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 

Controversies over the lack of diagnostic testing for the COVID-19 virus have dominated U.S headlines for weeks. Technical challenges with the first test developed by the Centers for Disease Control and Prevention (CDC) left the nation with minimal diagnostic capacity during the first few weeks of the epidemic, according to a new paper published today in the Journal of the American Medical Association by Michelle Mello, a professor of medicine at Stanford Health Policy and professor of law at Stanford Law School.

On February 29, the Food and Drug Administration (FDA) began allowing high-complexity labs across the country to use tests they developed in-house. On March 5, the Stanford Clinical Virology Lab deployed its own test for patients at Stanford Health Care and Stanford Children’s Health.

We asked Mello to answer some questions about the federal rollout of diagnostic testing.

You write that in the early stages, COVID-19 “spread beyond the nation’s ability to detect it.” Is there anything the U.S. government could or should have done weeks ago to get out ahead of the spread?

Adopting broader testing criteria and allowing use of a wider range of tests would have been helpful in identifying the first U.S. cases and containing the spread. Manufacturing problems like the one that arose with CDC’s test are always a risk, but the fact that CDC put all its eggs in that one basket made the manufacturing snafu highly consequential.

Also, the public messaging from Washington about the seriousness of the problem has been neither consistent nor accurate, and I worry it may have led Americans to take fewer steps to prevent community transmission than we should have. Containment was not “pretty close to airtight.” A vaccine was never going to be ready in “three to four months,” as the Trump administration claimed. The case fatality rate is not “way under 1 percent.” Part of the problem here is that as the stock market continues to plunge, the president and the task force he appointed appear to be more concerned about calming investors than stopping the virus.

We seem to be between a rock and a hard place: You write that remedying gaps in testing is imperative, yet “more testing is not always better.” How do we determine the happy middle ground?

First, the testing criteria have to be calibrated to our actual testing capacity. You can’t announce that any American who wants a coronavirus test can get one and then, within hours, announce that there aren’t enough test kits to make that possible. High priorities for testing include patients with serious, unexplained respiratory illness and contacts of known cases. From there, testing can be expanded, beginning with other high-risk groups, as capacity permits.

Second, we should consider unintended side effects of mass testing. The problem with this virus is that it doesn’t have signature symptoms. It looks like the common cold or the flu. If everyone with a cough or fever, or who has been around someone with a cough or fever, shows up in their doctor’s office demanding a test, it will quickly overwhelm care facilities that should be focusing on patients with a higher likelihood of being infected or and those who are infected and are seriously ill. It may also work against the social distancing measures that public health officials are trying to encourage, because crowded waiting rooms may spread the virus.

The CDC announced Monday it now has the testing capacity in 78 state and local public health labs across 50 states to test for the virus. There are now 75,000 lab kits cumulatively to test for COVID-19 with more coming on board by mid-March. But is there anything we could have done to roll this out earlier?

The alternative would have been to allow laboratories to deploy their own tests from the beginning, using the primers and protocols made publicly available by the World Health Organization. That’s what other countries have done. RT-PCR is a mature technology and high-complexity labs around the country are well-qualified to conduct this type of testing.

There is a public health argument for not going that route: perhaps those labs wouldn’t have done as good a job as CDC’s own lab and the state labs that it handpicked early in the outbreak. What if there were erroneous test results? We could miss cases, or we could put people into isolation, with huge social consequences, based on false-positive results. There is also a worry that some labs aren’t consistent about reporting positive test results to CDC, and underreporting could compromise disease surveillance efforts.

The counterargument is that high-complexity labs have that certification for a reason—they’re good at what they do. And of course, surveillance is also compromised when you miss cases because you don’t test.

You write in your paper that testing for COVID-19 “highlights a controversial area of public policy—the regulation of laboratory-developed tests—in which there has long been tension between the goals of access and quality.” Who should be in charge of regulating these tests?

Laboratory-developed tests are largely unregulated outside of emergencies. The FDA proposed draft guidance in 2014 that, if implemented, would have required labs to make certain showings to FDA about tests they developed in-house, with the particular evidence calibrated to the risks involved in having a wrong test result. Contrary to President Trump’s claim that an Obama-era policy constrained coronavirus testing, the guidance did not relate to emergency situations. During declared emergencies, another statute and set of regulations apply, and the FDA has broad discretion to allow or disallow use of novel diagnostics and therapies as emergency countermeasures.

As a general matter, it makes good sense to require labs to submit evidence that their in-house tests work. It’s odd that laboratory-developed tests are carved out of requirements that apply to other kinds of medical devices. It’s also sensible that our legal framework allows FDA’s regular rules to be relaxed during emergencies so we can tailor our response to the difficult and changing circumstances.

You write that diagnostic testing is critical to an effective response to the novel coronavirus. What sort of policies and guidelines should be put into place to prevent such a sluggish rollout during an emerging epidemic the next time one comes around?

The legal framework for an effective emergency response is in place. Because giving agency heads the discretion to act as potentially unforeseeable circumstances require is a linchpin of this legal framework, it only works if leaders make smart choices. Every emergency is different, and there is a danger of Monday-morning quarterbacking. But we should learn from every misstep we make, and I think the lesson here is to make better use of already developed networks of highly qualified labs to make sure we have adequate testing capacity to isolate cases and trace their contacts very early in an outbreak.

What are some innovative approaches we could be taking to speed up testing for those who really need it?

The South Koreans have set up drive-through testing stations in parking lots to avoid concentrating crowds of people indoors. Of course, that requires that you have plenty of test kits, which we don’t yet – but we should also be thinking about creative ways to address the epidemic. For example, how could video calls be used to monitor the health of people confined at home after being exposed to the virus? How can social media be used to connect neighbors to help one another when some are isolated at home? Hopefully we can find new ways for technology to bring us together when pathogens drive us apart.

More evidence-based research is needed before the U.S. Preventive Services Task Force can recommend that clinicians screen their older patients for cognitive impairment such as dementia and Alzheimer’s disease.

Cognitive impairment is a growing public health dilemma that affects millions of Americans as they age. The Global Burden of Disease study shows that Alzheimer’s rose from the 12th most burdensome disease or injury in the United States in 1990 to the 6th in 2016.

Medical experts who were commissioned to conduct an evidence report for the Task Force projected that the burden of Alzheimer’s disease is expected to grow to 13.8 million U.S. residents by 2050 — or nearly 3.3% of the projected U.S. population by that year.

Their findings, the Task Force recommendation statement and several accompanying editorials were all published Tuesday in the Journal of the American Medical Association.

The symptoms of cognitive impairment can range from problems with memory and language, to learning new things or making decisions that affect everyday life. 

“Early identification of cognitive impairment through screening would ideally allow patients and their families to receive care at an earlier stage in the disease process, potentially facilitating discussions regarding health, financial, and legal decision-making while the patient still retains decision-making capacity,” the authors of the Task Force evidence report wrote.

But after reviewing some 287 studies including more than 285,000 older adults, the Task Force determined there wasn’t sufficient evidence about the benefits or harms of screening adults 65 and older who do not have signs or symptoms. The Task Force also did not find adequate evidence that screening for cognitive impairment improves decision-making or planning by patients, caregivers or doctors.

At the same time, there is little evidence on potential harms of screening, such as depression, anxiety or lower quality of life.

“Given the burden of dementia and the intense public interest in preventing cognitive impairment, the lack of progress is disheartening,” Carol Brayne, MD, with the Department of Public Health and Primary Care at the University of Cambridge in the UK, wrote in an accompanying JAMA editorial to the Task Force evidence report.

But, she added, “Political considerations and pressure from commercial interests and patient advocacy groups notwithstanding, public policies for dementia screening should be supported by evidence.”

The Task Force — an independent panel of national experts in prevention and evidence-based medicine — encourages clinicians to remain alert for early signs of symptoms of cognitive impairment, while calling for more research on the detection of dementia.

“Research is especially needed on whether screening and early detection of cognitive impairment helps patients, caregivers, and doctors make decisions about health care or plan for the future,” said Douglas K. Owens, chair of the Task Force and the director of Stanford Health Policy.  “We share the frustration of clinicians who want to offer something that could help patients prevent cognitive impairment. We hope that additional research will enable us to know whether that’s possible.”

The most commonly used screening tests include the Mini-Mental State Examination as well as the clock-drawing test. Screening tests involve asking patients to perform a series of tasks that asses one or more aspects of cognitive functions. The USPSTF concluded that more research is needed to know whether such screening tests can lead to interventions that help prevent or improve cognitive impairment. 

Elderly patients hospitalized with congestive heart failure have a poor prognosis and high risk of death and hospital readmission. So, their post-discharge care can strongly influence their outcomes.

Yet despite data showing that transitional care interventions, such as home visits by nurses, can reduce death rates and hospital readmission by more than 30%, many health systems have not implemented such programs. Health policy experts say this is due in part to cost concerns and doubts about the effectiveness of these delivery services.

 Now, a team of Stanford Medicine and Veterans Affairs researchers has sought to assess whether transitional care interventions provide good value and better outcomes, as there are 5 million people living with congestive heart failure in the United States and 500,000 new cases diagnosed each year. CHF is the stage of chronic heart disease in which fluids build up around the heart, causing it to pump inefficiently.

The researchers updated a 2017 study on the impact of transitional care intervention with four years of additional data. They then used it to compare standard post-discharge management with three post-discharge regimes for patients 75 or older that they found to be most effective: disease management clinics, nurse home visits and nurse case management.

All three transitional care interventions delivered appreciable health benefits to the patient population, said Jeremy Goldhaber-Fiebert, PhD, associate professor of medicine at the Stanford School of Medicine and core faculty member of Stanford Health Policy.

The findings were published in the Annals of International Medicine. Goldhaber-Fiebert is the senior author. The lead authors are Manuel R. Blum, MD, MS in Epidemiology & Clinical Research at Stanford in 2019 and now at the Department of General Internal Medicine at the University Hospital of Bern; Henning Øien, PhD, Norwegian Institute of Public Health, Oslo; and Harris L. Carmichael, MD, a Stanford/Intermountain Fellow in Population Health, Delivery Science, and Primary Care

“Transitional care interventions for older individuals with congestive heart failure — particularly nurse home visits — offer a high-value care alternative that could improve the health and longevity of millions of Americans,” he said.

The researchers said these transitional care services should become the standard of care for post-discharge management of patients with heart failure.

Heart failure causes 1 in 8 deaths nationwide

The prevalence of heart failure is estimated to be 26 million people worldwide and growing. In the United states, heart 5.7 million adults have been diagnosed with HF, with an estimated annual direct cost of $39.2 billion to $60 billion. Total heart failure costs in the United States are expected to exceed $70 billion by 2030, the authors wrote. According to the Centers for Disease Control and Prevention, heart disease costs the United States about $219 billion each year from health-care services, medicines and lost productivity.

Of the 15 million Americans in their mid-70s to 80s today, about 1 million suffer heart failure.

“So population gains from more effective post-discharge care would be hundreds of thousands of life years,” Goldhaber-Fiebert said. “Likewise, tens of thousands of costly rehospitalizations could be prevented each year if these interventions were delivered successfully.”

Heart failure primarily affects older people and is the second-most common inpatient diagnosis billed to Medicare. Yet the authors cite a recent study of 18 million Medicaid charges which found that only 7% of eligible patients at risk of rehospitalization received transitional services.

The standard post-hospital care for those patients includes sending them home with some advice and scheduling follow-up visits for them with cardiologists within 14 days of discharge. The researchers found that patients who received this standard post-hospitalization care with an average age of 75 had an average life expectancy of 2.9 years and 2.9 hospitalizations during their remaining lifetime. In comparison, nurse home visits decreased the number of hospitalizations by 10 readmissions per 100 patients and increased life expectancy by approximately four months, the study found.

“If these interventions were successfully implemented at scale, they could provide important substantial benefits with very good value,” said co-author Douglas Owens, MD, the Henry J. Kaiser Jr. Professor and professor of medicine at Stanford.

Reduced hospitalizations for congestive heart failure, according to the research, produces substantial cost savings that partially offset the costs of delivering the interventions. Though nurse home visits increase lifetime health care costs by $4,622, the substantial health benefits that they deliver justify their costs: $19,570 quality adjusted life years gained, which is considered highly cost-effective.

Hospital and insurance administrators take note

“Our results have important implications for decision-makers in hospital administration as well as in insurance and policy settings,” the authors wrote. They concluded:

• Transitional care services should become the standard of care for post-discharge management of patients with heart failure;
• The increasing reimbursement restrictions and regulations affecting HF hospital readmissions, through such programs as the Centers for Medicare & Medicaid Services Hospital Readmission Reduction Program, makes this research particularly informative to decision-makers;
• Hospital administrators could use the research to determine which transitional services are most cost-effective for its rural population, overall patient base and hospital system.

The other Stanford researcher on the study was Paul Heidenreich, MD, a professor of medicine and health research and policy at the Stanford University School of Medicine and, by courtesy, professor of health research and policy at the Palo Alto Veterans Affairs Health Care System.

Stanford Health Policy researchers, led by Josh Salomon, have been awarded a five-year grant from the Centers for Disease Control and Prevention (CDC) to conduct health and economic modeling to guide national and local policies and programs focusing on some of the most important infectious diseases in the United States.

The CDC grant establishes the Prevention Policy Modeling Lab at Stanford, continuing a multi-institution collaboration that began when Salomon was a professor at Harvard prior to joining Stanford in 2017.

“The overall mission of the Prevention Policy Modeling Lab is to leverage the best available evidence to inform strategic decision-making about major public health problems,” Salomon said. “We do this by combining techniques from decision science, simulation modeling and health economics to estimate and project major patterns and trends in these diseases and to evaluate different clinical and public health strategies to address them.”

The initiative will focus on policy and practice in the areas of tuberculosis, HIV, hepatitis, sexually transmitted infections and adolescent health. The grant from the Centers for Disease Control and Prevention supports a wide range of modeling activities, including those that assess: 

• Projections of future morbidity and mortality
• Burden and costs of diseases
• Costs and cost-effectiveness of interventions
• Population-level program impact
• Optimized resource allocation

Stanford researchers who are involved in the Modeling Lab include Douglas K. Owens, Margaret Brandeau, Eran Bendavid, Jeremy Goldhaber-Fiebert, Jason Andrews, Samuel So and Mehlika Toy. The consortium also includes partners at Harvard, Yale, Michigan, Boston University, Boston Medical Center and the MA Department of Public Health.

“As a multi-institution consortium, on any given problem we’re able to assemble a team that includes both subject matter experts and collaborators who specialize in statistics, epidemiology, data science, economics and decision analysis,” Salomon said. “The policy models that we develop allow us to synthesize a wide array of different types and sources of evidence to shed light on the essence of the problem and to weigh the likely benefits and costs of responding in different ways.”

Prior work from the consortium on the potential impact and cost-effectiveness of expanding testing for hepatitis C virus was cited in the recent decision by the U.S. Preventive Services Task Force to revise their screening recommendations to cover all adults. The Modeling Lab has also examined prospects and strategies for eliminaitng tuberculosis in the United States and policies relevant to the rising threat of antimicrobial-resistant gonococcal infection among other topics.