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Secondary crashes or crashes that occur in the wake of a preceding or primary crash are among the most critical incidents occurring on highways, due to the exceptional danger they present to the first responders and victims of the primary crash. In this work, we developed a self-exciting temporal point process to analyze crash events data and classify it into primary and secondary crashes. Our model uses a self-exciting function to describe secondary crashes while primary crashes are modeled using a background rate function. We fit the model to crash incidents data from the Florida Department of Transportation, on Interstate-4 (I-4) highway for the years 2015-2017, to determine the model parameters. These are used to estimate the probability that a given crash is secondary crash and to find queue times. To represent the periodically varying traffic levels and crash incidents, we model the background rate, as a stationary function, a sinusoidal non-stationary function, and a piecewise non-stationary function. We show that the sinusoidal non-stationary background rate fits the traffic data better and replicates the daily and weekly peaks in crash events due to traffic rush hours. Secondary crashes are found to account for up to 15.09% of traffic incidents, depending on the city on the I-4 Highway., Competing Interests: There are no competing interests for this study., (Copyright: © 2023 Motagi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Competing Interests: Disclosures of conflicts of interest: J.C. No relevant relationships. S.P. National Science Foundation Graduate Research Fellowship, paid for through Brown University as part of the computer science department, additional stipend from Brown itself; consultant for Spellcraft AI (minor fees [<1000 dollars] for relatively unrelated consulting for a startup, the topic was similar: foundation models, although not in a medical context).

Background: Hereditary transthyretin amyloidosis (ATTRv) is an ultra-rare, life-shortening disease with a high unmet need. This study examined ATTRv caregiver health-related quality of life (HRQoL) and productivity., Methods: A cross-sectional online survey, including EQ-5D-3L, Hospital anxiety and depression scale (HADS), and caregiver and patient characteristics questions, was developed to assess ATTRv caregiver burden. A companion general population survey collected EQ-5D-3L, HADS and chronic health conditions data. Caregiver-control group differences in HRQoL were assessed using t-tests and chi-square tests. Ordinary Least Squares regression was used to estimate the disutility of being a caregiver compared to controls stratified by patient ambulatory status., Results: Thirty-six caregivers and matched controls completed the survey (n = 72). The disease severity of patients they cared for was varied: 33% required no assistance walking, 58% required assistance with walking and 9% required a wheelchair/were bedridden. On average, caregivers spent 6 h daily on practical care and 4 h daily on emotional support. Fifty-six percent indicated that they had changed their employment due to providing ATTRv care. Caregivers reported lower HRQoL, as indicated by lower EQ-5D 3L utility scores (M = 0.772, SD = 0.178 vs. M = 0.849, SD = 0.218) and higher HADS anxiety (9.3 vs. 6.1, p < 0.01) and depression (7.6 vs. 4.4, p < 0.01) scores, compared with matched controls. Caregivers were also more likely to report sleep problems (33% vs. 8%, p < 0.01) and stress (42% vs. 0%, p < 0.001) as chronic conditions than controls., Conclusions: The study results indicate that caring for a person with ATTRv can have a considerable negative impact on caregivers' HRQoL and productivity. The study findings provide important information for economic evaluations of ATTRv treatments., (© 2023. The Author(s).)

This article presents a framework to analyse the gendered impact of COVID-19 on workers in global value chains (GVCs) in the business process outsourcing, garment and electronics industries. Distinguishing between the health and lockdown effects of the pandemic, and between its supply- and demand-related impacts, the authors' gendered analysis focuses on multidimensional aspects of well-being, understands the economy as encompassing production and social reproduction spheres, and examines the social norms and structures of power that produce gender inequalities. Their findings suggest that the pandemic exposes and amplifies the existing vulnerabilities of women workers in GVCs., (© The authors 2021 Journal compilation © International Labour Organization 2021.)

Background: Successful development of new treatments for rare diseases (RDs) and their sustainable patient access require overcoming a series of challenges related to research and health technology assessment (HTA). These impediments, which may be unique to RDs or also apply to common diseases but are particularly pertinent in RDs, are diverse and interrelated., Objective: To develop for the first time a catalog of primary impediments to RD research and HTA, and to describe the cause and effect of individual challenges., Methods: Challenges were identified by an international 22-person expert working group and qualitative outreach to colleagues with relevant expertise. A broad range of stakeholder perspectives is represented. Draft results were presented at annual European and North American International Society for Pharmacoeconomics and Outcomes Research (ISPOR) congresses, and written comments were received by the 385-strong ISPOR Rare Disease Review Group from two rounds of review. Findings were refined and confirmed via targeted literature search., Results: Research-related challenges linked to the low prevalence of RDs were categorized into those pertaining to disease recognition and diagnosis, evaluation of treatment effect, and patient recruitment for clinical research. HTA-related challenges were classified into issues relating to the lack of a tailored HTA method for RD treatments and uncertainty for HTA agencies and health care payers., Conclusions: Identifying and highlighting diverse, but interrelated, key challenges in RD research and HTA is an essential first step toward developing implementable and sustainable solutions. A collaborative multistakeholder effort is required to enable faster and less costly development of safe, efficacious, and appropriate new RD therapies that offer value for money., (Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

Background: It has been suggested that ultra-rare diseases should be recognized as distinct from more prevalent rare diseases, but how drugs developed to treat ultra-rare diseases (DURDs) might be distinguished from drugs for 'other' rare diseases (DORDs) is not clear. We compared the characteristics of DURDs to DORDs from a health technology assessment (HTA) perspective in submissions made to the CADTH Common Drug Review. We defined a DURD as a drug used to treat a disease with a prevalence ≤ 1 patient per 100,000 people, a DORD as a drug used to treat a disease with a prevalence > 1 and ≤ 50 patients per 100,000 people. We assessed differences in the level and quantity of evidence supporting each HTA submission, the molecular basis of treatment agents, annual treatment cost per patient, type of reimbursement recommendation made by CADTH, and reasons for negative recommendations., Results: We analyzed 14 DURD and 46 DORD submissions made between 2004 and 2016. Compared to DORDs, DURDs were more likely to be biologic drugs (OR = 6.06, 95%CI 1.25 to 38.58), to have been studied in uncontrolled clinical trials (OR = 23.11, 95%CI 2.23 to 1207.19), and to have a higher annual treatment cost per patient (median difference = CAN$243,787.75, 95%CI CAN$83,396 to CAN$329,050). Also, submissions for DURDs were associated with a less robust evidence base versus DORDs, as DURD submissions were less likely to include data from at least one double-blinded randomized controlled trial (OR = 0.13, 95%CI 0.02 to 0.70) and have smaller patient cohorts in clinical trials (median difference = -108, 95%CI -234 to -50). Furthermore, DURDs are less likely to receive a positive reimbursement recommendation (OR = 0.22, 95%CI 0.05 to 0.91), and low level of evidence was the major contributor for a negative recommendation., Conclusions: The results suggest that DURDs could be viewed as distinct category from an HTA perspective. Applying the same HTA decision-making framework to DURDs and DORDs might have contributed the higher rate of negative reimbursement recommendations made for DURDs. Recognition of DURDs as a distinct subgroup of DRDs by explicitly defining DURDs based on objective criteria may facilitate the implementation of HTA assessment process that accounts for the issues associated with DURD.

Background: Rare diseases (RDs) affect a small number of people within a population. About 5000 to 8000 distinct RDs have been identified, with an estimated 6% to 8% of people worldwide suffering from an RD. Approximately 75% of RDs affect children. Frequently, these conditions are heterogeneous; many are progressive. Regulatory incentives have increased orphan drug designations and approvals., Objective: To develop emerging good practices for RD outcomes research addressing the challenges inherent in identifying, selecting, developing, adapting, and implementing patient-reported outcome (PRO) and observer-reported outcome (ObsRO) assessments for use in RD clinical trials., Good Practices for Outcomes Research: This report outlines the challenges and potential solutions in determining clinical outcomes for RD trials. It follows the US Food and Drug Administration Roadmap to Patient-Focused Outcome Measurement in Clinical Trials. The Roadmap consists of three columns: 1) Understanding the Disease or Condition, 2) Conceptualizing Treatment Benefit, and 3) Selecting/Developing the Outcome Measure. Challenges in column 1 include factors such as incomplete natural history data and heterogeneity of disease presentation and patient experience. Solutions include using several information sources, for example, clinical experts and patient advocacy groups, to construct the condition's natural history and understand treatment patterns. Challenges in column 2 include understanding and measuring treatment benefit from the patient's perspective, especially given challenges in defining the context of use such as variations in age or disease severity/progression. Solutions include focusing on common symptoms across patient subgroups, identifying short-term outcomes, and using multiple types of COA instruments to measure the same constructs. Challenges in column 3 center around the small patient population and heterogeneity of the condition or study sample. Few disease-specific instruments for RDs exist. Strategies include adapting existing instruments developed for a similar condition or that contain symptoms of importance to the RD patient population, or using a generic instrument validated for the context of use., Conclusions: This report provides state-of-the-art solutions to patient-reported outcome (PRO) and observer-reported outcome (ObsRO) assessments challenges in clinical trials of patients with RDs. These recommended solutions are both pragmatic and creative and posed with clear recognition of the global regulatory context used in RD clinical development programs., (Copyright © 2017. Published by Elsevier Inc.)

Background: At present, there is no universal definition of rare disease., Objective: To provide an overview of rare disease definitions currently used globally., Methods: We systematically searched for definitions related to rare disease from organizations in 32 international jurisdictions. Descriptive statistics of definitions were generated and prevalence thresholds were calculated., Results: We identified 296 definitions from 1109 organizations. The terms "rare disease(s)" and "orphan drug(s)" were used most frequently (38% and 27% of the definitions, respectively). Qualitative descriptors such as "life-threatening" were used infrequently. A prevalence threshold was specified in at least one definition in 88% of the jurisdictions. The average prevalence threshold across organizations within individual jurisdictions ranged from 5 to 76 cases/100,000 people. Most jurisdictions (66%) had an average prevalence threshold between 40 and 50 cases/100,000 people, with a global average of 40 cases/100,000 people. Prevalence thresholds used by different organizations within individual jurisdictions varied substantially. Across jurisdictions, umbrella patient organizations had the highest (most liberal) average prevalence threshold (47 cases/100,000 people), whereas private payers had the lowest threshold (18 cases/100,000 people)., Conclusions: Despite variation in the terminology and prevalence thresholds used to define rare diseases among different jurisdictions and organizations, the terms "rare disease" and "orphan drug" are used most widely and the average prevalence threshold is between 40 and 50 cases/100,000 people. These findings highlight the existing diversity among definitions of rare diseases, but suggest that any attempts to harmonize rare disease definitions should focus on standardizing objective criteria such as prevalence thresholds and avoid qualitative descriptors., (Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)