Source Code: Your daily look at what matters in tech.

source-codesource codeauthorIssie LapowskyNoneWant your finger on the pulse of everything that's happening in tech? Sign up to get David Pierce's daily newsletter.64fd3cbe9f
×

Get access to Protocol

Your information will be used in accordance with our Privacy Policy

I’m already a subscriber
Power

Where should vaccines go next? In California, machines could hold the answer.

A firm called Macro-eyes is using machine learning to predict which of California's community health centers are equipped to handle the vaccine.

Where should vaccines go next? In California, machines could hold the answer.

With data on vaccine preparedness in community health centers scarce, Direct Relief is turning to machine learning firm Macro-eyes for help "predicting the present."

Photo: Province of British Columbia/Flickr

Andrew Schroeder has been trying for a while now to figure out which of California's community health centers are equipped to handle and distribute the COVID-19 vaccine. These are the places that serve California's poorest people — more than 7 million of them, to be exact — and, as vice president of research and analysis for the humanitarian aid organization Direct Relief, Schroeder wants to make sure they're ready for the vaccine as more supply becomes available.

So, working with the California Primary Care Association, he recently sent a survey around to the organizations that manage some 1,370 federally qualified healthcare centers in the state, asking questions about their power sources, their refrigeration capabilities and their staffing. In the end, the survey yielded data on just 106 sites — less than 8% of the total.

"We respond to so many disasters across California, and we just run into this repeated frustration at not having enough detailed information at the site level," he said, noting that surveys are notoriously unhelpful in disaster response scenarios.

But sending vaccines to facilities that can't store them isn't an option when supply is so limited and the public health need is so great. So this time, Schroeder is taking a new approach. Last week, Direct Relief and the California Primary Care Association launched a project with a Washington-based firm called Macro-eyes that's promising to use machine learning to predict the vaccine readiness of every community health center in the state.

Founded in 2013 by an MIT professor and former hedge fund trader, Macro-eyes uses a combination of publicly available data, government-provided data and satellite imagery to help healthcare officials "predict the present," as CEO Benjamin Fels put it.

If a government wants to determine whether a given healthcare facility has backup power, for instance, Macro-eyes might start by, say, reviewing satellite imagery to see if there's a solar panel on the roof or using a web scraper to mine stories about recent investments in that facility. The company uses every scrap of information it finds as an input in its model, so it can then predict the characteristics of other, similarly situated facilities where data is more scarce.

"There's a portion of what we're doing where we are aggregating data, and there's a portion of what we're doing where we're using that data we aggregated to predict what's missing," Fels said.

Macro-eyes has already begun this work in parts of Africa where it's predicting healthcare infrastructure, population characteristics and healthcare utilization in countries like Sierra Leone and Tanzania, backed by more than $3 million in funding from the Bill & Melinda Gates Foundation. But this is the first deployment of this technology in the United States.

"The more data we have, the more we can share with the state and the county, and the better it is for our community health centers, which we know are the key players in reaching diverse populations and the really hard-to-reach populations," said Robert Beaudry, executive vice president of the California Primary Care Association.

Using machine learning in any healthcare setting has traditionally been a fraught endeavor. While these tools hold the promise of improved diagnostics and resource allocation, stories abound of algorithms inadvertently entrenching racial biases in healthcare data and prioritizing care for white patients over Black patients with similar chronic illnesses.

When it comes to vaccine distribution, the stakes couldn't be any higher. A miscalculation about a given healthcare facility's readiness could result in well-prepared facilities and their patients being passed over for life-saving vaccines or, worse yet, vaccines going to waste in facilities that can't properly store them.

The potential downside isn't lost on Schroeder or Fels, so they're starting small. In the initial phase of the project, their goal is to predict three things about each facility: how much refrigeration it has, whether it has a backup power source and whether it serves a population that is at high risk of complications with COVID-19. Then, they plan to go back to a subset of those facilities to validate their predictions. That, they say, will be easier than constantly calling or surveying thousands of facilities at the height of a health crisis. It will at least create a pool of ground truth data and help them understand how accurate their predictions really were in the first place. Those answers will be fed back into the model to improve the rest of the predictions.

This, Fels said, is the difference between a static algorithm and a true machine-learning model.

"You're baking in that engagement with being proven wrong all the time, and that's a good thing," he said.

Besides, Schroeder argues, it's better than the alternative, which is working with next to no information at all. That has left community health centers sidelined when it comes to vaccine distribution. Until now, the state and local health agencies have mostly sent vaccines to large healthcare systems that they know are equipped to handle vaccinations. It also happens to be where the densest population of doctors and nurses, who were first in line for vaccines, happen to work. But as California's distribution plans expand, community health centers will need to play an increasingly important role, Schroeder argued, because they already have relationships with the very people who need those vaccines most.

"If we were leading with things like building community trust, the health centers would be at the forefront of how we think about the vaccine," Schroeder said, "but they're really in the back seat."

Protocol | China

China’s edtech crackdown isn’t what you think. Here’s why.

It's part of an attempt to fix education inequality and address a looming demographic crisis.

In the past decade, China's private tutoring market has expanded rapidly as it's been digitized and bolstered by capital.

Photo: Getty Images

Beijing's strike against the private tutoring and ed tech industry has rattled the market and led observers to try to answer one big question: What is Beijing trying to achieve?

Sweeping policy guidelines issued by the Central Committee of the Chinese Communist Party on July 24 and the State Council now mandate that existing private tutoring companies register as nonprofit organizations. Extracurricular tutoring companies will be banned from going public. Online tutoring agencies will be subject to regulatory approval.

Keep Reading Show less
Shen Lu

Shen Lu is a reporter with Protocol | China. She has spent six years covering China from inside and outside its borders. Previously, she was a fellow at Asia Society's ChinaFile and a Beijing-based producer for CNN. Her writing has appeared in Foreign Policy, The New York Times and POLITICO, among other publications. Shen Lu is a founding member of Chinese Storytellers, a community serving and elevating Chinese professionals in the global media industry.

After a year and a half of living and working through a pandemic, it's no surprise that employees are sending out stress signals at record rates. According to a 2021 study by Indeed, 52% of employees today say they feel burnt out. Over half of employees report working longer hours, and a quarter say they're unable to unplug from work.

The continued swell of reported burnout is a concerning trend for employers everywhere. Not only does it harm mental health and well-being, but it can also impact absenteeism, employee retention and — between the drain on morale and high turnover — your company culture.

Crisis management is one thing, but how do you permanently lower the temperature so your teams can recover sustainably? Companies around the world are now taking larger steps to curb burnout, with industry leaders like LinkedIn, Hootsuite and Bumble shutting down their offices for a full week to allow all employees extra time off. The CEO of Okta, worried about burnout, asked all employees to email him their vacation plans in 2021.

Keep Reading Show less
Stella Garber
Stella Garber is Trello's Head of Marketing. Stella has led Marketing at Trello for the last seven years from early stage startup all the way through its acquisition by Atlassian in 2017 and beyond. Stella was an early champion of remote work, having led remote teams for the last decade plus.

It’s soul-destroying and it uses DRM, therefore Peloton is tech

"I mean, the pedals go around if you turn off all the tech, but Peloton isn't selling a pedaling product."

Is this tech? Or is it just a bike with a screen?

Image: Peloton and Protocol

One of the breakout hits from the pandemic, besides Taylor Swift's "Folklore," has been Peloton. With upwards of 5.4 million members as of March and nearly $1.3 billion in revenue that quarter, a lot of people are turning in their gym memberships for a bike or a treadmill and a slick-looking app.

But here at Protocol, it's that slick-looking app, plus all the tech that goes into it, that matters. And that's where things got really heated during our chat this week. Is Peloton tech? Or is it just a bike with a giant tablet on it? Can all bikes be tech with a little elbow grease?

Keep Reading Show less
Karyne Levy

Karyne Levy ( @karynelevy) is the West Coast editor at Protocol. Before joining Protocol, Karyne was a senior producer at Scribd, helping to create the original content program. Prior to that she was an assigning editor at NerdWallet, a senior tech editor at Business Insider, and the assistant managing editor at CNET, where she also hosted Rumor Has It for CNET TV. She lives outside San Francisco with her wife, son and lots of pets.

Protocol | Workplace

In Silicon Valley, it’s February 2020 all over again

"We'll reopen when it's right, but right now the world is changing too much."

Tech companies are handling the delta variant in differing ways.

Photo: alvarez/Getty Images

It's still 2021, right? Because frankly, it's starting to feel like March 2020 all over again.

Google, Apple, Uber and Lyft have now all told employees they won't have to come back to the office before October as COVID-19 case counts continue to tick back up. Facebook, Google and Uber are now requiring workers to get vaccinated before coming to the office, and Twitter — also requiring vaccines — went so far as to shut down its reopened offices on Wednesday, and put future office reopenings on hold.

Keep Reading Show less
Allison Levitsky
Allison Levitsky is a reporter at Protocol covering workplace issues in tech. She previously covered big tech companies and the tech workforce for the Silicon Valley Business Journal. Allison grew up in the Bay Area and graduated from UC Berkeley.
Protocol | China

Livestreaming ecommerce next battleground for China’s nationalists

Vendors for Nike and even Chinese brands were harassed for not donating enough to Henan.

Nationalists were trolling in the comment sections of livestream sessions selling products by Li-Ning, Adidas and other brands.

Collage: Weibo, Bilibili

The No. 1 rule of sales: Don't praise your competitor's product. Rule No. 2: When you are put to a loyalty test by nationalist trolls, forget the first rule.

While China continues to respond to the catastrophic flooding that has killed 99 and displaced 1.4 million people in the central province of Henan, a large group of trolls was busy doing something else: harassing ordinary sportswear sellers on China's livestream ecommerce platforms. Why? Because they determined that the brands being sold had donated too little, or too late, to the people impacted by floods.

Keep Reading Show less
Zeyi Yang
Zeyi Yang is a reporter with Protocol | China. Previously, he worked as a reporting fellow for the digital magazine Rest of World, covering the intersection of technology and culture in China and neighboring countries. He has also contributed to the South China Morning Post, Nikkei Asia, Columbia Journalism Review, among other publications. In his spare time, Zeyi co-founded a Mandarin podcast that tells LGBTQ stories in China. He has been playing Pokemon for 14 years and has a weird favorite pick.
Latest Stories