To maximize its value, the design, development and implementation of structural health monitoring (SHM) should focus on its role in facilitating decision support. In this position paper, we offer perspectives on the synergy between SHM and decision-making. We propose a classification of SHM use cases aligning with various dimensions that are closely linked to the respective decision contexts. The types of decisions that have to be supported by the SHM system within these settings are discussed along with the corresponding challenges. We provide an overview of different classes of models that are required for integrating SHM in the decision-making process to support the operation and maintenance of structures and infrastructure systems. Fundamental decision-theoretic principles and state-of-the-art methods for optimizing maintenance and operational decision-making under uncertainty are briefly discussed. Finally, we offer a viewpoint on the appropriate course of action for quantifying, validating, and maximizing the added value generated by SHM. This work aspires to synthesize the different perspectives of the SHM, Prognostic Health Management, and reliability communities, and provide directions to researchers and practitioners working towards more pervasive monitoring-based decision-support.

Accelerating COVID-19 Treatment Interventions and Vaccines (ACTIV) was initiated by the US government to rapidly develop and test vaccines and therapeutics against COVID-19 in 2020. The ACTIV Therapeutics-Clinical Working Group selected ACTIV trial teams and clinical networks to expeditiously develop and launch master protocols based on therapeutic targets and patient populations. The suite of clinical trials was designed to collectively inform therapeutic care for COVID-19 outpatient, inpatient, and intensive care populations globally. In this report, we highlight challenges, strategies, and solutions around clinical protocol development and regulatory approval to document our experience and propose plans for future similar healthcare emergencies.

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future.

We compared study characteristics of randomized controlled trials funded by industry (N=697) to those not funded by industry (N=835). RCTs published in high-impact journals are more likely to be blinded, more likely to include a placebo, and more likely to post trial results on ClinicalTrials.gov. Our findings emphasize the importance of evaluating the quality of an RCT based on its methodological rigor, not its funder type.

OBJECTIVES/GOALS: Community-based residency programs often lack formal training in research scholarship required by ACGME. To address this need, UCSF’s CTSI collaborated with residency leaders to implement a self-paced online curriculum for residents called Training in Practice Based Research (TIPR). We describe characteristics of the initial trainee cohort. METHODS/STUDY POPULATION: In the 2022-23 academic year, TIPR was offered to 10 UCSF-affiliated family medicine residency programs across Northern California and the Central Valley, and 8 chose to participate. An additional community-based psychiatry residency independently contacted our team and was also granted permission to participate. We conducted baseline surveys with participants to understand their prior research experience and motivation to join TIPR. Descriptive data for demographics of trainees and their prior research experience were collected using Qualtrics. Thematic analyses were conducted on qualitative responses. RESULTS/ANTICIPATED RESULTS: Of 32 participants, 29 completed the survey (91%). Learners identified as 40% non-Hispanic White, 28% Asian, 16% Hispanic, 9% non-Hispanic Black, and 15% non-Hispanic other. 28% were motivated to participate in the program because it was a residency requirement, 31% wanted to improve their scholarly skills and confidence, 16% were interested in career development, and 6% were interested in networking. 19% reported no research experience. Participants are currently working on scholarly projects designed during the first year of TIPR. In 2023-2024, with the addition of two new family medicine residency programs, an additional 40 residents have enrolled in TIPR. In April 2024, we will present data on projects completed, and demographics of the full cohort. DISCUSSION/SIGNIFICANCE: With CTSI support, TIPR has reached a large cohort of ethnically diverse physician trainees in community-based settings. Future evaluation will focus on whether TIPR increases the quantity and quality of practice-based research within residency training programs served by this program.

This study investigated replicating six generations of glasshouse-based flowering date selection in wild radish (Raphanus raphanistrum L.) using an adaptation of the population model SOMER (Spatial Orientated Modelling of Evolutionary Resistance). This individual-based model was chosen because it could be altered to contain varying numbers of genes, along with varying levels of environmental influence on the phenotype (namely the heritability). Accurate replication of six generations of genetic change that had occurred in a previous glasshouse-based selection was achieved, without intermediate adjustments. This study found that multiple copies of just two genes were required to reproduce the polygenic flowering time adaptations demonstrated in that previous research. The model included major effect type M1 genes, with linkage and crossing over, and minor effect type M2 genes undergoing independent assortment. Within the model, transmissibility (heritability of each gene type) was parameterized at 0.60 for the M1 genes and 0.45 for the M2 genes. The serviceable parameterization of the genetics of flowering in R. raphanistrum within a population model means that simulated examinations of the effects of external weed control on flowering time adaptations are now more feasible. An accurate and simplified Mendelian-based model replicating the adaptive shifts of flowering time that is controlled by a complex array of genes is useful in predicting life-cycle adaptations to evade weed control measures such as harvest weed seed control, which apply intense adaptive selections on traits that affect seed retention at harvest, including flowering time.

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

It is acknowledged that health technology assessment (HTA) is an inherently value-based activity that makes use of normative reasoning alongside empirical evidence. But the language used to conceptualise and articulate HTA's normative aspects is demonstrably unnuanced, imprecise, and inconsistently employed, undermining transparency and preventing proper scrutiny of the rationales on which decisions are based. This paper – developed through a cross-disciplinary collaboration of 24 researchers with expertise in healthcare priority-setting – seeks to address this problem by offering a clear definition of key terms and distinguishing between the types of normative commitment invoked during HTA, thus providing a novel conceptual framework for the articulation of reasoning. Through application to a hypothetical case, it is illustrated how this framework can operate as a practical tool through which HTA practitioners and policymakers can enhance the transparency and coherence of their decision-making, while enabling others to hold them more easily to account. The framework is offered as a starting point for further discussion amongst those with a desire to enhance the legitimacy and fairness of HTA by facilitating practical public reasoning, in which decisions are made on behalf of the public, in public view, through a chain of reasoning that withstands ethical scrutiny.

A key insight from Adam Smith is that economists should base their conclusions about a monetary institution or policy on a careful study of the history of that institution or policy, a study that includes the experiences of other countries. To illustrate Smith’s reliance on financial history we cover five current monetary problems that have close analogies with problems that Smith discussed: (1) inflation, (2) banking panics, (3) public debt, (4) usury laws, (5) central bank digital currencies.