The Biden administration’s new National Cybersecurity Strategy takes on the third rail of cybersecurity policy: software liability. For decades, scholars and litigators have been talking about imposing legal liability on the makers of insecure software. Authored by Jim Dempsey for Lawfare Blog

From The Lancet, March 2023

In this JAMA Health Forum commentary, SHP's Michelle Mello and colleagues argue that the $1.7 trillion omnibus bill that Congress passed in December 2022 responds to several urgent public health needs, yet only narrowly addresses some of the critical determinants of pandemic preparedness.

Objective: To evaluate the cost effectiveness of California's statewide perinatal quality collaborative for reducing severe maternal morbidity (SMM) from hemorrhage.

Results: The collaborative was cost effective, exhibiting strong dominance when compared with the baseline or standard of care. In a theoretical cohort of 480,000 births, collaborative implementation added 182 QALYs (0.000379/birth) by averting 913 cases of SMM, 28 emergency hysterectomies, and one maternal mortality. Additionally, it saved $9 million ($17.78/birth) due to averted SMM costs. Although sensitivity analyses across parameter uncertainty ranges provided cases where the intervention was not cost saving, it remained cost effective throughout all analyses. Additionally, scenario-based sensitivity analysis found the intervention cost effective regardless of birth volume and implementation costs.

China, the Republic of Korea, and the Yellow Sea

Abstract

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop a framework to generate simple classification rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We show that these classification rules present reasonable accuracy, sensitivity, and specificity (all ≥ 80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

The COVID-19 pandemic spurred a rapid expansion of wastewater-based infectious disease surveillance systems to monitor and anticipate disease trends in communities.The Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System in September 2020 to help coordinate and build upon those efforts. Produced at the request of CDC, this report reviews the usefulness of community-level wastewater surveillance during the pandemic and assesses its potential value for control and prevention of infectious diseases beyond COVID-19.

A joint report with Georgetown University’s Center for Security and Emerging Technology OpenAI and Stanford Internet Observatory

Objective: To develop a measure for fair inclusion in pivotal trials by assessing transparency and representation of enrolled women, older adults (aged 65 years and older), and racially and ethnically minoritized patients.

Federal courts in Texas are fast becoming known as the graveyards of U.S. health policies.1 Decisions concerning a range of statutes, from the Affordable Care Act (ACA) to the Emergency Medical Treatment and Labor Act, have chipped away at federal powers to protect the public’s health. The latest case in this series, Braidwood Management Inc. v. Becerra,2 targets the ACA’s use of U.S. Preventive Services Task Force (USPSTF) recommendations as a basis for mandating insurance coverage for preventive care. The Braidwood decision not only destabilizes efforts to ensure access to essential insurance benefits but also illustrates an emerging strategy among litigants with antiregulatory agendas: wielding heretofore sleepy doctrines of administrative and constitutional law to undercut health initiatives.

In this cross-sectional study of nearly 800,000 U.S. participants aged 5 to 17 years with family income under 200% of the federal poverty threshold, researchers found that higher family income was significantly associated with a lower prevalence of diagnosed infections, mental health disorders, injury, asthma, anemia, and substance use disorders and lower 10-year mortality. Read the full original investigation in JAMA.

Key policy takeaways from Renée DiResta on the need to understand how platforms moderate content, David Relman and Megan Palmer on strengthening regulations on risky pathogen research, Steven Pifer on the ramifications of the Ukraine-Russia war on the Kremlin, Larry Diamond on the protests in China, Iran, and Russia, Naomi Egel on protecting civilians during war, and Rose Gottemoeller on U.S. nuclear negotiations with Russia.

Suspected Russian Actors Leverage Alternative Tech Platforms in Continued Effort to Covertly Influence Right-Wing U.S. Audiences

In Science magazine, Stanford researchers Megan Palmer and David Relman are among co-authors recommending a reset of U.S. and global policy to address the gaps and challenges of current guidance.

Abstract

This paper analyzes the impact of paid family leave (PFL) policies in California, New Jersey, and New York on the labor market and mental health outcomes of individuals whose spouses or children experience health shocks. We use data from the 1996-2019 restricted-use version of the Medical Expenditure Panel Survey (MEPS), which provides state of residence and the precise timing of hospitalizations and surgeries, our health shock measures. We use difference-in-difference and event-study models to compare the differences in post-health-shock labor market and mental health outcomes between spouses and parents before and after PFL implementation relative to analogous differences in states with no change in PFL access. We find that PFL access leads to a 7.0 percentage point decline in the likelihood that the (healthy) wives of individuals with medical conditions or limitations who experience a hospitalization or surgery report “leaving a job to care for home or family” in the post-health-shock rounds. Impacts of PFL access on women's mental health outcomes and on men whose spouses have health shocks are more mixed, and we find no effects on parents of children with health shocks. Lastly, we show that improvements in job continuity are concentrated among caregivers with 12 or fewer years of education, suggesting that government-provided PFL might reduce disparities in leave access.

During the first year of the pandemic, East Asian countries have reported fewer infections, hospitalizations, and deaths from COVID-19 disease than most countries in Europe and the Americas. Our goal in this paper is to generate and evaluate hypothesis that may explain this striking fact. We consider five possible explanations: (1) population age structure (younger people tend to have less severe COVID-19 disease upon infection than older people); (2) the early adoption of lockdown strategies to control disease spread; (3) genetic differences between East Asian population and European and American populations that confer protection against COVID-19 disease; (4) seasonal and climactic contributors to COVID-19 spread; and (5) immunological differences between East Asian countries and the rest of the world. The evidence suggests that the first four hypotheses are unlikely to be important in explaining East Asian COVID-19 exceptionalism. Lockdowns, in particular, fail as an explanation because East Asian countries experienced similarly good infection outcomes despite vast differences in lockdown policies adopted by different countries to control the COVID-19 epidemic. The evidence to date is consistent with our fifth hypothesis – pre-existing immunity unique to East Asia – but there are still essential parts of this story left for scientists to check.

Key policy takeaways from Michael McFaul on Russia after Putin, Rose Gottemoeller on the New START talks, Nathaniel Persily on the midterm elections and U.S. democracy, Francis Fukuyama on democracy in America, Anna Grzymala-Busse on Hungary's Viktor Orbán and the GOP, Daphne Keller on the European Union's new cyber policies, and Marietje Schaake on Twitter and Elon Musk.

Importance  Statin-associated muscle symptoms (SAMS) are common and may lead to discontinuation of indicated statin therapy. Observational studies suggest that vitamin D therapy is associated with reduced statin intolerance, but no randomized studies have been reported.

Objective  To test whether vitamin D supplementation was associated with prevention of SAMS and a reduction of statin discontinuation.

We evaluated the protection conferred by mRNA vaccines and previous infection against infection with the omicron variant in two high-risk populations: residents and staff in the California state prison system. We used a retrospective cohort design to analyze the risk of infection during the omicron wave using data collected from December 24, 2021, through April 14, 2022. Weighted Cox models were used to compare the effectiveness (measured as 1 minus the hazard ratio) of vaccination and previous infection across combinations of vaccination history (stratified according to the number of mRNA doses received) and infection history (none or infection before or during the period of B.1.617.2 [delta]–variant predominance). A secondary analysis used a rolling matched-cohort design to evaluate the effectiveness of three vaccine doses as compared with two doses.

We use linked administrative data that combines the universe of California birth records, hospitalizations, and death records with parental income from Internal Revenue Service tax records and the Longitudinal Employer-Household Dynamics file to provide novel evidence on economic inequality in infant and maternal health. We find that birth outcomes vary nonmonotonically with parental income, and that children of parents in the top ventile of the income distribution have higher rates of low birth weight and preterm birth than those in the bottom ventile. However, unlike birth outcomes, infant mortality varies monotonically with income, and infants of parents in the top ventile of the income distribution---who have the worst birth outcomes---have a death rate that is half that of infants of parents in the bottom ventile. When studying maternal health, we find a similar pattern of non-monotonicity between income and severe maternal morbidity, and a monotonic and decreasing relationship between income and maternal mortality. At the same time, these disparities by parental income are small when compared to racial disparities, and we observe virtually no convergence in health outcomes across racial and ethnic groups as income rises. Indeed, infant and maternal health in Black families at the top of the income distribution is markedly worse than that of white families at the bottom of the income distribution.Lastly, we benchmark the health gradients in California to those in Sweden, finding that infant and maternal health is worse in California than in Sweden for most outcomes throughout the entire income distribution.