Coronavirus testing in the United States is disorganized and needs coordination at the national level, infectious disease experts said in a new report released Wednesday.
Right now, testing is not accurate enough to use alone to make most decisions, including who should go back to work or to school, the team at the University of Minnesota said.
“It’s a mess out there,” Mike Osterholm, head of the university’s Center for Infectious Disease Research and Policy (CIDRAP), which issued the report, told CNN.
“Testing is very, very important, but we’re not doing the right testing.”
The coronavirus pandemic has taken a hit in the paychecks of close to half of U.S. households, the Census Bureau says.
Since March 13, 47% of adults say they — or another adult in their home — have lost employment income, while 39% say they’re expecting their households to earn less from work over the next four weeks.
With the first of the month coming in less than two weeks, more than a fifth of adults report they have just slight or no confidence in their ability to make their next rent or mortgage payment on time. [audio, 4:08]
A patchwork was inevitable, especially when a pandemic unfolds over a nation as large as the U.S. But the White House has intensified it by devolving responsibility to the states. There is some sense to that. American public health works at a local level, delivered by more than 3,000 departments that serve specific cities, counties, tribes, and states. This decentralized system is a strength: An epidemiologist in rural Minnesota knows the needs and vulnerabilities of her community better than a federal official in Washington, D.C.
But in a pandemic, the actions of 50 uncoordinated states will be less than the sum of their parts. Only the federal government has pockets deep enough to fund the extraordinary public-health effort now needed. Only it can coordinate the production of medical supplies to avoid local supply-chain choke points, and then ensure that said supplies are distributed according to need, rather than influence. Instead, Trump has repeatedly told governors to procure their own tests and medical supplies.
Los Angeles Times, Kaiser Health News, Ashley Gold
from
Dr. Albert Hsiao and his colleagues at the UC San Diego health system had been working for 18 months on an artificial intelligence program designed to help doctors identify pneumonia on a chest X-ray. When the coronavirus hit the United States, they decided to see what it could do.
The researchers quickly deployed their program, which dots X-ray images with spots of color where there may be lung damage or other signs of pneumonia. It has now been applied to more than 6,000 chest X-rays, and it’s providing some value in diagnosis, said Hsiao, the director of UCSD’s augmented imaging and artificial intelligence data analytics laboratory.
His team is one of several around the country that has pushed AI programs into the COVID-19 crisis to perform tasks like deciding which patients face the greatest risk of complications and which can be safely channeled into lower-intensity care.
Palantir, the data analytics company co-founded by Peter Thiel, is already an active tech player in the scrum for federal contracts, but it’s playing a new and increasingly prominent role in providing the government with software tools to address the COVID-19 crisis.
This month, the Department of Veterans Affairs awarded a new $5 million contract to Palantir through veteran-owned software reseller i3 Federal LLC, which lists Palantir as a partner. The contract, set to run through November, will provide the VA with Palantir’s Gotham software to “track and analyze COVID-19 outbreak areas and make timely decisions with insight into supply chain capacity, hospital inventory, social service utilization and lab diagnostics.”
Google and Alphabet CEO Sundar Pichai recently joined The Vergecast to talk about the challenges Google faces during this time, including a shift in its core ad business and the challenges of managing the company remotely. Pichai is himself adapting to remote work; he’s actively blocking out more time on his calendar to read and think, something he used to do during his commute. And he’s learning to make pizza from scratch by watching YouTube videos. [audio, 51:50]
In nature, bacteria use CRISPR as an adaptive immune system to protect themselves against viruses. Over the past decade, scientists have been able to successfully build upon that natural phenomenon with the discovery of CRISPR proteins found in bacteria — the most widely used of which is the Cas9 enzyme. In combination with a guide RNA, Cas9 is able to target, cut, and degrade specific DNA sequences.
With applications ranging from the treatment of genetic diseases to the nutritional potency of agricultural crops, CRISPR has emerged as one of the most promising tools for genome editing. Cas9 enzymes, however, rely on specific DNA ZIP codes to pinpoint where to cut and edit. The most widely-used Cas9 from Streptococcus pyogenes bacteria, SpCas9, requires two “G” nucleotides beside target sites. Less than 10 percent of DNA sequences meet this requirement.
In research published this month in both Nature Biotechnology and Nature Communications, a team of computational biologists in the Media Lab’s Molecular Machines group and the MIT Center for Bits and Atoms have successfully engineered new proteins with enhanced genome editing capabilities, significantly broadening the spectrum of DNA sequences that can be accurately and effectively accessed.
University of California System, Office of Scholarly Communication
from
The Advisory Council of the EarthArXiv preprint service for earth sciences is pleased to announce a partnership with the California Digital Library (CDL) that will support EarthArXiv’s mission, future growth, and long-term sustainability. Core to this partnership will be the transition of EarthArXiv’s preprints server – including public display and submission management – from the Center for Open Science to the eScholarship Publishing program at the CDL.
At the University of Toronto, Ted Sargent runs a test kitchen of sorts. His team, composed of researchers and students, develops recipes, measures and mixes ingredients carefully, and then evaluates the aftermath. The concoctions mostly—if not always—turn out to be inedible.
Fortunately, though, flavor is not the point. They’re not making food. Sargent’s team cooks with carbon dioxide. Their goal is to invent recipes to “upgrade” the greenhouse gas into useful materials, says Sargent, an electrical engineer. Instead of releasing the pollutant into the air, or capturing and sequestering it underground, factories and power plants of the future could use renewable energy to convert the carbon dioxide into raw materials they could sell.
One promising class of recipes involves electrically zapping carbon dioxide with other reactants to transform it into the six-atom molecule ethylene, composed of two carbon atoms and four hydrogens. Ethylene is a raw material used to make common plastics, including those found in supermarket and Ziploc bags. “It’s about a $60 billion market,” says Sargent. “It’s a pretty valuable commodity chemical.”
Before the Covid-19 pandemic, health data privacy wasn’t exactly a hot topic on Capitol Hill. By and large, lawmakers stuck to scolding tech giants like Google for getting their hands on patient data gathered by hospitals and smartphone apps.
But the digital tools being deployed to combat Covid-19 have thrust the issue into the spotlight, drawing fresh interest from federal lawmakers who have swiftly introduced several new bills aimed at protecting Americans’ health data related to the coronavirus.
While the issue is getting another look from lawmakers, it’s not clear whether a divided and distracted Congress will be able to reach a consensus on how best to regulate the vast amounts of data collected by digital contact tracing tools and other pandemic response efforts — or whether the bills are destined to fizzle before they ever come up for a vote.
PsyArXiv; Patrick Forscher Eric-Jan Wagenmakers Lisa DeBruine Nicholas Coles Miguel Silan Hans IJzerman
from
Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, we argue that these five problems share a common cause: insufficient investment of resources into the typical psychology study. We argue that team science is a possible solution to these problems because it allows large groups of scientists to pool their resources, allowing higher resource investments than would be possible by solo PIs. As long as the unique barriers and risks are properly recognized and managed, we believe team science has unique potential to spur progress in psychology and beyond.
The coronavirus has massively disrupted the food supply chain.
Before the crisis, over half of Americans’ food dollars was spent outside the home, at restaurants and other food service locations. But with that industry largely shuttered, many farmers have found themselves without a market for their crops, even as demand at grocery stores and food banks rises.
While farmers would like to sell their excess produce to grocery outlets or donate it to food banks, they’re up against an inflexible supply chain that is specialized for the end customer. Longstanding contracts between farmers, restaurants, schools and grocery stores determine how the crops will be packaged and processed. So it’s just not easy to find new markets and set up new distribution channels.
The New York Times will no longer use 3rd-party data to target ads come 2021, executives tell Axios, and it is building out a proprietary first-party data platform.
Why it matters: Third-party data, which is collected from consumers on other websites, is being phased out of the ad ecosystem because it’s not considered privacy-friendly.
Markedly different conclusions about brain scans reached by 70 independent teams highlight the challenges to data analysis in the modern era of mammoth datasets and highly flexible processing workflows.
The seed for Penn State’s Institute for Sustainable Agricultural, Food, and Environmental Science was planted well before the COVID-19 outbreak. The concept had been growing in the College of Agricultural Sciences for about two years when the pandemic emerged.
The aim of the institute — referred to as SAFES — is to convene expertise at Penn State to address complex, interconnected food-energy-water-land challenges, such as food security, supply chain disruptions, bioenergy production, biodiversity, changing land uses, environmental degradation and climate volatility. With the havoc wrought by the pandemic, these issues have emerged as urgently critical.
Online May 26, starting at 4 p.m. EDT. “How will this disruption to the progress of potentially lifesaving and world-changing efforts affect humanity? Can we build a safe, socially distant scientific infrastructure?” [registration required]
Online September 15-16. “Due to the coronavirus (COVID-19) pandemic, the International Conference Organisation Committee has decided to hold the Data for Policy 2020 meeting virtually replacing the physical meeting scheduled for 15-16 September 2020 in London. The committee has also decided to cancel pre-conference workshops for this year originally planned for 14 September 2020.” [registration required]
Online May 28, starting at 10 a.m. PDT. “Don’t miss our upcoming fireside chat on May 28th w/CTO, @chicagoben
and @wendiwhitmore
, Vice President of IBM X-Force, to discuss how COVID is impacting cybersecurity today and how teams can best prepare and prevail in the future.”
“To provide some insight into the difficulty of predicting the total effect of a pandemic, we have created two pandemic quizzes, in which you try to predict the number of people who eventualy become infected. Each quiz covers five pandemics. For each pandemic, you see the first two weeks of data – the number of infected, the number recovered, and the number of new cases. You have to predict the total number who will be infected if no interventions occur.”
“The TREC Fair Ranking track evaluates systems according to how well they fairly rank documents. We are currently working on the guidelines for the 2020 Fair Ranking task. The details will be announced on this website.”
During its Build 2020 developer conference, which takes place online this week, Microsoft announced the addition of new capabilities to Azure Machine Learning, its cloud-based environment for training, deploying, and managing AI models. WhiteNoise, a toolkit for differential privacy, is now available both through Azure and in open source on GitHub, joining new AI interpretability and fairness tools as well as new access controls for data, models, and experiments; new techniques for fine-grained traceability and lineage; new confidential machine learning products; and new workflow accountability documentation.
“There’s no playbook; there’s no manual,” explains Leigh Thompson, a professor of management and organization at Kellogg.
So Thompson, who has researched and written about virtual negotiation and collaboration, offered up a number of “hacks” to improve our online meetings during a recent webinar from Kellogg Executive Education. The talk was based on insights from her new book, Negotiating the Sweetspot: The Art of Leaving Nothing on the Table.
Most people agree that virtual meetings are highly efficient, but they lack a good deal of the spontaneity and creative energy of in-person meetings. So Thompson suggests building in time for that at the start of a gathering.
Researchers are rushing to pool resources and data sets to tackle the pandemic, but the new era of openness comes with concerns around privacy, ownership and ethics.
Apple and Google today made available the first public version of their exposure notification API, which was originally debuted as a joint contact-tracing software tool. The partners later renamed it the Exposure Notification system to more accurately reflect its functionality, which is designed to notify individuals of potential exposure to others who have confirmed cases of COVID-19, while preserving privacy around identifying info and location data.
The launch today means that public health agencies can now use the API in apps released to the general public. To date, Apple and Google have only released beta versions of the API to help with the development process.
As Murray points out, generally speaking, small group exercise classes will be the highest risk, especially if the class is indoors, simply because this brings you into closer contact with other people who are forcefully exhaling.
In a recent report, a single dance fitness workshop in South Korea, attended by instructors who went on to teach multiple classes while infectious, led to 112 infections. Transmission was thought to be increased due to multiple people in a small space, combined with the air flow of aerobic movement, meaning everyone was breathing each other’s contaminated air.