Federalism and Polycentric Government in a Pandemic


Paper by Victoria Perez and Justin M. Ross: “Networks of overlapping local governments are the front line of governmental responses to pandemics. Local governments, both general purpose (municipalities, counties, etc.) and special districts (school, fire, police, hospital, etc.), implement state and federal directives while acting as a producer and as a third-party payer in the healthcare system. They possess local information necessary in determining the best use of finite resources and available assets. Furthermore, a liberal society requires voluntary cooperation of citizens skeptical of opportunistic authoritarianism. Therefore, successful local governance instills a reassuring division of political power.

The COVID-19 pandemic has created two significant challenges for local governments in their efforts to respond effectively to the crisis: public finance and intergovernmental collaboration. This brief recommends practical solutions to meet these challenges….(More)”.

Casualties of a Pandemic: Truth, Trust and Transparency


Essay by Frank D. LoMonte at the Journal of Civic Information: “In an April 1 interview with NPR’s “Morning Edition,” retired U.S. Army Gen. Stanley A. McChrystal, former commander of U.S. forces in Iraq, explained that, in a crisis situation, accurate information from government authorities can be crucial in reassuring the public – and in the absence of accurate information, speculation and rumor will proliferate. Joni Mitchell, who’s probably never before appeared in the same paragraph with Stanley McChrystal, might have put it a touch more poetically: “Don’t it always seem to go; That you don’t know what you’ve got ’til it’s gone.”

The outbreak of the coronavirus strain COVID-19, which prompted the U.S. Department of Health and Human Services to declare a public health emergency on Jan. 31, 2020,3 is introducing Americans to a newfound world of austerity and loss. Professional haircuts, sit-down restaurant meals and recreational plane flights increasingly seem like memories from a bygone golden age (small inconveniences, to be sure, alongside the suffering of thousands who’ve died and the families they’ve left behind).

Access to information from government agencies, too, is adapting to a mail-order, drive-through society. As public-health authorities reached consensus that the spread of COVID-19 could be contained only by eliminating non-essential travel and group gatherings, strict adherence to open-meeting and public-records laws became a casualty alongside salad bars and theme-park rides. Governors and legislatures relaxed, or entirely waived, compliance with statutes that require agencies to open their meetings to in-person public attendance and promptly fulfill requests for documents.

As with all other areas of public life, some sacrifices in open-government formalities are unavoidable. With agencies down to a sustenance-level crew of essential workers, it’s unrealistic to expect that decades-old paper documents will be speedily located and produced. And it’s unsafe to invite people to congregate at public hearings to address their elected officials. But the public shouldn’t be alone in the sacrifice….(More)”.

How Facebook and Google are helping the CDC forecast coronavirus


Karen Hao at MIT Technology Review: “When it comes to predicting the spread of an infectious disease, it’s crucial to understand what Ryan Tibshirani, an associate professor at Carnegie Mellon University, calls the “the pyramid of severity.” The bottom of the pyramid is asymptomatic carriers (those who have the infection but feel fine); the next level is symptomatic carriers (those who are feeling ill); then come hospitalizations, critical hospitalizations, and finally deaths.

Every level of the pyramid has a clear relationship to the next: “For example, sadly, it’s pretty predictable how many people will die once you know how many people are under critical care,” says Tibshirani, who is part of CMU’s Delphi research group, one of the best flu-forecasting teams in the US. The goal, therefore, is to have a clear measure of the lower levels of the pyramid, as the foundation for forecasting the higher ones.

But in the US, building such a model is a Herculean task. A lack of testing makes it impossible to assess the number of asymptomatic carriers. The results also don’t accurately reflect how many symptomatic carriers there are. Different counties have different testing requirements—some choosing only to test patients who require hospitalization. Test results also often take upwards of a week to return.

The remaining option is to measure symptomatic carriers through a large-scale, self-reported survey. But such an initiative won’t work unless it covers a big enough cross section of the entire population. Now the Delphi group, which has been working with the Centers for Disease Control and Prevention to help it coordinate the national pandemic response, has turned to the largest platforms in the US: Facebook and Google.

Facebook will help CMU Delphi research group gather data about Covid symptoms

In a new partnership with Delphi, both tech giants have agreed to help gather data from those who voluntarily choose to report whether they’re experiencing covid-like symptoms. Facebook will target a fraction of their US users with a CMU-run survey, while Google has thus far been using its Opinion Rewards app, which lets users respond to questions for app store credit. The hope is this new information will allow the lab to produce county-by-county projections that will help policymakers allocate resources more effectively.

Neither company will ever actually see the survey results; they’re merely pointing users to the questions administered and processed by the lab. The lab will also never share any of the raw data back to either company. Still, the agreements represent a major deviation from typical data-sharing practices, which could raise privacy concerns. “If this wasn’t a pandemic, I don’t know that companies would want to take the risk of being associated with or asking directly for such a personal piece of information as health,” Tibshirani says.

Without such cooperation, the researchers would’ve been hard pressed to find the data anywhere else. Several other apps allow users to self-report symptoms, including a popular one in the UK known as the Covid Symptom Tracker that has been downloaded over 1.5 million times. But none of them offer the same systematic and expansive coverage as a Facebook or Google-administered survey, says Tibshirani. He hopes the project will collect millions of responses each week….(More)”.

A guide to healthy skepticism of artificial intelligence and coronavirus


Alex Engler at Brookings: “The COVID-19 outbreak has spurred considerable news coverage about the ways artificial intelligence (AI) can combat the pandemic’s spread. Unfortunately, much of it has failed to be appropriately skeptical about the claims of AI’s value. Like many tools, AI has a role to play, but its effect on the outbreak is probably small. While this may change in the future, technologies like data reporting, telemedicine, and conventional diagnostic tools are currently far more impactful than AI.

Still, various news articles have dramatized the role AI is playing in the pandemic by overstating what tasks it can perform, inflating its effectiveness and scale, neglecting the level of human involvement, and being careless in consideration of related risks. In fact, the COVID-19 AI-hype has been diverse enough to cover the greatest hits of exaggerated claims around AI. And so, framed around examples from the COVID-19 outbreak, here are eight considerations for a skeptic’s approach to AI claims….(More)”.

The 9/11 Playbook for Protecting Privacy


Adam Klein and Edward Felten at Politico: “Geolocation data—precise GPS coordinates or records of proximity to other devices, often collected by smartphone apps—is emerging as a critical tool for tracking potential spread. But other, more novel types of surveillance are already being contemplated for this first pandemic of the digital age. Body temperature readings from internet-connected thermometers are already being used at scale, but there are more exotic possibilities. Could smart-home devices be used to identify coughs of a timbre associated with Covid-19? Can facial recognition and remote temperature sensing be harnessed to identify likely carriers at a distance?

Weigh the benefits of each collection and use of data against the risks.

Each scenario will present a different level of privacy sensitivity, different collection mechanisms, different technical options affecting privacy, and varying potential value to health professionals, meaning there is no substitute for case-by-case judgment about whether the benefits of a particular use of data outweighs the risks.

The various ways to use location data, for example, present vastly different levels of concern for privacy. Aggregated location data, which combines many individualized location trails to show broader trends, is possible with few privacy risks, using methods that ensure no individual’s location trail is reconstructable from released data. For that reason, governments should not seek individualized location trails for any application where aggregated data would suffice—for example, analyzing travel trends to predict future epidemic hotspots.

If authorities need to trace the movements of identifiable people, their location trails should be obtained on the basis of an individualized showing. Gathering from companies the location trails for all users—as the Israeli government does, according to news reports—would raise far greater privacy concerns.

Establish clear rules for how data can be used, retained, and shared.

Once data is collected, the focus shifts to what the government can do with it. In counterterrorism programs, detailed rules seek to reduce the effect on individual privacy by limiting how different types of data can be used, stored, and shared.

The most basic safeguard is deleting data when it is no longer needed. Keeping data longer than needed unnecessarily exposes it to data breaches, leaks, and other potential privacy harms. Any individualized location tracking should cease, and the data should be deleted, once the individual no longer presents a danger to public health.

Poland’s new tracking app for those exposed to the coronavirus illustrates why reasonable limits are essential. The Polish government plans to retain location data collected by the app for six years. It is hard to see a public-health justification for keeping the data that long. But the story also illustrates well how a failure to consider users’ privacy can undermine a program’s efficacy: the app’s onerous terms led at least one Polish citizen to refuse to download it….(More)”.

The War on Coronavirus Is Also a War on Paperwork


Article by Cass Sunstein: “As part of the war on coronavirus, U.S. regulators are taking aggressive steps against “sludge” – paperwork burdens and bureaucratic obstacles. This new battle front is aimed at eliminating frictions, or administrative barriers, that have been badly hurting doctors, nurses, hospitals, patients, and beneficiaries of essential public and private programs. 

Increasingly used in behavioral science, the term sludge refers to everything from form-filling requirements to time spent waiting in line to rules mandating in-person interviews imposed by both private and public sectors. Sometimes those burdens are justified – as, for example, when the Social Security Administration takes steps to ensure that those who receive benefits actually qualify for them. But far too often, sludge is imposed with little thought about its potentially devastating impact.

The coronavirus pandemic is concentrating the bureaucratic mind – and leading to impressive and brisk reforms. Consider a few examples. 

Under the Supplemental Nutrition Assistance Program (formerly known as food stamps), would-be beneficiaries have had to complete interviews before they are approved for benefits. In late March, the Department of Agriculture waived that requirement – and now gives states “blanket approval” to give out benefits to people who are entitled to them.

Early last week, the Internal Revenue Service announced that in order to qualify for payments under the Families First Coronavirus Response Act, people would have to file tax returns – even if they are Social Security recipients who typically don’t do that. The sludge would have ensured that many people never got money to which they were legally entitled. Under public pressure, the Department of Treasury reversed course – and said that Social Security recipients would receive the money automatically.

Some of the most aggressive sludge reduction efforts have come from the Department of Health and Human Services. Paperwork, reporting and auditing requirements are being eliminated. Importantly, dozens of medical services can now be provided through “telehealth.” 

In the department’s own words, the government “is allowing telehealth to fulfill many face-to-face visit requirements for clinicians to see their patients in inpatient rehabilitation facilities, hospice and home health.” 

In addition, Medicare will now pay laboratory technicians to travel to people’s homes to collect specimens for testing – thus eliminating the need for people to travel to health-care facilities for tests (and risk exposure to themselves or others). There are many other examples….(More)”.

Synthetic data offers advanced privacy for the Census Bureau, business


Kate Kaye at IAPP: “In the early 2000s, internet accessibility made risks of exposing individuals from population demographic data more likely than ever. So, the U.S. Census Bureau turned to an emerging privacy approach: synthetic data.

Some argue the algorithmic techniques used to develop privacy-secure synthetic datasets go beyond traditional deidentification methods. Today, along with the Census Bureau, clinical researchers, autonomous vehicle system developers and banks use these fake datasets that mimic statistically valid data.

In many cases, synthetic data is built from existing data by filtering it through machine learning models. Real data representing real individuals flows in, and fake data mimicking individuals with corresponding characteristics flows out.

When data scientists at the Census Bureau began exploring synthetic data methods, adoption of the internet had made deidentified, open-source data on U.S. residents, their households and businesses more accessible than in the past.

Especially concerning, census-block-level information was now widely available. Because in rural areas, a census block could represent data associated with as few as one house, simply stripping names, addresses and phone numbers from that information might not be enough to prevent exposure of individuals.

“There was pretty widespread angst” among statisticians, said John Abowd, the bureau’s associate director for research and methodology and chief scientist. The hand-wringing led to a “gradual awakening” that prompted the agency to begin developing synthetic data methods, he said.

Synthetic data built from the real data preserves privacy while providing information that is still relevant for research purposes, Abowd said: “The basic idea is to try to get a model that accurately produces an image of the confidential data.”

The plan for the 2020 census is to produce a synthetic image of that original data. The bureau also produces On the Map, a web-based mapping and reporting application that provides synthetic data showing where workers are employed and where they live along with reports on age, earnings, industry distributions, race, ethnicity, educational attainment and sex.

Of course, the real census data is still locked away, too, Abowd said: “We have a copy and the national archives have a copy of the confidential microdata.”…(More)”.

Experts warn of privacy risk as US uses GPS to fight coronavirus spread


Alex Hern at The Guardian: “A transatlantic divide on how to use location data to fight coronavirus risks highlights the lack of safeguards for Americans’ personal data, academics and data scientists have warned.

The US Centers for Disease Control and Prevention (CDC) has turned to data provided by the mobile advertising industry to analyse population movements in the midst of the pandemic.

Owing to a lack of systematic privacy protections in the US, data collected by advertising companies is often extremely detailed: companies with access to GPS location data, such as weather apps or some e-commerce sites, have been known to sell that data on for ad targeting purposes. That data provides much more granular information on the location and movement of individuals than the mobile network data received by the UK government from carriers including O2 and BT.

While both datasets track individuals at the collection level, GPS data is accurate to within five metres, according to Yves-Alexandre de Montjoye, a data scientist at Imperial College, while mobile network data is accurate to 0.1km² in city centres and much less in less dense areas – the difference between locating an individual to their street and to a specific room in their home…

But, warns de Montjoye, such data is never truly anonymous. “The original data is pseudonymised, yet it is quite easy to reidentify someone. Knowing where someone was is enough to reidentify them 95% of the time, using mobile phone data. So there’s the privacy concern: you need to process the pseudonymised data, but the pseudonymised data can be reidentified. Most of the time, if done properly, the aggregates are aggregated, and cannot be de-anonymised.”

The data scientist points to successful attempts to use location data in tracking outbreaks of malaria in Kenya or dengue in Pakistan as proof that location data has use in these situations, but warns that trust will be hurt if data collected for modelling purposes is then “surreptitiously used to crack down on individuals not respecting quarantines or kept and used for unrelated purposes”….(More)”.

Privacy Protection Key for Using Patient Data to Develop AI Tools


Article by  Jessica Kent: “Clinical data should be treated as a public good when used for research or artificial intelligence algorithm development, so long as patients’ privacy is protected, according to a report from the Radiological Society of North America (RSNA).

As artificial intelligence and machine learning are increasingly applied to medical imaging, bringing the potential for streamlined analysis and faster diagnoses, the industry still lacks a broad consensus on an ethical framework for sharing this data.

“Now that we have electronic access to clinical data and the data processing tools, we can dramatically accelerate our ability to gain understanding and develop new applications that can benefit patients and populations,” said study lead author David B. Larson, MD, MBA, from the Stanford University School of Medicine. “But unsettled questions regarding the ethical use of the data often preclude the sharing of that information.”

To offer solutions around data sharing for AI development, RSNA developed a framework that highlights how to ethically use patient data for secondary purposes.

“Medical data, which are simply recorded observations, are acquired for the purposes of providing patient care,” Larson said….(More)”

Unpredictable Residency during the COVID-19 Pandemic Spells Trouble for the 2020 Census Count


Blog by Diana Elliott and Robert Santos: “Social distancing measures to curtail the community spread of COVID-19 have upended daily life. Just before lockdowns were implemented across the country, there was tremendous movement and migration of people relocating to different residences to shelter in place. This makes sense for the people involved but could be disastrous for the communities they fled and the final 2020 Census counts.

Pandemic-based migration undermines an accurate count

The 2020 Census, like most data collected by the US Census Bureau, is residence based. In the years leading up to 2020, the US Census Bureau worked diligently on the quality of the Master Address File, or the catalog of all residential addresses in the country. Staff account for newly built housing developments and buildings, apartment units or accessory dwelling units that are used as permanent residences, and the demolition of homes and apartments in the past decade. Census materials are sent to an address, rather than a person.

Most residences across America have already received their 2020 Census invitation. Whether completed online, by paper, by phone, or in person, the first official question on the 2020 Census questionnaire is “How many people were living or staying in this house, apartment, or mobile home on April 1, 2020?” Households are expected to answer this based on the concept of “usual residence,” or the place where a person lives and sleeps most of the time.

Despite written guidance provided on the 2020 Census on how to answer this question, doing so may be wrought with complexities and nuance from the pandemic.

First, research reveals that respondents do not often read questionnaire instructions; they dive in and start answering. With many people scrambling to other counties, cities, and states to hunker down for the long haul with loved ones, this will lead to incorrect counts when people are counted at temporary addresses.

Second, for many, the concept of “usual residence” has little relevance in the uncertainty unfolding during the COVID-19 pandemic. What if your temporary address becomes your permanent address? What does “usual residence” mean during a global epidemic that could stretch for 18 months or more? And perhaps more importantly, what should it mean?

Finally, there is the added complication of census operational delays (PDF). Self-response to the 2020 Census has been extended into August, as have the nonresponse follow-up efforts, when enumerators knock on the doors of those who haven’t yet answered the census. Additional delays seem unavoidable. The longer the delay, the more time there is for people who have not yet completed a census form to realize their temporary plan has evolved into a state of permanence….(More)”.