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Experts Predict

Experts Predict What Flu Season Will Be Like During The Pandemic – HuffPost

As if we didn’t have enough public health concerns right now, cold and flu season is coming up.

We generally think of flu season as a normal part of life ― but there’s nothing normal about what’s happening this year. The coronavirus pandemic isn’t going away in the next few months, which means we’ll be dealing with COVID-19 alongside the other viruses and bacteria that appear in the chillier months.

So what happens when we have to deal with both at the same time? What can we do to prepare? Below, we spoke to experts about what they believe we’ll see when flu season hits the U.S. this fall and winter.

Let’s start with the good news: Flu rates overall might go down

Those vital health measures we’re taking to prevent COVID-19? Yeah, they really do work ― even beyond the coronavirus.

“Data from countries which would normally experience the flu season earlier (countries in the southern hemisphere) are seeing record low rates of the flu,” Kavita Patel, HuffPost’s medical contributor and a practicing internal medicine physician in Washington, D.C., wrote in an email. “More people are staying home, washing their hands and wearing masks. So it is possible we will see similarly low rates if we continue those important precautions.”

Some age groups may be more at risk for the flu because there could be lower rates of vaccination

Patel is worried that not as many people will proactively get a flu vaccine this year, so they can avoid medical centers during the pandemic. And that can put certain groups at risk.

“People might be reluctant” to go to the pharmacy or a doctor’s office, she said. “We know that people over the age of 65 as well as under the age of 2 are incredibly vulnerable to getting really sick from the flu ― including dying. … We could see an increase of cases in those categories.”

People’s anxiety will continue to increase

A recent report from the Centers for Disease Control and Prevention found a large increase in mental health problems during the pandemic. Experts predict this issue will only continue as we go into winter, especially with fewer social options and the stress of avoiding potential illness rises again.

“It is no surprise to anyone that the COVID-19 pandemic is causing a mental health crisis,” Cara Pensabene, medical director at EHE Health and an internal medicine specialist, told HuffPost. As flu season approaches, “there will be increased amount of anxiety and stress amongst patients.”

Many will probably confuse flu and COVID-19 symptoms

“Many COVID-19 symptoms overlap with influenza symptoms including fever, chills, shortness of breath, fatigue, runny/stuffy nose, headache, muscle pain or aches and/or sore throat,” Pensabene said. “We will see many patients who may not otherwise seek medical advice or treatment for a common cold or the flu now turning to their healthcare providers for reassurance and help differentiating between the common cold, influenza, and COVID-19.”

If you’re in this camp, Pensabene said there’s one major differentiator between the flu and many COVID-19 cases: “One key symptom that is present with COVID-19 … is the loss of taste and smell.”

But never hesitate reaching out to your doctor when you’re sick; it doesn’t matter if it’s a cold, the flu, COVID-19 or anything else that’s making you feel unwell.

The spread could continue to affect businesses, travel and more

Over the summer, we’ve been able to get outside and generally keep our distance from others while going to restaurants, the beach and more. (Of course, being outside isn’t a complete safeguard against COVID.) In the winter, that’s obviously harder. There are fewer outdoor activities, which could lead to more people doing things indoors, which could potentially increase transmission rates, as both COVID-19 and the flu tend to spread more inside when people are in closer contact.

“Influenza and COVID-19 are both contagious respiratory illnesses [that] spread from person to person, between people who are in close contact with one another (within 6 feet), and mainly by droplets,” Pensabene said.

While we don’t know yet how exactly this might play out, we could see closings or more precautions required for businesses, restaurants and more. We could also see some more travel restrictions, Pensabene said.

Hospitals could get crowded again if people are too lax

By cold and flu season, we’ll have spent the majority of 2020 in a pandemic and a lot of that time indoors. This could lead to some serious fatigue. But if people don’t wear masks, practice social distancing, wash their hands or get flu shots ― basically if we get too secure and start throwing caution to the wind ― we could wind up with more severe illnesses.

“Hospitals tend to go from ‘normal’ to ‘overwhelmed’ pretty quickly,” Patel said. “That’s because of our ‘fee for service’ reimbursement system where hospitals have to try and stay pretty full (like a hotel) in order to keep the business running.”

Add carelessness, a pandemic and flu season to that and, “presto, you have a problem,” she added.

Here’s how to protect yourself during flu season this year

Want to do your part to stay healthy and make sure this isn’t the winter from hell? Number one, get your flu shot.

It’s essential to get a flu vaccine every year, but especially this year. Getting the vaccine isn’t just about protecting yourself from illness; it also protects other people who are more susceptible and those who may not be able to medically receive the vaccine.

“Simply put, get your flu shot and tell your family and friends and neighbors to get one,” Patel said. “Pharmacies can give them. Chances are your employer might also offer them. Get them, get them, get them. And remember, the flu shot doesn’t mean you won’t get the flu, but that you might get a less severe version. And you are playing your part in helping our entire country be protected through herd immunity.”

Pensabene also stressed the importance of knowing your own personal risk when it comes to both illnesses.

“We know that either one of these respiratory viruses can be dangerous for individuals with high risk conditions, and the combination of two could be fatal,” she said. “Schedule your physical examinations and your flu shots, and while you are there, talk to your doctor about your medical conditions to understand and begin reducing your vulnerability. Whether or not you are in a high-risk category, everyone needs to take steps to protect themselves and others from catching or spreading COVID-19.”

The final thing you can do? Prepare to keep doing what you’re doing now.

“Buckle up, it could be a bumpy ride,” Patel said. “I will be wearing my mask and you should too. And wash your hands, and stay 6 feet away.”

Experts are still learning about COVID-19. The information in this story is what was known or available as of publication, but guidance can change as scientists discover more about the virus. Please check the Centers for Disease Control and Prevention for the most updated recommendations.

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Algorithm Predict

Can an Algorithm Predict the Pandemic’s Next Moves? – The New York Times

Researchers have developed a model that uses social-media and search data to forecast outbreaks of Covid-19 well before they occur.

Credit…Tony Luong for The New York Times

Benedict Carey

Judging when to tighten, or loosen, the local economy has become the world’s most consequential guessing game, and each policymaker has his or her own instincts and benchmarks. The point when hospitals reach 70 percent capacity is a red flag, for instance; so are upticks in coronavirus case counts and deaths.

But as the governors of states like Florida, California and Texas have learned in recent days, such benchmarks make for a poor alarm system. Once the coronavirus finds an opening in the population, it gains a two-week head start on health officials, circulating and multiplying swiftly before its re-emergence becomes apparent at hospitals, testing clinics and elsewhere.

Now, an international team of scientists has developed a model — or, at minimum, the template for a model — that could predict outbreaks about two weeks before they occur, in time to put effective containment measures in place.

In a paper posted on Thursday on arXiv.org, the team, led by Mauricio Santillana and Nicole Kogan of Harvard, presented an algorithm that registered danger 14 days or more before case counts begin to increase. The system uses real-time monitoring of Twitter, Google searches and mobility data from smartphones, among other data streams.

The algorithm, the researchers write, could function “as a thermostat, in a cooling or heating system, to guide intermittent activation or relaxation of public health interventions” — that is, a smoother, safer reopening.

“In most infectious-disease modeling, you project different scenarios based on assumptions made up front,” said Dr. Santillana, director of the Machine Intelligence Lab at Boston Children’s Hospital and an assistant professor of pediatrics and epidemiology at Harvard. “What we’re doing here is observing, without making assumptions. The difference is that our methods are responsive to immediate changes in behavior and we can incorporate those.”

Outside experts who were shown the new analysis, which has not yet been peer reviewed, said it demonstrated the increasing value of real-time data, like social media, in improving existing models.

The study shows “that alternative, next-gen data sources may provide early signals of rising Covid-19 prevalence,” said Lauren Ancel Meyers, a biologist and statistician at the University of Texas, Austin. “Particularly if confirmed case counts are lagged by delays in seeking treatment and obtaining test results.”

The use of real-time data analysis to gauge disease progression goes back at least to 2008, when engineers at Google began estimating doctor visits for the flu by tracking search trends for words like “feeling exhausted,” “joints aching,” “Tamiflu dosage” and many others.

The Google Flu Trends algorithm, as it is known, performed poorly. For instance, it continually overestimated doctor visits, later evaluations found, because of limitations of the data and the influence of outside factors such as media attention, which can drive up searches that are unrelated to actual illness.

Since then, researchers have made multiple adjustments to this approach, combining Google searches with other kinds of data. Teams at Carnegie-Mellon University, University College London and the University of Texas, among others, have models incorporating some real-time data analysis.

“We know that no single data stream is useful in isolation,” said Madhav Marathe, a computer scientist at the University of Virginia. “The contribution of this new paper is that they have a good, wide variety of streams.”

In the new paper, the team analyzed real-time data from four sources, in addition to Google: Covid-related Twitter posts, geotagged for location; doctors’ searches on a physician platform called UpToDate; anonymous mobility data from smartphones; and readings from the Kinsa Smart Thermometer, which uploads to an app. It integrated those data streams with a sophisticated prediction model developed at Northeastern University, based on how people move and interact in communities.

The team tested the predictive value of trends in the data stream by looking at how each correlated with case counts and deaths over March and April, in each state.

In New York, for instance, a sharp uptrend in Covid-related Twitter posts began more than a week before case counts exploded in mid-March; relevant Google searches and Kinsa measures spiked several days beforehand.

The team combined all its data sources, in effect weighting each according to how strongly it was correlated to a coming increase in cases. This “harmonized” algorithm anticipated outbreaks by 21 days, on average, the researchers found.

Looking ahead, it predicts that Nebraska and New Hampshire are likely to see cases increase in the coming weeks if no further measures are taken, despite case counts being currently flat.

“I think we can expect to see at least a week or more of advanced warning, conservatively, taking into account that the epidemic is continually changing,” Dr. Santillana said. His co-authors included scientists from the University of Maryland, Baltimore County; Stanford University; and the University of Salzburg, as well as Northeastern.

He added: “And we don’t see this data as replacing traditional surveillance but confirming it. It’s the kind of information that can enable decision makers to say, ‘Let’s not wait one more week, let’s act now.’”

For all its appeal, big-data analytics cannot anticipate sudden changes in mass behavior any better than other, traditional models can, experts said. There is no algorithm that might have predicted the nationwide protests in the wake of George Floyd’s killing, for instance — mass gatherings that may have seeded new outbreaks, despite precautions taken by protesters.

Social media and search engines also can become less sensitive with time; the more familiar with a pathogen people become, the less they will search with selected key words.

Public health agencies like the Centers for Disease Control and Prevention, which also consults real-time data from social media and other sources, have not made such algorithms central to their forecasts.

“This is extremely valuable data for us to have,” said Shweta Bansal, a biologist at Georgetown University. “But I wouldn’t want to go into the forecasting business on this; the harm that can be done is quite severe. We need to see such models verified and validated over time.”

Given the persistent and repeating challenges of the coronavirus and the inadequacy of the current public health infrastructure, that seems likely to happen, most experts said. There is an urgent need, and there is no lack of data.

“What we’ve looked at is what we think are the best available data streams,” Dr. Santillana said. “We’d be eager to see what Amazon could give us, or Netflix.”

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