Science and policy in extremis: the UK’s initial response to COVID-19

Drawing on the SAGE minutes and other documents, I consider the wider lessons for norms of scientific advising that can be learned from the UK’s initial response to coronavirus in the period January–March 2020, when an initial strategy that planned to avoid total suppression of transmission was abruptly replaced by an aggressive suppression strategy. I introduce a distinction between “normatively light advice”, in which no specific policy option is recommended, and “normatively heavy advice” that does make an explicit recommendation. I argue that, although scientific advisers should avoid normatively heavy advice in normal times in order to facilitate democratic accountability, this norm can be permissibly overridden in situations of grave emergency. SAGE’s major mistake in early 2020 was not that of endorsing a particular strategy, nor that of being insufficiently precautionary, but that of relying too heavily on a specific set of “reasonable worst-case” planning assumptions. I formulate some proposals that assign a more circumscribed role to “worst-case” thinking in emergency planning. In an epilogue, I consider what the implications of my proposals would have been for the UK’s response to the “second wave” of late 2020.

To exit or not to exit: Evaluating a case management pathway in a Global South context to decrease service dependency

An evaluation was undertaken of a case management pathway for a child protection organization in Cambodia to decrease service dependency. Save the Children’s ‘Steps to Protect’ was used as an evaluation framework to identify how the organization met the criteria for the core components of case management. These included identification and initial screening, case planning, implementation, and case review, and the findings show that a well-defined, staged process for case management actively reduces service dependency. The recommendations are that a staged case management pathway should be developed in child protection services as an approach for reducing service dependency.

Robustness assessment of a novel 4D optimization approach for lung cancer radiotherapy

One of the main challenges to treatment of lung cancer with radiation therapy is the tumor motion due to respiration. Previously, a novel approach was developed to generate treatment plans which compensate for respiratory motion and its variations. The worst case method is based on combining two intensity maps from two 4D plans optimized on the two worst cases of motion variations. The worst case planning method was previously tested on simulated motion variations. The goal of this project was to further test the worst case approach on realistic patient motion variations and treatment planning data. Two approaches to combining worst case plans were investigated: the first method takes the average of the two intensity maps, and the second method takes the maximum intensity of the two intensity maps. The robustness of worst case plans was compared with ITV plans and nominal 4D plans on three different motion variation scenarios. Study 1 and 2 investigated the robustness of the worst case methods on amplitude variations and patient motion variations on simulated image data. Study 3 investigated the robustness of the worst case methods on patient motion variations using real patient image data. The average intensity worst case method was only robust to Study 3 motion variations. The maximum intensity worst case method, the margin based, and the nominal approaches were not robust to any of the motion variations. Further evaluation over a wide range of tumour sizes, motion amplitudes and variability is required to determine the clinical applicability of the worst case planning method.

Robustness assessment of a novel 4D optimization approach for lung cancer radiotherapy

One of the main challenges to treatment of lung cancer with radiation therapy is the tumor motion due to respiration. Previously, a novel approach was developed to generate treatment plans which compensate for respiratory motion and its variations. The worst case method is based on combining two intensity maps from two 4D plans optimized on the two worst cases of motion variations. The worst case planning method was previously tested on simulated motion variations. The goal of this project was to further test the worst case approach on realistic patient motion variations and treatment planning data. Two approaches to combining worst case plans were investigated: the first method takes the average of the two intensity maps, and the second method takes the maximum intensity of the two intensity maps. The robustness of worst case plans was compared with ITV plans and nominal 4D plans on three different motion variation scenarios. Study 1 and 2 investigated the robustness of the worst case methods on amplitude variations and patient motion variations on simulated image data. Study 3 investigated the robustness of the worst case methods on patient motion variations using real patient image data. The average intensity worst case method was only robust to Study 3 motion variations. The maximum intensity worst case method, the margin based, and the nominal approaches were not robust to any of the motion variations. Further evaluation over a wide range of tumour sizes, motion amplitudes and variability is required to determine the clinical applicability of the worst case planning method.

Structured well-being assessments in public child welfare: Observations across two states

Children entering custody within the child welfare system have been found to have high levels of trauma and significant behavioral health needs. In this paper, authors demonstrate how a structured functional well-being assessment can be used with the custody population to promote an understanding of behavioral health needs, inform case planning, and measure functional improvement over time. Specifically, this paper will: (a) briefly describe how two states implemented a common standardized assessment of functioning to inform case planning and measure well-being progress of children in the custody of a public child welfare system (b) examine what this common assessment tool reveals about the strengths and needs of children entering custody across two sites and (c) describe the magnitude of change in functional improvement measured across 6 months. This paper will contribute to the existing knowledge by sharing possible themes in functioning related to children entering custody while examining changes in functioning over time. Implications for practice, policy, and future research will be discussed.

Risk-Need-Responsivity Meets Mental Health: Implementation Challenges in Probation Case Planning

This study examined the feasibility of and fidelity to risk/needs assessment, mental health screening, and risk-need-responsivity (RNR)-based case planning within juvenile probation in two states. The researcher-guided implementation effort included the Massachusetts Youth Screening Instrument-2 (MAYSI-2), Structured Assessment of Violence Risk in Youth (SAVRY), and policies to prioritize criminogenic needs while using mental health services only when warranted. Data from 53 probation officers (POs) and 553 youths indicated three of five offices had high fidelity to administration and case planning policies. The interrater reliability ( n = 85; intraclass correlation coefficient [ICC][A, 1] = .92 [Northern state] and .80 [Southern state]) and predictive validity ( n = 455; Exp[B] = 1.83) of SAVRY risk ratings were significant. There was an overreliance on mental health services; 48% of youth received these referrals when only 20% screened as having mental health needs. Barriers to fidelity to RNR practices in some offices included assessments not being conducted before disposition, lack of service availability, and limited buy-in from a few stakeholders.

Hardness of Motion Planning with Obstacle Uncertainty in Two Dimensions

We consider the problem of motion planning in the presence of uncertain obstacles, modeled as polytopes with Gaussian-distributed faces (PGDFs). A number of practical algorithms exist for motion planning in the presence of known obstacles by constructing a graph in configuration space, then efficiently searching the graph to find a collision-free path. We show that such an exact algorithm is unlikely to be practical in the domain with uncertain obstacles. In particular, we show that safe 2D motion planning among PGDF obstacles is [Formula: see text]-hard with respect to the number of obstacles, and remains [Formula: see text]-hard after being restricted to a graph. Our reduction is based on a path encoding of MAXQHORNSAT and uses the risk of collision with an obstacle to encode variable assignments and literal satisfactions. This implies that, unlike in the known case, planning under uncertainty is hard, even when given a graph containing the solution. We further show by reduction from [Formula: see text]-SAT that both safe 3D motion planning among PGDF obstacles and the related minimum constraint removal problem remain [Formula: see text]-hard even when restricted to cases where each obstacle overlaps with at most a constant number of other obstacles.

Patient selection for LIVE therapy - From clinical indications to multimodality imaging individual case planning

Background LIVE (Less Invasive Ventricular Enhancement) with Revivent TC™ is an innovative therapy for symptomatic ischemic Heart Failure (HF). It is designed to reconstruct a negatively remodeled left ventricle (LV) after an anterior myocardial infarction (MI) by plication of the scar tissue. Its indications are specific and, as with any other structural heart intervention, the success of the procedure starts with appropriate patient selection. We aim to present the indications of the technique, crucial aspects in patient selection and individual case planning approach. Methods and Results After clinical evaluation, transthoracic echocardiography is the first imaging modality to be performed in a potential candidate for the therapy. However, definitive indication and detailed case planning rely on late gadolinium-enhanced cardiac magnetic resonance imaging or multiphasic contrast-enhanced cardiac computed tomography. These imaging modalities also assist with relative or absolute contra-indications for the procedure. Individual assessment is done to tailor the procedure to the specifics of the LV anatomy and location of the myocardial scar. Conclusion LIVE procedure is a unique intervention to treat symptomatic heart failure and ischemic cardiomyopathy after anterior MI. It is a highly customizable intervention that allows a patient-tailored approach, based on multimodality imaging assessment and planification.