FSI's scholars tackle a range of issues, from longstanding concerns like nuclear nonproliferation and military defense to new challenges such as cybersecurity, biosecurity and emerging regional conflicts.
Research Spotlight
Particulate Plutonium Released from the Fukushima Daiichi Meltdowns
A new study reveals particles that were released from nuclear plants damaged in the devastating 2011 Tohoku earthquake and tsunami contained small amounts of radioactive plutonium.
Upon request by the United States Senate Select Committee on Intelligence (SSCI), researchers reviewed a data set of social media posts that Facebook provided to SSCI.
Living in Fear: The Dynamics of Extortion in Mexico’s Drug War
Using new survey data from Mexico, including list experiments to elicit responses about potentially illegal behavior, this article measures the prevalence of extortion and assistance among drug trafficking organizations.
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
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.
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.
National Academies of Sciences, Engineering, and Medicine,
January 22, 2023
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.
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.
