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Are There Better Ways to Track Covid Cases?

An increasing reliance on at-home testing and the closings of mass testing sites are making official case counts less reliable, scientists say.

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When the highly transmissible Omicron variant of the coronavirus arrived in the United States last fall, it pushed new case numbers to previously unseen peaks.

Even then, the record wave of recorded infections was a significant undercount of reality.
In New York City, for example, officials logged more than 538,000 new cases between January and mid-March, representing roughly 6 percent of the city’s population. But a recent survey of New York adults suggests that there could have been more than 1.3 million additional cases that were either never detected or never reported — and that 27 percent of the city’s adults may have been infected during those months.

The official tally of coronavirus infections in the United States has always been an underestimate. But as Americans increasingly turn to at-home tests, states shutter mass testing sites and institutions cut back on surveillance testing, case counts are becoming an increasingly unreliable measure of the virus’s true toll, scientists say.

“It seems like the blind spots are getting worse with time,” said Denis Nash, an epidemiologist at the CUNY Graduate School of Public Health & Health Policy who led the New York City analysis, which is preliminary and has not yet been published.

That could leave officials increasingly in the dark about the spread of the highly contagious new subvariant of Omicron known as BA.2, he said, adding, “We are going to be more likely to be surprised.” On Wednesday, New York officials announced that two new Omicron subvariants, both descended from BA.2, have been circulating in the state for weeks and are spreading even faster than the original version of BA.2.

The official case count can still pick up major trends, and it has begun to tick up again as BA.2 spreads. But undercounts are likely to be a bigger problem in the weeks ahead, experts said, and mass testing sites and widespread surveillance testing may never return.

“That’s the reality we find ourselves in,” said Kristian Andersen, a virologist at the Scripps Research Institute in San Diego. “We don’t really have eyes on the pandemic like we used to.”
To track BA.2, as well as future variants, officials will need to pull whatever insights they can from an array of existing indicators, including hospitalization rates and wastewater data. But truly keeping tabs on the virus will require more creative thinking and investment, scientists said.

For now, some scientists said, people can gauge their risk by deploying a lower-tech tool: paying attention to whether people they know are catching the virus.

“If you’re hearing your friends and your co-workers get sick, that means your risk is up and that means you probably need to be testing and masking,” said Samuel Scarpino, the vice president of pathogen surveillance at the Rockefeller Foundation’s Pandemic Prevention Institute.

Tracking the virus has been a challenge since the earliest days of the pandemic, when testing was severely constrained. Even when testing improved, many people did not have the time or resources to seek it out — or had asymptomatic infections that never made themselves known.
By the time Omicron hit, a new challenge was presenting itself: At-home tests had finally become more widely available, and many Americans relied on them to get through the winter holidays. Many of those results were never reported.

“We haven’t done the groundwork to systematically capture those cases on a national level,” said Katelyn Jetelina, an epidemiologist at the University of Texas Health Science Center at Houston.

Some jurisdictions and test manufacturers have developed digital tools that allow people to report their test results. But one recent study suggests that it may take work to get people to use them. Residents of six communities across the country were invited to use an app or an online platform to order free tests, log their results and then, if they chose, send that data to their state health departments.

Nearly 180,000 households used the digital assistant to order the tests, but just 8 percent of them logged any results on the platform, researchers found, and only three-quarters of those reports were sent on to health officials.

General Covid fatigue, as well as the protection that vaccination provides against severe symptoms, may also prompt fewer people to seek testing, experts said. And citing a lack of funds, the federal government recently announced that it would stop reimbursing health care providers for the cost of testing uninsured patients, prompting some providers to stop offering those tests for free. That could make uninsured Americans especially reluctant to test, Dr. Jetelina said.

“The poorest neighborhoods will have even more depressed case numbers than high-income neighborhoods,” she noted.

Monitoring case trends remains important, experts said. “If we see an increase in cases, it’s an indicator that something is changing — and quite possibly that something is changing because of a larger shock to the system, like a new variant,” said Alyssa Bilinski, a public health policy expert at the Brown University School of Public Health.

But more modest increases in transmission may not be reflected in the case tally, which means that it could take officials longer to detect new surges, experts said. The problem could be exacerbated by the fact that some jurisdictions have begun updating their case data less frequently.

Dr. Nash and his colleagues have been exploring ways to overcome some of these challenges. To estimate how many New Yorkers may have been infected during the winter Omicron surge, they surveyed a diverse sample of 1,030 adults about their testing behaviors and results, as well as potential Covid-19 exposures and symptoms.

People who reported testing positive for the virus on tests administered by health care or testing providers were counted as cases that would have been caught by standard surveillance systems. Those who tested positive only on at-home tests were counted as hidden cases, as were those who had probable unreported infections — a group that included people who had both Covid-19-like symptoms and known exposures to the virus.

The researchers used the responses to calculate how many infections might have escaped detection, weighting the data to match the demographics of the city’s adult population.
The study has limitations. It relies on self-reported data and excludes children, as well as adults living in institutional settings, including nursing homes. But health departments could use the same approach to try to fill in some of their surveillance blind spots, especially during surges, Dr. Nash said.

“You could do these surveys on a daily or weekly basis and quickly correct prevalence estimates in real time,” he said.

Another approach would be to replicate what Britain has done, regularly testing a random selection of hundreds of thousands of residents. “That’s really the Cadillac of surveillance methods,” said Natalie Dean, a biostatistician at Emory University.

The method is expensive, however, and Britain has recently started scaling back its efforts. “It’s something that should be part of our arsenal in the future,” Dr. Dean said. “It’s sort of unclear what people have the appetite for.”

The spread of Omicron, which easily infects even vaccinated people and generally causes milder disease than the earlier Delta variant, has prompted some officials to put more emphasis on hospitalization rates.

“If our goal is to track serious illness from the virus, I think that’s a good way to do it,” said Jason Salemi, an epidemiologist at the University of South Florida.

But hospitalization rates are lagging indicators and may not capture the true toll of the virus, which can cause serious disruptions and long Covid without sending people to the hospital, Dr. Salemi said.

Indeed, different metrics can create very different portraits of risk. In February, the Centers for Disease Control and Prevention began using local hospitalization rates and measures of hospital capacity, in addition to case counts, to calculate its new “Covid-19 community levels,” which are designed to help people decide whether to wear masks or take other precautions. More than 95 percent of U.S. counties currently have low community Covid-19 levels, according to this measure.

But the C.D.C.’s community transmission map, which is based solely on local case and test positivity rates, suggests that just 29 percent of U.S. counties currently have low levels of viral transmission.

Hospitalization data may be reported differently from one place to another. Because Omicron is so transmissible, some localities are trying to distinguish between patients who were hospitalized specifically for Covid-19 and those who picked up the virus incidentally.

“We felt like, because of the intrinsic factors of the virus itself that we’re seeing circulating in our region now, that we needed to update our metrics,” said Dr. Jonathan Ballard, the chief medical officer at the New Hampshire Department of Health and Human Services.

Until late last month, New Hampshire’s Covid-19 online dashboard displayed all inpatients with active coronavirus infections. Now, it instead displays the number of hospitalized Covid-19 patients taking remdesivir or dexamethasone, two frontline treatments. (Data on all confirmed infections in hospitalized patients remains available through the New Hampshire Hospital Association, Dr. Ballard noted.)

Another solution is to use approaches, such as wastewater surveillance, that don’t rely on testing or health care access at all. People with coronavirus infections shed the virus in their stool; monitoring the levels of the virus in wastewater provides an indicator of how widespread it is in a community.

“And then you combine that with sequencing, so you get a sense of what variants are circulating,” said Dr. Andersen, who is working with colleagues to track the virus in San Diego’s wastewater.

The C.D.C. recently added wastewater data from hundreds of sampling sites to its Covid-19 dashboard, but coverage is highly uneven, with some states reporting no current data at all. If wastewater surveillance is going to fill in the testing gaps, it needs to be expanded, and the data needs to be released in near real time, scientists said.

“Wastewater is a no-brainer to me,” Dr. Andersen said. “It gives us a really good, important passive surveillance system that can be scaled. But only if we realize that that’s what we have to do.”

Dr. Scarpino, of the Pandemic Prevention Institute, said that there were other data sources that officials could leverage, including information on school closings, flight cancellations and geographic mobility.

“One of the things we’re not doing a good enough job of doing is pulling those together in a thoughtful, coordinated way,” Dr. Scarpino said.


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Rally bags $12M to build the future of e-commerce checkout

E-commerce had a moment during the global pandemic, but not only have things chilled since then, it’s gotten downright competitive as the economy cooled in the past year, according to Jordan Gal, co-founder and CEO of Rally.

“Founders in this space used to speak of optimism, but that has turned into realism, and people are more careful,” Gal told TechCrunch. “The pie seems to have stopped growing, and there’s more ferocious competition for what’s left in that pie.”

Gal went on to explain that merchants are having to make harder decisions, including whether they can afford to invest in software.

That’s why Rally, a composable checkout platform for e-commerce merchants, has broken up its business into two segments: the first to meet merchants where they are with integrations to commerce tools, like Salesforce Commerce Cloud, Magento and BigCommerce; the second to offer merchants a “headless” ecosystem.

The term “headless” refers to the ability to change the front end or back end of a website without affecting the other. Gal said he was not able to provide details just yet, but said Rally is close to announcing a partnership with companies specializing in front end and back end to offer headless-as-a-service.

Gal started Rally with Rok Knez to create checkout tools for merchants outside of the Shopify ecosystem. Both were previously involved with another checkout company, CartHook, and led the company to process nearly $3 billion in transactions for Shopify merchants before selling to Pantastic in 2021, Gal said.

Rally, which is working with 50 e-commerce merchants currently, provides one-click checkout with payment processing and tools for post-purchase offers that turns the purchase into a multi-revenue channel by allowing the merchant to inject offers after the checkout. For example, rather than going right to a “thank you” page, consumers would be offered the option of upgrading to a subscription or purchasing additional similar products in a way that doesn’t interrupt the payment flow.

Implementing the post-purchase offer has helped merchants increase revenue by over 12% on average, Gal said.

Meanwhile, over the past 12 months, Rally has doubled the size of its team and is “doing millions in monthly GMV (gross merchandise volume),” Gal said.

TechCrunch previously profiled the company when it raised $6 million in seed funding. Today, the company announced additional funding of $12 million in Series A funding. It was led by March Capital, which was joined by Felix Capital, Commerce Ventures, Afore Capital, Alumni Ventures and Kraken Ventures. The new investment, which closed in the first quarter of 2023, gives Rally $18 million in total venture-backed capital.

Gal plans to focus the new funding on go-to-market, including entering new markets, like enterprise and international, and expanding integrations beyond Swell, BigCommerce and others, including Salesforce Commerce Cloud, commercetools, Affirm and AfterPay. Rally will also focus on strengthening its fraud protection offering and build out web3 features, starting with allowing merchants to accept cryptocurrencies in their checkout.

“We want to establish a reputation as the best choice when a merchant is looking to either upgrade their checkout or build a new site without having to build their own checkout,” Gal said. “You can’t just build it and leave it alone, so merchants are looking for a partner that they can trust so they can focus on what they’re best at.”

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So you want to launch an AI startup

t seems like it’s the best of times for founders thinking about launching an AI startup, especially with OpenAI releasing ChatGPT to the masses, as it has the potential to really put AI front and center in business and perhaps everything we do technologically. Who wouldn’t want to launch a startup right now with the energy and hype surrounding the industry?

But it also could be the worst of times for founders thinking about launching an AI startup, especially one that can grow and be defensible against incumbents in a fast-changing environment. And that’s a real problem for companies thinking about this area: AI is evolving so rapidly that your idea could be obsolete before it’s even off the ground.

How do you come up with a startup idea that can endure in such a challenging and rapidly evolving landscape? The bottom line is that the same principles that apply to previously successful startups apply here, too. It just may be a bit harder this time because of how quickly everything is moving.

A bunch of successful founders and entrepreneurs spoke last week at the Imagination in Action conference at MIT. Their advice could help founders understand what they need to do to be successful and take advantage of this technological leap.

What’s working?
CB Insights compiled data from 2021 and 2022 to understand where VC investment money has been going when it comes to generative AI startups. Given the recent hype around this area, it’s reasonable to think that the volume of investment will increase, and perhaps the allocation will be different, but this is what we have for now.

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New Zealander without college degree couldn’t talk his way into NASA and Boeing—so he built a $1.8 billion rocket company

This story is part of CNBC Make It’s The Moment series, where highly successful people reveal the critical moment that changed the trajectory of their lives and careers, discussing what drove them to make the leap into the unknown.

In early 2006, Peter Beck took a “rocket pilgrimage” to the U.S.

The native New Zealander always dreamed of sending a rocket into space. He even skipped college because of it, taking an apprenticeship at a tools manufacturer so he could learn to work with his hands, tinkering with model rockets and propellants in his free time.

By the time of his pilgrimage, he’d built a steam-powered rocket bicycle that traveled nearly 90 mph. He hoped his experiments were enough to convince NASA or companies like Boeing to hire him as an intern. Instead, he was escorted off the premises of multiple rocket labs.

“On the face of it, here’s a foreign national turning up to an Air Force base asking a whole bunch of questions about rockets — that doesn’t look good,” Beck, now 45, tells CNBC Make It.

Still, he learned that few companies were actually building what he wanted to build: lightweight, suborbital rockets to transport small satellites. On the flight back to New Zealand, he plotted his future startup, even drawing a logo on a napkin.

Convincing investors to back someone without a college degree in an industry where he couldn’t even land an internship wouldn’t be easy. Failure would push him even further away from his lifelong dream.

Beck launched the company, Rocket Lab, later that same year. In 2009, it became the Southern Hemisphere’s first private company to reach space. Today, it’s a Long Beach, California-based public company with a market cap of $1.8 billion. It has completed more than 35 space launches, including a moon-bound NASA satellite last year.

Here, Beck discusses how he turned his disappointment into opportunity, the biggest challenges he faced, and whether he ever regrets his decision to create Rocket Lab.

CNBC Make It: When you didn’t land an aerospace job in the U.S., you immediately started thinking about launching your own company. Why?

Beck: One of the things I’m always frustrated with is how long everything takes. Ask anybody who works around me: There’s a great urgency in everything. I don’t walk upstairs, I run upstairs. As we’ve grown as a company, it’s always a sprint.

I wish things would get faster. I’m always battling time.

How do you recognize a window of opportunity opening, and when is it worth the risk to jump through it?

Back your intuition and go for it.

I would classify my job as taking an enormous risk and then mitigating that risk to the nth degree. Given that, you have to see windows of opportunity and run into them.

The challenge is that, especially within this industry, you have to poke your head into the corner but not commit too deeply. Otherwise, you’ll get your head cut off. I start by being very analytical: “OK, we’re here. What happened for us to get here? And how do we get out of here?”

Sometimes, you can take big risks. Sometimes, you need to be very safe and methodical about how to back out of situations. Control the things you can control and acknowledge the things you can’t control.

Running a rocket company is kind of like that scene in “Indiana Jones,” where he’s getting chased by that giant ball. You have to flawlessly execute, because the moment that you don’t, the consequences can be terminal for the company pretty quickly.

What do you wish you’d known when you decided to start your own rocket company?

At the end of the day, I probably wouldn’t change anything. There were plenty of errors and failures along the way, but ultimately, those things create the DNA of a company.

Getting your first rocket to orbit is the easiest part. On rocket No. 1, you’ve got all your engineers and technicians poring over one rocket for a large period of time. Now, there’s one rocket that rolls out of that production line every 18 days. That’s just immensely more difficult.

Sometimes, it’s really good to have a bit of a bad day. Not during a flight, obviously, but during testing. Just when you think things are going good, you’re reminded of how hard this business really is. Every time that you take too much of a breath, you’ll be humbled very quickly.

What’s the biggest challenge you faced getting started?

Nothing happens without funding in this business. When I first started Rocket Lab, I ran around Silicon Valley trying to raise $5 million.

At that time, that was an absurd amount of money for a rocket startup. A rocket startup was absurd [in general], it was only SpaceX then. A rocket startup from someone living in New Zealand was even more absurd.

We grew up and tried to raise really small amounts of funding. That really shaped us about being ruthlessly efficient and absolutely laser-focused on execution. The hardest thing [we did] is actually the thing that shaped the company into the most successful form it could be.

When do you feel the most pressure?

The most terrifying thing I’ve ever done is the staff Christmas party. That’s the moment you realize that your decisions are responsible for these people’s livelihoods. As a public company, I take that even more seriously. It’s a tremendous amount of pressure.

On top of that, you have a customer. That can be a national security customer, where lives are depending on you delivering that asset to orbit. It can be a startup, and there can be hundreds of people at a company that you can destroy just by putting the payload into the ocean.

So I absolutely hate launch days. Now that we’ve done 35 launches, I’m not puking in the toilet like I used to. But man, I still really don’t enjoy it, because there’s just so much invested in each launch. So much responsibility.

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