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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."

Power

Google wants to help you get a life

Digital car windows, curved AR glasses, automatic presentations and other patents from Big Tech.

A new patent from Google offers a few suggestions.

Image: USPTO

Another week has come to pass, meaning it's time again for Big Tech patents! You've hopefully been busy reading all the new Manual Series stories that have come out this week and are now looking forward to hearing what comes after what comes next. Google wants to get rid of your double-chin selfie videos and find things for you as you sit bored at home; Apple wants to bring translucent displays to car windows; and Microsoft is exploring how much you can stress out a virtual assistant.

And remember: The big tech companies file all kinds of crazy patents for things, and though most never amount to anything, some end up defining the future.

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Mike Murphy

Mike Murphy ( @mcwm) is the director of special projects at Protocol, focusing on the industries being rapidly upended by technology and the companies disrupting incumbents. Previously, Mike was the technology editor at Quartz, where he frequently wrote on robotics, artificial intelligence, and consumer electronics.

Sponsored Content

The future of computing at the edge: an interview with Intel’s Tom Lantzsch

An interview with Tom Lantzsch, SVP and GM, Internet of Things Group at Intel

An interview with Tom Lantzsch

Senior Vice President and General Manager of the Internet of Things Group (IoT) at Intel Corporation

Edge computing had been on the rise in the last 18 months – and accelerated amid the need for new applications to solve challenges created by the Covid-19 pandemic. Tom Lantzsch, Senior Vice President and General Manager of the Internet of Things Group (IoT) at Intel Corp., thinks there are more innovations to come – and wants technology leaders to think equally about data and the algorithms as critical differentiators.

In his role at Intel, Lantzsch leads the worldwide group of solutions architects across IoT market segments, including retail, banking, hospitality, education, industrial, transportation, smart cities and healthcare. And he's seen first-hand how artificial intelligence run at the edge can have a big impact on customers' success.

Protocol sat down with Lantzsch to talk about the challenges faced by companies seeking to move from the cloud to the edge; some of the surprising ways that Intel has found to help customers and the next big breakthrough in this space.

What are the biggest trends you are seeing with edge computing and IoT?

A few years ago, there was a notion that the edge was going to be a simplistic model, where we were going to have everything connected up into the cloud and all the compute was going to happen in the cloud. At Intel, we had a bit of a contrarian view. We thought much of the interesting compute was going to happen closer to where data was created. And we believed, at that time, that camera technology was going to be the driving force – that just the sheer amount of content that was created would be overwhelming to ship to the cloud – so we'd have to do compute at the edge. A few years later – that hypothesis is in action and we're seeing edge compute happen in a big way.

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Saul Hudson
Saul Hudson has a deep knowledge of creating brand voice identity, especially in understanding and targeting messages in cutting-edge technologies. He enjoys commissioning, editing, writing, and business development, in helping companies to build passionate audiences and accelerate their growth. Hudson has reported from more than 30 countries, from war zones to boardrooms to presidential palaces. He has led multinational, multi-lingual teams and managed operations for hundreds of journalists. Hudson is a Managing Partner at Angle42, a strategic communications consultancy.
Transforming 2021

Truveta’s plan to make health AI that actually works

Former Microsoft executive Terry Myerson's new health data venture aims to apply big data to patient care with "an alliance of health systems."

Former Windows chief Terry Myerson on the move to AI in medicine.

Photo: Truveta

If health AI were a patient at a hospital, its chart up to this point wouldn't look too promising.

Its symptoms are long-standing and chronic: a lack of interoperability, a dearth of equitable data sets and a difficult-to-navigate relationship with patient privacy. And the specialists that have taken a crack at treating it — Big Tech, insurance giants, AI and cloud companies — have largely come up short with patient-care tools that have broad utility across the medical field.

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Kevin McAllister

Kevin McAllister ( @k__mcallister) is an associate editor at Protocol, leading the development of Braintrust. Prior to joining the team, he was a rankings data reporter at The Wall Street Journal, where he oversaw structured data projects for the Journal's strategy team.

Transforming 2021

Blockchain, QR codes and your phone: the race to build vaccine passports

Digital verification systems could give people the freedom to work and travel. Here's how they could actually happen.

One day, you might not need to carry that physical passport around, either.

Photo: CommonPass

There will come a time, hopefully in the near future, when you'll feel comfortable getting on a plane again. You might even stop at the lounge at the airport, head to the regional office when you land and maybe even see a concert that evening. This seemingly distant reality will depend upon vaccine rollouts continuing on schedule, an open-sourced digital verification system and, amazingly, the blockchain.

Several countries around the world have begun to prepare for what comes after vaccinations. Swaths of the population will be vaccinated before others, but that hasn't stopped industries decimated by the pandemic from pioneering ways to get some people back to work and play. One of the most promising efforts is the idea of a "vaccine passport," which would allow individuals to show proof that they've been vaccinated against COVID-19 in a way that could be verified by businesses to allow them to travel, work or relax in public without a great fear of spreading the virus.

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Mike Murphy

Mike Murphy ( @mcwm) is the director of special projects at Protocol, focusing on the industries being rapidly upended by technology and the companies disrupting incumbents. Previously, Mike was the technology editor at Quartz, where he frequently wrote on robotics, artificial intelligence, and consumer electronics.

People

Citizen’s plan to keep people safe (and beat COVID-19) with an app

Citizen CEO Andrew Frame talks privacy, safety, coronavirus and the future of the neighborhood watch.

Citizen added COVID-19 tracking to its app over the summer — but its bigger plans got derailed.

Photo: Citizen

Citizen is an app built on the idea that transparency is a good thing. It's the place users — more than 7 million of them, in 28 cities with many more to come soon — can find out when there's a crime, a protest or an incident of any kind nearby. (Just yesterday, it alerted me, along with 17,900 residents of Washington, D.C., that it was about to get very windy. It did indeed get windy.) Users can stream or upload video of what's going on, locals can chat about the latest incidents and everyone's a little safer at the end of the day knowing what's happening in their city.

At least, that's how CEO Andrew Frame sees it. Critics of Citizen say the app is creating hordes of voyeurs, incentivizing people to run into dangerous situations just to grab a video, and encouraging racial profiling and other problematic behaviors all under the guise of whatever "safety" means. They say the app promotes paranoia, alerting users to things that they don't actually need to know about. (That the app was originally called "Vigilante" doesn't help its case.)

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David Pierce

David Pierce ( @pierce) is Protocol's editor at large. Prior to joining Protocol, he was a columnist at The Wall Street Journal, a senior writer with Wired, and deputy editor at The Verge. He owns all the phones.

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