A team of SHP faculty and researchers, together with Stanford Medicine graduate and medical students and in collaboration with colleagues at CIDE in Mexico, have launched a modeling framework to investigate the epidemiology of COVID-19 and to support pro-active resource planning and policy evaluations for diverse populations and geographies — including California, Mexico and India.

The Stanford-CIDE Coronavirus Simulation Model — or SC-COSMO — incorporates realistic demography and patterns of contacts sufficient for transmission of the virus that has infected more than 2 million people worldwide and claimed more than 125,600 lives, according to the widely used Johns Hopkins COVID-19 map which is updated several times a day.

The SC-COSMO model also incorporates non-pharmaceutical interventions, such as social distancing, timing and effects on reductions in contacts which may differ by demography.

Jeremy Goldhaber-Fiebert, an associate professor of medicine at Stanford Health Policy, is the principal investigator of the project, along with Fernando Alarid-Escudero, an assistant professor at the Center for Research and Teaching in Economics (CIDE) in Mexico and Jason Andrews, an assistant professor of medicine (infectious diseases) at Stanford Medicine. Other SHP faculty among the 20 investigators and staff members who are working on the project are Joshua Salomon and David Studdert, both professors of medicine.

The SC-COSMO team is a multi-disciplinary, multi-institutional team including expertise and experience in infectious disease, epidemiology, mathematical modeling and simulation, statistics, decision science, health policy, health law and health economics.

“As COVID-19 transmission occurs throughout the world’s diverse populations, it is critical to efficiently model and forecast its future spread between and within these populations and to appropriately reflect uncertainty in modeled outcomes,” Goldhaber-Fiebert said. “Doing so supports timely resource planning and decision making between potentially appropriate and effective interventions that balance the trade-offs they embody.”

The team is currently working on three projects:

1. The researchers are providing California with county-level COVID-19 estimates for such things as the number of infections, detected cases and projections of future needs for hospital and ICU beds, personal protective equipment (PPE) and ventilators.
2. The project is working on potential strategies to mitigate the COVID-19 pandemic in Mexico by focusing on three specific objectives: collecting, synthesizing and openly sharing the most relevant and useful data; accelerating the development of the SC-COSMO model and its adaptation to the Mexican situation; and identifying a set of mitigation strategies, comparing the health and economic consequences in the population in the medium and long term.
3. They are developing forecast models of the COVID-19 epidemic in India with the Wadhwani Institute of Artificial Intelligence and its Indian government partners, providing a rapid response to urgent needs for planning and resource allocation.

Half of the medical students in the United States are women, as are two-thirds of the health-care workers taking care of patients in hospitals, clinics and residential communities.

And the majority of the nurses on the frontlines of the COVID-19 pandemic? Women.

Yet gender bias and workplace harassment continue to plague women who have dedicated their careers to taking care of others.

A classic example given by Michelle Mello in a Perspective published in this week’s New England Journal of Medicine goes like this: A female attending physician and a male resident respond to a call to the emergency department. The ED staff direct questions about medical decisions to the man, addressing the logistics to the woman.

“The resident looks awkwardly at the attending but says nothing,” Mello writes. “Gesturing at the attending, the patient says he hopes `the hot new nurse is going to be mine.’ Everyone ignores the comment.”

Sexual harassment and gender bias remain highly prevalent in medicine, ranging from the banal comments by the patient in the scenario above to aggressive misconduct that can damage female health professionals’ well-being, careers and quality of care.

Healthcare organizations have formal processes in place to respond to complaints of workplace discrimination, but these processes “are insufficient to transform cultures,” writes Mello, a professor of medicine with Stanford Health Policy and a professor of law with Stanford Law, and her co-author Reshma Jagsi, director of the Center for Bioethics and Social Sciences at the University of Michigan.

Health-care professionals of both genders must speak up.

“We believe health professionals have a moral duty to practice `upstanding’ — intervening as bystanders — in response to sexual harassment and general bias and that this obligation should be described in codes of medical professional ethics and supported within institutional training,” the authors write.

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While many medical professional societies now mention sexual harassment in their ethical codes, these guidelines fall short in that they do not encourage professionals to respond to the behaviors and intervene when they become aware of discrimination or harassment. The only large specialty society whose guidelines contain “aspirational advice” to stop sexual harassment in its tracks is the American Association of Orthopaedic Surgeons.

The American Medical Association (AMA) Code of Ethics Opinion 9.1.3 requires only that physicians “promote and adhere to strict sexual harassment policies in medical workplaces.” Mello and Jagsi note a striking contrast to the AMA’s approach to physicians who appear to be impaired (for example, due to substance use or mental health problems): Opinion 9.3.2. requires that physicians “intervene in a timely manner” to ensure that impaired colleagues stop practicing and get help.

“Absent stronger exhortation from within the profession, the norm will continue to be that clinicians are lauded when they stand up to harassment or bias but do not feel obligated — and they are not trained and equipped — to do so,” the authors write.

They recommend formal training in bystander intervention and peer-to-peer coaching, using tip sheets describing various courses of action, like this one adapted from Mary Rowe, an adjunct professor of negotiation and management at MIT Sloan.

(This is excerpted from a story from The Mercury News.)

Long motorcades of volunteers converged at three Stanford University research sites this week, donating blood for a new test that identifies the prevalence of coronavirus in our community – and could help reveal the full scope of Santa Clara County’s epidemic.

The 2,500 test slots on Friday and Saturday filled up within hours, as news of the project — the first large scale study of its type in the U.S. — spread quickly through the county, according to this Mercury News story.

The test detects protective antibodies to the virus rather than the virus itself. This gives scientists a snapshot of how many people in the county have already been infected, but weren’t seriously sick and didn’t realize it. And it tells residents whether they carry potentially protective antibodies – so may be immune to future infection.

“This is critical information,” said principal investigator Eran Bendavid, an infectious disease specialist and associate professor of medicine with Stanford Health Policy. “We will show the country what to do and how to do it,” he said.

The project, coordinated with the Santa Clara County Department of Health, was applauded by Gov. Gavin Newsom during a Saturday press conference in Sacramento, who called it “the first home-grown serum test in the state of California.”

Read The Mercury News Story

Stanford Health Policy's Eran Bendavid and Jay Bhattacharya write in this Wall Street Journal editorial that current estimates about the COVID-19 fatality rate may be too high by orders of magnitude.

"If it’s true that the novel coronavirus would kill millions without shelter-in-place orders and quarantines, then the extraordinary measures being carried out in cities and states around the country are surely justified. But there’s little evidence to confirm that premise—and projections of the death toll could plausibly be orders of magnitude too high.

"Fear of Covid-19 is based on its high estimated case fatality rate — 2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, 2 million to 4 million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases."

"The latter rate is misleading because of selection bias in testing. The degree of bias is uncertainbecause available data are limited. But it could make the difference between an epidemic that kills 20,000 and one that kills 2 million. If the number of actual infections is much larger than the number of cases—orders of magnitude larger—then the true fatality rate is much lower as well. That’s not only plausible but likely based on what we know so far."

Read the Editorial 

As the deaths and detected cases from the COVID-19 epidemic continue to rise globally, government planners and policymakers require projections of its future course and impacts. They also need to understand how potential interventions might “flatten the curve.”

“It’s important to understand these overall effects by geographic area, demographic group, and for special populations like health-care workers,” says Stanford Health Policy’s Jeremy Goldhaber-Fiebert, who will be teaching a new class in the spring on infectious disease modeling with Stanford Medicine’s Jason Andrews. “Doing this requires mathematical models that incorporate the best available clinical, epidemiological, and policy data along with their associated uncertainties — the state-of-the-art of infectious disease modeling.”

Goldhaber-Fiebert and Andrews will debut the new course, Models for Understanding and Controlling Global Infectious Diseases (HUMBIO 154D for undergrads and HRP204 for graduate students) in the upcoming spring quarter. Stanford Provost Persis Drell announced last week that all spring courses at the university will now be taught online and pushed the start of the new quarter April 6.

Andrews is an infectious disease physician and assistant professor of medicine and Goldhaber-Fiebert, an associate professor of medicine, is a decision scientist.

The class will enable students to become critical consumers of studies using infectious disease modeling and to learn the building blocks for constructing infectious disease models themselves.

Despite the course being new and listed in the middle of winter quarter, they have seen enrollment rise from eight — prior to the rise of COVID-19 in the U.S. and its direct impacts on Stanford’s operations — to nearly 30 students as of March 22.

“Together Jason and I are leading one of several efforts on COVID-19 modeling here in Stanford,” said Goldhaber-Fiebert. “And we anticipate that the course will increase the number of Stanford students with the necessary skills to contribute to Stanford’s leadership in this area.”