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        COVID + AI: The Road Ahead

Session I: The Economic Road out of COVID

Abigail Wozniak

Large-scale National Surveys of Covid and its Impacts

What should employers and workers expect if workplace COVID symptom screening becomes widespread? Wozniak uses data from the COVID Impact Survey to assess the potential impact of such screens on daily workplace attendance. The data suggest that 3-4% or more of the workforce could be screened to stay home on a daily basis. Policy to encourage compliance with self-monitoring will be needed to support workers and firms through the full course of the pandemic. 
 

Lisa Kahn

Using Vacancy Postings to Assess Labor Demand During the COVID-19 Pandemic

We use job vacancy data collected in real time by Burning Glass Technologies, as well as initial unemployment insurance (UI) claims data to study the impact of COVID-19 on the labor market. Our data allow us to the economy in real time at disaggregated geography and by detailed occupation and industry. We find that job vacancies collapsed in the second half of March and fell by 35% in late April. To a first approximation, this collapse was broad based, hitting all U.S. states, regardless of the intensity of the initial virus spread or timing of stay-at-home policies. UI claims also largely match these patterns. Nearly all industries and occupations saw contraction in postings and spikes in UI claims, with little difference depending on whether they are deemed essential and whether they have work-from-home capability. The only major exceptions are in essential retail and nursing, the "front line" jobs most in-demand during the current crisis. This set of facts suggests the current damage is not caused solely by the stay-at-home orders, and is therefore unlikely to be undone simply by lifting them. Indeed, early data on states reopening shows little difference in postings rebound.

https://www.nber.org/papers/w27061

Session II: Humanity’s Road out of COVID 

Danielle Allen

Prerequisites for Effective COVID Responses 

An effective covid response requires a clear decision about our overarching goals. Should we merely act therapeutically, treating patients? Should we mitigate the disease? Or should we even try to suppress the disease? How do the different possible objectives intersect with economic objectives? With the need for liberty protections? The goal is to find the policy pathway that integrates our overarching aims. This can be done.

Session III: The Medical Road out of COVID

Session III is Eligible for Stanford Continuing Medical Education Credits. Learn more. 

Susan Athey

New Models for Financing Vaccine Trials 

Most therapeutics aim to improve human health. A vaccine for COVID-19 would not just save lives, but also improve the health of the economy by reducing the costs of the other actions and policies, such as social distancing and lockdowns, that people and governments have imposed in order to protect human health. The IMF estimates that the responses to COVID-19 will reduce global output by $9 trillion over 2020-2021 or $375 billion a month. When the pandemic’s harm is counted in billions of dollars per month, the social benefit from accelerating progress far outweighs the private benefits, and as a result policy makers can play an important role in creating the appropriate financing programs to align social and private incentives. Even after a vaccine has been shown to be safe and effective, substantial time and resources are required to develop and receive regulatory approval for the manufacturing process for each vaccine and each facility. We design a program to incentivize the accelerated creation of manufacturing capacity. Using data on over 100 vaccine candidates and their characteristics, we estimate  an optimal portfolio of vaccine candidates and capacity investment. We then design a mix of incentives, including cost reimbursement and pay-for-outcomes, to implement the optimal candidate portfolio and capacity investment. We identify a variety of potential coordination failures and institutional impediments that must be addressed to achieve society’s goals.

 

Eric Horvitz

Predictions, Outcomes, and Decisions: Leveraging Machine Learning in Strategy on COVID-19

Machine learning is being applied in numerous ways to address challenges with the COVID-19 pandemic. I will provide a brief overview of efforts to leverage predictive models to augment the decisions of care providers and discuss opportunities with developing models of risk in support of personal and public health decision making.  

Additional Resources

Racial and Ethnic Health Disparities Research in COVID-19

Yvonne Maldonado, MD, Senior Associate Dean for Faculty Development and Diversity, Chief of Pediatric Infectious Diseases, and Professor of Pediatrics and of Epidemiology and Population Health at Stanford Medicine, along with a panel of community experts discuss racial health disparities related to COVID-19 and COVID-19 research opportunities. 

COVID-19 Collaboration Opportunities

COVID-19 is having a substantial impact on our students and broader research community, such as job or internship offers that are being rescinded.  At the same time, many new research projects and collaborations are being launched to address the pandemic.  HAI would like to create a clearinghouse for COVID-19 research collaborations and other opportunities, such as RA positions, internships, or funding opportunities. Share your opportunities here.

COVID-19 and AI: Understanding, Tracking, and Responding to the Disease

Watch Stanford HAI’s first conference focused on COVID, from April 1, 2020, which focused on understanding the virus and its impact on society. Speakers and topics covered the infodemic that health crises create, biosecurity, country best practices at tracking and treating the illness, epidemiological forecasting tools, and identifying vaccine candidates and repurposing existing drugs using machine learning.

Privacy and Ethics Recommendations

The National Security Commission on Artificial Intelligence developed guidelines for computing applications created to mitigate COVID-19. Read the white paper by clicking on the link above.

Earn or Claim Stanford Continuing Medical Education Credits for COVID + AI: The Road Ahead, Session III 

Read More

After COVID: The Future of Work, Labor Markets, and Elections
Experts discuss the economic and social ramifications of COVID during a Stanford HAI conference.

Emerging Models to Track and Prevent COVID-19
Panelists during the COVID+AI conference tackle ways to speed the vaccine delivery market and understand infection rates.