: The New England Journal of Medicine (www.nejm.org)

Usually a new disease would not be highly infectious between humans so only people who had very close contact with the patients could be infected, he said. If the Wuhan disease was similar to SARS, patients could be cured by doses of ribavirin, protease inhibitor and interferon, he said.

People could help stop the spread of the disease simply by not eating wild animals, while markets should stop selling them, Yuen said. If 10-20 more cases are identified in Wuhan within the coming week, a community outbreak could have happened, he added.

Wearing a surgical mask, instead of a n95 mask, in public places is good enough to keep the Wuhan disease infection away, said David Hui Shu-cheong, chairman, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong.

A bat. Photo: Wikimedia Commons/Anton Croos/Art of Photography

People should wear surgical masks on public transport, in offices and schools as a mask can block 95% of the airborne droplets of secretions from the nose, throat or lungs, he said. People should also wear masks at home if they are sick, he said.

Medical staff can choose to wear n95 masks but not for long hours or they may suffer from headaches due to a lack of fresh air, Hui said.

At 8pm on Sunday, The Wuhan Municipal Health Commission released a statement saying, it had identified 59 people who were infected by an unknown pneumonia disease.

Seven cases were serious. The commission also said it had traced 163 people who were close to the patients and would continue the contact tracing.

However, the commission gave no update about the disease during the past two days, fueling concerns it was covering up some figures.

On Tuesday, Hong Kong’s Center for Health Protection announced that a total of 30 suspected cases related to the “severe respiratory disease associated with a novel infectious agent” had been reported since December 31.

Thirteen people have recovered and left hospitals and none of the cases were confirmed as the Wuhan disease.

Sophia Chan Siu-chee, Secretary for Food and Health. Photo: RTHK

Sophia Chan Siu-chee, the Secretary for Food and Health, said Wednesday in a Legislative Council meeting that she communicated with officials from China’s National Health Commission every day, but she could not get the new figures. She said based on a bilateral agreement, the mainland and Hong Kong would share information about infectious diseases.

Rebecca Chan Hoi-yan, a pro-establishment lawmaker and the political assistant to former Secretary for Food and Health Ko Wing-man, said public hospitals would not be able to fight against the Wuhan disease as they were all full.

Civic Party lawmaker Tanya Chan criticized the Hong Kong government for having not done enough to ask for new figures from the Wuhan government.

Alvin Yeung Ngok-kiu, another Civic Party legislator, said the government had to clarify whether it would recommend people wore masks in public places as it had previously banned protesters from wearing masks on the streets.

Chan avoided directly answering Yeung’s question, but said people who visit hospitals and clinics should wear masks, while those who feel sick should stay home.

She said public hospitals and clinics still had enough masks to use, while the Hospital Authority would continue to monitor the situation. She said a total of 1,400 beds would be added in 16 hospitals within days if necessary.

Read: Wuhan disease human transmission not ruled out

Read: Hong Kong court rules mask law unconstitutional

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COVID-19's shifting impact: the changing relationship between infections and severe outcomes – News-Medical.Net

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A recent study published in the PLOS Biology Journal explored the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection hospitalization (IHR) and fatality (IFR) ratios in England over 23 months.

Study: Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England. Image Credit: AlexanderSteamaze/Shutterstock.com

Background

SARS-CoV-2 has globally increased morbidity and mortality rates. England witnessed a massive surge in hospitalizations and deaths after SARS-CoV-2 Alpha emerged.

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Consequently, a national lockdown was imposed in January 2021 to curb social contact, with the concurrent implementation of a mass vaccination program.

As a result, coronavirus disease 2019 (COVID-19) cases, hospitalizations, and deaths declined sharply in early 2021. Restrictions were gradually eased after March 2021, and the pandemic re-entered a growth phase with the emergence of the SARS-CoV-2 Delta in April 2021.

All domestic restrictions were removed in July 2021, with society reopening to an extent unseen since the start of the pandemic.

Restrictions were not since re-introduced at a large scale, even when the prevalence was high late in 2021 and during the Omicron waves.

Evaluating the trends between infection levels and hospitalization rates can help inform public health agencies and governments to implement proportionate and appropriate restrictions. When IHR and IFR are accurate, severe outcomes could be forecast over the short term.

The study and findings

In the present study, researchers explored the dynamics of SARS-CoV-2 IHR and IFR in England over 23 months. They used data from the real-time assessment of community transmission (REACT)-1 study that conducted 19 cycles of surveys from May 2020 to March 2022. Persons aged five or older were contacted for participation and sent a self-administered swab test.

Data on COVID-19 cases, hospitalizations, deaths, and vaccinations were accessed from an official government website. The time lag from swab positivity to the occurrence of severe outcomes declined throughout the study.

There was a time lag of 19 days to hospitalization and 26 days to death during REACT-1 cycles 1-7 (May 1 to December 3, 2020).

During cycles 14-19 (September 9, 2021, to March 31, 2022), time lags were shorter at seven days to hospitalization and 18 days to death. Contrastingly, time lags were extremely long during cycles 8-13 (December 30, 2020, to July 12, 2021) at 24 days to hospitalization and 40 days to death. The IHR and IFR were estimated to be 2.6% and 0.67%, respectively, during cycles 1-7.

IHR was 0.76%, and IFR was 0.09% during cycles 14-19. The IHR and IFR were far lower for participants aged 64 or younger than those aged 65 or above during cycles 1-7 and 14-19.

The team compared the average IFRs and IHRs over four-week intervals to a baseline period (May 1 to November 11, 2020).

The average IFR was 1.68 and 1.31 times greater than the baseline in late November 2020 and January 2021, when SARS-CoV-2 Alpha accounted for 15% and 86% of cases, respectively. The average IHR and IFR reduced to 0.51 and 0.25 of baseline in April 2021, when 47% of the population had received at least one vaccine dose.

The average IHR and IFR were 0.84 and 0.43 of baseline in June-July 2021, respectively, when the Delta variant accounted for 99% of infections and 50% of the population had been double vaccinated.

IHR and IFR showed a steady decline from September 2021 and were sharply reduced in December 2021, when the proportion of booster vaccine recipients increased.

The mean IHR was 0.62%, and the average IFR was 0.06% by March 2022, when the Omicron variant caused over 99% of cases. The time lag between swab positivity and daily case numbers varied throughout the study and was three days, -7 days, and one day during cycles 1-7, 8-13, and 14-19, respectively.

The case ascertainment rate, defined as the proportion of cases identified with a positive test through mass testing, was 36.1% overall and varied throughout the study.

It increased from around 20% in July 2020 to 30% during August-December 2020, with a sharp surge between May and July 2021 and a steep decline between December 2021 and March 2022.

Conclusions

The researchers illustrated the temporal relationship between community prevalence of SARS-CoV-2 infection and severe outcomes.

They estimated SARS-CoV-2 IHR, IFR, and case ascertainment rates by assessing the differences in the swab positivity estimates and the time lag of COVID-19 cases, hospitalizations, and deaths.

The findings revealed a decline in SARS-CoV-2 infection severity over time in England. Community-based studies like REACT-1 can provide unbiased temporal estimates of infection levels, allowing for rapid detection of IHR or IFR changes.

Appropriate interventions can be implemented with early warnings when they are highly effective.

Journal reference:

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5 Ways to Take a Break at Work (In Less Than 60 Seconds) – Outside

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No one needs to tell you that work is a source of stress. But the workplace—and its unrelenting deadlines, meetings, politics, and frustrations—has become the leading stressor for Americans. According to a recent review of data, 83 percent of workers in the United States suffer from work-related stress. Among that group, 25 percent report that work is their number one complaint.

While work stress takes a toll in numerous ways in our everyday lives, perhaps the largest toll is on mental well-being. Recently Calm, the mental health brand, asked users what difficult moments prompted them to use the app. Facing challenges at work was the most common response.

Eradicating workplace stress obviously isn’t an option. That leaves everyone in need of different ways to handle that stress better. The answer may seem too obvious.

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“Taking a mental health break can take you out of the monotony—or chaos—of your day and bring you back to the present, allowing you to re-enter your work day less stressed and more focused, increasing your productivity in a calm and sustainable way,” says Madeline Lucas, a New York-based therapist at Real, a mental health therapy platform.

Easier said than done. If you think you’re too busy to take a break, feel guilty slipping away during work hours, or don’t want your co-workers to think you’re unproductive, you’re not alone. Those are the top three reasons why workers don’t take a break during the day for their mental health, according to a Calm Business report.

But finding even 60 seconds to be present with yourself and your surroundings can help you feel more centered, says Jay Shetty, a life coach, host of the On Purpose podcast, best-selling author, and chief purpose officer at Calm.

When Do You Need to Take a Break at Work?

It may seem like you would know when you need to take a break. But that’s not necessarily the case. “Taking breaks at work is not intuitive,” Shetty says. “We haven’t been trained on when to take breaks or how to do them, so most people just skip them and take their stress into the next task or meeting.”

There are actually classic signs of needing to take a mental health break. Lucas explains, “Are you, for instance, having difficulty focusing or completing a task, becoming easily distracted by other thoughts or activities, or even noticing a dull numbness if you’ve been on your computer too long?”

You might also notice that you’re more irritated, annoyed, or resentful toward your coworkers and tasks than usual. Even feeling constantly fatigued can indicate you need to step away from the screen. Check in with yourself throughout the day—or even the hour.

5 Ways to Take a Break at Work (In Less Than 60 Seconds)

How long you take a break is up to you. The more time you can devote to your mental health, the better. Although any amount of time for a break is better than none. Even 60 seconds.

The duration of your break might also depend on your manager or your workplace. “No one will probably notice if you take one minute for a few deep breaths before a meeting,” Shetty says.
If, however, you intend to take a longer break, you might want to communicate your need for that.

The most important thing to remember is, as Shetty says, “a short break is better than no break.” Here are five to try.

1. Stretch Your Neck

Settle yourself comfortably in your chair, close your eyes or soften your gaze, and release your shoulders away from your ears. Lower your chin toward your chest and slowly roll your head from side to side. As you do this, breathe deeply. Repeat at least two to three times, Lucas says. Releasing tight muscles in your neck can activate the vagus nerve, which in turn kicks in your parasympathetic nervous system, which lessens physical and mental tension.

2. Practice the Three Ws

This refers to “walk, water, and window,” a practice that Shetty created. First, take a walk, which has stress-reducing benefits. Bonus points if you can be outside. But even just walking into another room or down the hallway can help, he says.

Next, drink some water. “Five cups of water per day lowers the risk of anxiety,” he says. This, by the way, comes from a recent study in the World Journal of Psychiatry.

The last one is looking into the distance through a window. Not only will you give your mind a well-needed break, you’ll also reduce eye strain, he says. Follow the 20-20-20 rule from the American Optometric Association: Every 20 minutes, take a 20-second break and look at something 20 feet away.

3. Slow Your Breathing

Turning your attention to your breath is one of the most time-tested and science-backed ways to give your body and mind a break. Slowing your breath causes your heart rate to lessen, your blood pressure to lower, and your mind to quiet. And it can start to take effect in just a few seconds. Although focusing on your breath  won’t eradicate the source of your stress, it can modulate how you show up to it.

Inhale for a count of four and exhale for a count of four. Or as you breathe in, say “inhale” in your head, and say “exhale” as you breathe out. You could also use a specific mantra that matches your inhale and exhale. One option sometimes used in yoga is “so hum,” which means “I am that” in Sanskrit; say “so” to yourself as you inhale and “hum” as you exhale.

4. Tap it out

Using your fingertips, lightly tap across your chest, then down each arm and back up to your chest. Take long, slow breaths as you do so. “This can awaken your system and reground you in the present moment,” Lucas says.

How, exactly? “Tapping is another way you can activate the parasympathetic nervous system to signal messages of safety, calm and relaxation to the brain,” she says. Science supports this.

5. Give (and Receive) Some TLC

Although silly pet videos can soothe your nervous system by making you laugh, research indicates that the real deal is even more effective. Engaging with a cat or dog for 10 minutes can significantly lower levels of the stress hormone cortisol. Can’t take a break for that long? Finding one minute to play with your fur baby isn’t going to make you feel worse.

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Canadian researchers use AI to find a possible treatment for bacteria superbug – CBC.ca

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The Current22:28AI helps kill drug-resistant superbug

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Researchers have discovered a promising treatment for an antibiotic-resistant superbug — with the help of artificial intelligence.

Acinetobacter baumannii is a hospital-acquired pathogen that’s commonly found on surfaces in clinical settings. It can cause diseases such as pneumonia, meningitis and sepsis.

According to the World Health Organization, A. baumannii is a critical threat to patients whose care requires devices such as ventilators, due in large part to its resistance against most antibiotics.

“It’s remarkably challenging [to tackle],” said Jonathan Stokes, an assistant professor at McMaster University, in Hamilton, Ont., who led the research.

“When we go to search for new antibiotics, it necessitates that we start looking for chemicals, antibiotics that have brand new structures and brand new functions. You know, we have to develop a fundamentally new treatment,” he told The Current‘s Matt Galloway.

Usually, this involves testing hundreds of thousands of chemicals to see which ones work best against the disease. But Stokes says “that’s remarkably laborious and time-consuming and expensive.”

That’s why Stokes and the rest of the team, which included scientists at the Massachusetts Institute of Technology, turned to AI for assistance.

“Ideally, by leveraging these artificial intelligence algorithms, they can look at these chemicals much more rapidly,” he said. “And by looking at a broad array of chemicals very rapidly, they can help us prioritize which experiments to run in the laboratory.”

Stokes and his team published their findings in the journal Nature Chemical Biology on Thursday.

Training the model

Before the AI can find a chemical that could kill A. baumannii, Stokes and his team trained it by feeding it data on bacteria-killing chemicals and chemical structures “associated with the antibacterial activity that we want,” he said.

“We physically tested in the laboratory about 7,500 chemicals, looking at which ones inhibited the growth of Acinetobacter and which ones did not,” he said. 

A 3D illustration shows the morphology of Acinetobacter baumannii, an antibiotic-resistant superbug that, thanks in part to McMaster University scientists and AI, might finally be treatable. (Kateryna Kon/Shutterstock)

Once the AI model was trained, the team could then show it new chemicals it had never seen before. It could then predict which of those chemicals it thought were antibacterial and which ones it thought weren’t.

Eventually, the AI discovered a new antibacterial compound they named abaucin. Further laboratory experiments found that it can treat A. baumannii-infected wounds in mice.

The next step, Stokes said, is to perfect the drug in the laboratory and then perform clinical trials.

This work highlights a promising lead in the fight against A. baumannii — and the role of AI technology in that cause.

“When we completed this project … I feel like we’re entering an era where AI approaches can meaningfully influence how we discover clinical medicine from the earliest stages of discovery,” Stokes said.

Large-scale experiments

For Stokes, AI promises to dramatically speed up scientific and medicinal research.

“Humans might not have to spend so much time and effort performing these large-scale experiments,” he said. 

WATCH: How AI could change the future of our health care

How AI could change the future of our health care

4 years ago

Duration 2:53

Often called the future of health care, artificial intelligence is already finding a place in Canadian hospitals. But AI is far from perfect and some worry about the costs that could come with it.

That promise resonates with other scientists, like Rahul Krishnan, an assistant professor in computational medicine at the University of Toronto.

“If it helps us get to discoveries even 10 per cent faster, that’s a huge win for society as a whole, because we can start making and discovering these drugs at a much faster scale,” he told Galloway.

My goal is to discover new antibiotics to save people’s lives. So if there are … powerful AI technological developments that help me achieve that goal, I am going to embrace them.-Jonathan Stokes

Krishnan, who studies the intersection of AI technology and health care, says the key idea for AI in medicine is to help clinicians make faster, safer decisions.

An AI could look at a patient’s medical records and use them “in conjunction with a predictive model to assist in clinical decision-making,” he said. For example, an AI could quickly predict whether a patient was likely to develop diabetes and then “have a clinician prescribe early interventions,” preventing more serious outcomes later on.

“From a public health standpoint, having the ability to have good predictive models deployed at scale might actually help individuals make better downstream decisions about their health,” he added.

Is AI data accurate, or ethical?

That’s not to say the introduction of AI wouldn’t have its challenges, though.

The growing popularity of AI in multiple fields has led to some warning it could lead to privacy and copyright violations and misinformation campaigns.

Executives, researchers and AI pioneers have warned that its unregulated use of AI could pose serious risks or even threats to humanity itself.

Krishnan says AI could be susceptible to biases that exist in the medical sphere, depending on the data used to train it.

“We know from a lot of studies that have been done over the decades that the health care system that we have in North America is incredibly, in some ways, unfair,” he said. 

“Those inequities are often translated into the data that are then fed into these algorithms. And if not corrected for at the point of training, these biases get encoded into the algorithm and every subsequent output that they put out.”

There’s also a risk of the AI making things up, even if it’s trained on reliable data.

“It, in some sense, can often hallucinate, and this is one of the failure modes of large language models … and obviously, that is a huge concern in the context of health care,” Krishnan said.

A woman in a white lab coat and black gloves inspects a small container.
Denise Catacutan, graduate student in the Department of Biochemistry & Biomedical Science and co-author of the paper. (Matt Clarke/McMaster University)

Stokes believes AI technology is advanced enough that it can be implemented now. But he says there’s still a lack of data “across many disease areas” to train these models.

“These AI models are … data hungry. They need to see a lot of examples in order to make robust predictions,” he said.

“So I think the acquisition of data with which we can train these models needs to be at the forefront of all of our thought.” 

Embracing AI in medicine

Krishnan sees a future where AI helps a clinician “automate away a lot of the simplistic cases,” freeing them up for more complex work.

“They can spend their cognitive effort and the cognitive cycles on the much more complex cases that demand their attention,” he said.

It’s this augmentation that leads to Stokes to believe that AI have a place in the laboratory and hospitals.

“My goal currently is to discover new antibiotics to save people’s lives,” he said.

“So if there are, you know, more robust, more powerful AI technological developments that help me achieve that goal, I am going to embrace them.”


Produced by Kate Cornick, Willow Smith and Magan Carty.

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