Population-level Information Research Articles

Defining and quantifying population-level need for children’s palliative care: findings from a rapid scoping review

BackgroundThe number of children who require palliative care has been estimated to be as high as 21 million globally. Delivering effective children’s palliative care (CPC) services requires accurate population-level information on current and future CPC need, but quantifying need is hampered by challenges in defining the population in need, and by limited available data. The objective of this paper is to summarise how population-level CPC need is defined, and quantified, in the literature.MethodsScoping review performed in line with Joanna Briggs Institute methodology for scoping reviews and PRISMA-ScR guidelines. Six online databases (CINAHL, Cochrane Library, EMBASE, Medline, PsycINFO, and Web of Science), and grey literature, were searched. Inclusion criteria: literature published in English; 2008–2023 (Oct); including children aged 0–19 years; focused on defining and/or quantifying population-level need for palliative care.ResultsThree thousand five hundred seventy-eight titles and abstracts initially reviewed, of which, 176 full-text studies were assessed for eligibility. Overall, 51 met the inclusion criteria for this scoping review. No universal agreement identified on how CPC need was defined in population-level policy and planning discussions. In practice, four key definitions of CPC need were found to be commonly applied in quantifying population-level need: (1) ACT/RCPCH (Association for Children with Life-Threatening or Terminal Conditions and their Families, and the Royal College of Paediatrics and Child Health) groups; (2) The ‘Directory’ of Life-Limiting Conditions; (3) ‘List of Life-Limiting Conditions’; and (4) ‘Complex Chronic Conditions’. In most cases, variations in data availability drove the methods used to quantify population-level CPC need and only a small proportion of articles incorporated measures of complexity of CPC need.ConclusionOverall, greater consistency in how CPC need is defined for policy and planning at a population-level is important, but with sufficient flexibility to allow for regional variations in epidemiology, demographics, and service availability. Improvements in routine data collection of a wide range of care complexity factors could facilitate estimation of population-level CPC need and ensure greater alignment with how need for CPC is defined at the individual-level in the clinical setting.

A proactive/reactive mass screening approach with uncertain symptomatic cases.

We study the problem of mass screening of heterogeneous populations under limited testing budget. Mass screening is an essential tool that arises in various settings, e.g., the COVID-19 pandemic. The objective of mass screening is to classify the entire population as positive or negative for a disease as efficiently and accurately as possible. Under limited budget, testing facilities need to allocate a portion of the budget to target sub-populations (i.e., proactive screening) while reserving the remaining budget to screen for symptomatic cases (i.e., reactive screening). This paper addresses this decision problem by taking advantage of accessible population-level risk information to identify the optimal set of sub-populations for proactive/reactive screening. The framework also incorporates two widely used testing schemes: Individual and Dorfman group testing. By leveraging the special structure of the resulting bilinear optimization problem, we identify key structural properties, which in turn enable us to develop efficient solution schemes. Furthermore, we extend the model to accommodate customized testing schemes across different sub-populations and introduce a highly efficient heuristic solution algorithm for the generalized model. We conduct a comprehensive case study on COVID-19 in the US, utilizing geographically-based data. Numerical results demonstrate a significant improvement of up to 52% in total misclassifications compared to conventional screening strategies. In addition, our case study offers valuable managerial insights regarding the allocation of proactive/reactive measures and budget across diverse geographic regions.

Population-level information for improving quantile regression efficiency

Observational studies often rely on sample survey data for estimation, given the difficulty of obtaining exhaustive information for the entire population. However, the use of sample data can lead to a reduction in estimation efficiency due to sampling error. When certain population-level data are accessible, devising an effective strategy to integrate them into the underlying estimation process proves advantageous. This paper proposes a methodology based on empirical likelihood for conducting quantile regression analysis on longitudinal data while incorporating population-level information. Both theoretical analysis and numerical simulations demonstrate that the proposed approach outperforms estimation methods that do not leverage population-level data.

European Health Information Portal: a one-stop shop for health information.

Timely and high-quality population-level health information is needed to support evidence-informed decision-making, for planning and evaluation of prevention, care and cure activities as well as for research to generate new knowledge. FAIR (Findable, Accessible, Interoperable and Reusable) principles are one of the key elements supporting health research and making it more cost-effective through the reuse of already existing data. Currently, health data are in many countries dispersed and difficult to find and access. Two EU Public Health Programmes co-funded Joint Actions, Information for Action (InfAct) and Population Health Information Research Infrastructure (PHIRI) have established a European Health Information Portal, a web-based service, to facilitate better findability, access, interoperability and reuse of existing health information. The European Health Information Portal (www.healthinformationportal.eu) has been established including sections on National Nodes, data sources, publications, health information projects within countries and across Europe, research networks and research infrastructures, ethical and legal issues for health information exchange and use, capacity-building activities in all areas of population health and a dedicated COVID-19 section. The European Health Information Portal, being a central place for a wide range of population health information from EU Member States, is an information source for researchers, policy-makers and other relevant stakeholders. It is important to ensure the sustainability of the portal, especially in light of the European Health Data Space (EHDS) Regulation proposal and its requirements regarding the secondary use of health data.

Geographically weighted regression model-calibration for finite population parameter estimation under two stage sampling design

In many agricultural, forestry, environmental, and ecological surveys, data are often spatial in nature and exhibit spatial nonstationarity. A well-known method for addressing spatial nonstationarity and capturing the spatially varying relationships between different variables is Geographic Weighted Regression (GWR). The calibration approach is one of the most widely used techniques in sample surveys for incorporating the known population characteristics of auxiliary variables by changing the original sampling design weights. The model-calibration approach is an improvement on the conventional calibration approach that can handle a variety of assisting working models. Two-stage sampling is one of the most frequently used sampling strategies in large-scale sample surveys. In the present study, a couple of GWR model-calibration estimators were proposed under two-stage sampling, assuming the availability of population-level complete auxiliary information. Under a set of regularity assumptions, the asymptotic properties of the developed estimators have been evaluated such as design unbiasedness, model unbiasedness, approximate variance, and estimators of variances. The performance of the developed estimators has been compared with the existing estimators through a spatial simulation study and a design-based simulation based on real data. The performance of the proposed estimator was found to be more precise than the existing estimators under two-stage sampling.

An optimization framework for large-scale screening under limited testing capacity with application to COVID-19.

We consider the problem of targeted mass screening of heterogeneous populations under limited testing capacity. Mass screening is an essential tool that arises in various settings, e.g., ensuring a safe supply of blood, reducing prevalence of sexually transmitted diseases, and mitigating the spread of infectious disease outbreaks. The goal of mass screening is to classify whole population groups as positive or negative for an infectious disease as efficiently and accurately as possible. Under limited testing capacity, it is not possible to screen the entire population and hence administrators must reserve testing and target those among the population that are most in need or most susceptible. This paper addresses this decision problem by taking advantage of accessible population-level risk information to identify the optimal set of sub-populations to target for screening. We conduct a comprehensive analysis that considers the two most commonly adopted schemes: Individual testing and Dorfman group testing. For both schemes, we formulate an optimization model that aims to minimize the number of misclassifications under a testing capacity constraint. By analyzing the formulations, we establish key structural properties which we use to construct efficient and accurate solution techniques. We conduct a case study on COVID-19 in the United States using geographic-based data. Our results reveal that the considered proactive targeted schemes outperform commonly adopted practices by substantially reducing misclassifications. Our case study provides important managerial insights with regards to optimal allocation of tests, testing designs, and protocols that dictate the optimality of schemes. Such insights can inform policy-makers with tailored and implementable data-driven recommendations.

People with genetic kidney diseases on kidney replacement therapy have different clinical outcomes compared to people with other kidney diseases

Despite increasing awareness of genetic kidney disease prevalence, there is limited population-level information about long term outcomes of people with genetic kidney disease receiving kidney replacement therapy. This analysis included people who commenced kidney replacement therapy between 1989 and 2020 as recorded in the Australian and New Zealand Dialysis and Transplant registry. Genetic kidney diseases were subclassified as majority and minority monogenic. Non-genetic kidney diseases were included as the comparator group. Primary outcome measures were 10-year mortality and 10-year graft failure. Cox proportional hazard regression were used to calculate unadjusted and adjusted hazard ratios (AHRs) for primary outcomes. There were 59,231 people in the dialysis subgroup and 21,860 people in the transplant subgroup. People on dialysis with genetic kidney diseases had reduced 10-year mortality risk (majority monogenic AHR: 0.70, 95% CI 0.66–0.76; minority monogenic AHR 0.86, 95% CI 0.80–0.92). This reduced 10-year mortality risk continued after kidney transplantation (majority monogenic AHR: 0.82, 95% CI 0.71–0.93; minority monogenic AHR 0.80, 95% CI 0.68–0.95). Majority monogenic genetic kidney diseases were associated with reduced 10-year graft failure compared to minority monogenic genetic kidney diseases and other kidney diseases (majority monogenic AHR 0.69, 95% CI 0.59–0.79). This binational registry analysis identified that people with genetic kidney disease have different mortality and graft failure risks compared to people with other kidney diseases.

Wastewater-based SARS-CoV-2 surveillance and sequencing

Though most often associated with poliovirus surveillance, wastewater-based surveillance (WBS) can be employed for viruses shed in human excreta (faeces, urine, skin, sputum, blood) that may enter the wastewater system, including SARS-CoV-2. WBS has been widely adopted during the COVID-19 pandemic, to complement clinical surveillance in monitoring community burden and implementing timely public health interventions. As wastewater is a non-biased, composite sample, it can provide population-level health information in near real-time, in a cost-effective manner compared to similarly scaled clinical surveillance. In many instances, data gathered from wastewater, including viral loads (quantified by RT-qPCR) and variant detections (determined through partial or whole genome sequencing), have been predictive of what is observed eventually in clinical cases. Newly emergent lineages, including the recent BA.2.86 variant, can and have been detected in wastewater samples prior to their detection in clinical specimens. There remain many challenges to wastewater genomic analysis including the presence of RT-qPCR inhibitors, degraded nucleic acid and the lack of consistent or standardised methodology between reporting labs. The wide adoption of WBS practices provides an excellent opportunity to expand this method for surveillance of other pathogens of public health importance. Herein, a broad overview of the WBS field will be provided including discussion on its advantages and applications, challenges, and how it is being utilised to characterise circulating SARS-CoV-2 lineages through sequencing.

Multiplexing PCR allows the identification of within-species genetic diversity in ancient eDNA.

Sedimentary ancient DNA (sedaDNA) has rarely been used to obtain population-level data due to either a lack of taxonomic resolution for the molecular method used, limitations in the reference material or inefficient methods. Here, we present the potential of multiplexing different PCR primers to retrieve population-level genetic data from sedaDNA samples. Vaccinium uliginosum (Ericaceae) is a widespread species with a circumpolar distribution and three lineages in present-day populations. We searched 18 plastid genomes for intraspecific variable regions and developed 61 primer sets to target these. Initial multiplex PCR testing resulted in a final set of 38 primer sets. These primer sets were used to analyse 20 lake sedaDNA samples (11,200 cal. yr BP to present) from five different localities in northern Norway, the Alps and the Polar Urals. All known V. uliginosum lineages in these regions and all primer sets could be recovered from the sedaDNA data. For each sample on average 28.1 primer sets, representing 34.15 sequence variants, were recovered. All sediment samples were dominated by a single lineage, except three Alpine samples which had co-occurrence of two different lineages. Furthermore, lineage turnover was observed in the Alps and northern Norway, suggesting that present-day phylogeographical studies may overlook past genetic patterns. Multiplexing primer is a promising tool for generating population-level genetic information from sedaDNA. The relatively simple method, combined with high sensitivity, provides a scalable method which will allow researchers to track populations through time and space using environmental DNA.

Drug utilization studies in Turkiye: A systematic review.

Drug utilization studies (DUS) provide a framework for drug utilization at the national or targeted population level and important information on unmet medical needs, particularly in assessing the rationality of drug use. We aimed to systematically review DUS conducted in Turkiye. We examined 162 DUS with an accessible full-text, published as "research articles" and conducted in Turkiye between 2000 and 2021 using medical records and prescription data. We included English or Turkish papers with English abstracts. We examined the scientific characteristics of the publications, source of the data, place/time of collection, research designs, and studied drug groups. We found that 79.6% of articles were in English, 45.1% were listed in SCI/SCIE, and 63.0% were on the WOS platform with 3.5 (interquartile range: 1-15) citations. The mean study period and publication time were 2.9±3.1 and 2.9±2.1 years, respectively. The highest number of studies (17.9%) were published in 2021 and (26.5%) were conducted nationwide. We identified that 93.8% of the studies had retrospective design, 67.8% were conducted in secondary/tertiary health-care institutions, and 54.9% used direct hospital data. We detected that 68.5% of the studies were conducted on the general population, 19.1% on adults, 12.4% on children, and 44.4% were antibiotic oriented. Our study showed that a significant portion of the DUS, the trend of which has gained momentum in recent years, was antibiotic focused and conducted with a retrospective design from hospital-based data collected on the general patient population. This situation points to the necessity of expanding the existing DUS range by effectively using the new advantages provided by medical record databases and conducting more DUS that can provide critical clues for specific patients and drug groups.

OP22 Benchmarking Of Population-Based Childhood Cancer Survival By Toronto Stage: Know The Differences To Propose Effective Interventions

IntroductionPediatric cancers are rare tumors, heterogeneous in location and biologically very different from adult cancers. Documented survival variation across European countries and Italian regions shows that there is still room for further improvement by reducing inequalities. We aim to understand why there are differences in survival. The BENCHISTA-ITA project (National Benchmarking of Childhood Cancer Survival by Stage at diagnosis), that is the Italian twin project of the International BENCHISTA, collects stage at diagnosis of solid pediatric tumors, according to the Toronto Guidelines. We will compare how far the cancer has spread at diagnosis and test if differences in tumor stage explain any survival differences between Italian regions.MethodsThe project study involved the stage distribution and the survival of 9 pediatric solid tumors diagnosed between 2013 and 2017 in Italy. All patients therefore had at least 3 years of follow-up in 2021 for life-stage definition. The study involves the identification of all new diagnoses of cancer, evaluation of the clinical documentation of cases eligible for research, and international classification and coding. Analyses of stage distribution and survival rates for each tumor type will be described.ResultsData from 35 population-based cancer registries from 18 out of 20 Italian regions were collected covering about 84 percent of the Italian child population. In particular, data on: imaging/examination performed before any treatment; source used for staging; primary treatment defined as given within one year from diagnosis; relapse/ recurrence/ progression; follow up and status of life. The study tested the applicability of the Toronto Guidelines as a tool to obtain population-level comparable stage information for childhood cancers. There were 1,343 cases collected (242 Neuroblastoma, 124 Wilms Tumour, 145 Medulloblastoma, 148 Osteosarcoma, 135 Ewing sarcoma, 115 Rhabdomyososarcoma, 54 Ependymoma, 47 Retinoblastoma, 333 Astrocytoma). Toronto stage could be assigned in more than 90 percent in the majority of tumors. Tumors in which it was more difficult to assign the stage using the Toronto staging guidelines were ependymoma, astrocytoma, and retinoblastoma. It was easier to retrieve data for patients in the 0-14 years of age range than adolescents (14-18 years). Differences in stage distribution and survival differences between regional grouping were presented.ConclusionsThe Italian BENCHISTA project, improving the connection between pediatric cancer registries, aims to improve care of children with cancer across the nation, reducing possible disparities.The wide adoption of the Toronto Guidelines will facilitate international comparative incidence studies, strengthen the interpretation of survival data, and contribute to more appropriate solutions to improve childhood cancer outcomes.

Three novel methods for determining motor threshold with transcranial magnetic stimulation outperform conventional procedures.

Objective. Thresholding of neural responses is central to many applications of transcranial magnetic stimulation (TMS), but the stochastic aspect of neuronal activity and motor evoked potentials (MEPs) challenges thresholding techniques. We analyzed existing methods for obtaining TMS motor threshold and their variations, introduced new methods from other fields, and compared their accuracy and speed.Approach. In addition to existing relative-frequency methods, such as the five-out-of-ten method, we examined adaptive methods based on a probabilistic motor threshold model using maximum-likelihood (ML) or maximuma-posteriori(MAP) estimation. To improve the performance of these adaptive estimation methods, we explored variations in the estimation procedure and inclusion of population-level prior information. We adapted a Bayesian estimation method which iteratively incorporated information of the TMS responses into the probability density function. A family of non-parametric stochastic root-finding methods with different convergence criteria and stepping rules were explored as well. The performance of the thresholding methods was evaluated with an independent stochastic MEP model.Main Results. The conventional relative-frequency methods required a large number of stimuli, were inherently biased on the population level, and had wide error distributions for individual subjects. The parametric estimation methods obtained the thresholds much faster and their accuracy depended on the estimation method, with performance significantly improved when population-level prior information was included. Stochastic root-finding methods were comparable to adaptive estimation methods but were much simpler to implement and did not rely on a potentially inaccurate underlying estimation model.Significance. Two-parameter MAP estimation, Bayesian estimation, and stochastic root-finding methods have better error convergence compared to conventional single-parameter ML estimation, and all these methods require significantly fewer TMS pulses for accurate estimation than conventional relative-frequency methods. Stochastic root-finding appears particularly attractive due to the low computational requirements, simplicity of the algorithmic implementation, and independence from potential model flaws in the parametric estimators.

Environmental DNA reveals the genetic diversity and population structure of an invasive species in the Laurentian Great Lakes

Environmental DNA (eDNA) has been established as a noninvasive and efficient approach to sample genetic material from aquatic environments. Although most commonly used to determine species presence and measure biodiversity, eDNA approaches also hold great potential to obtain population-level genetic information from water samples. In this study, we sequenced a panel of multiallelic microsatellite markers from filtered water and fish tissue samples to uncover patterns of intraspecific diversity in the freshwater Round Goby (Neogobius melanostomus) across their invaded range in the Laurentian Great Lakes region. Although we found that the concentration of nuclear eDNA is lower than mitochondrial eDNA, we nonetheless detected over two-thirds of all nuclear alleles identified from genotyped tissues in our eDNA samples, with the greatest recovery of common alleles in the population. Estimates of allele frequencies and genetic variability within and between populations were detected from eDNA in patterns that were consistent with individual tissue-based estimates of genetic diversity and differentiation. The strongest genetic differentiation in both eDNA and tissues exists in an isolation by distance pattern. Our study demonstrates the potential for eDNA-based approaches to characterize key population parameters required to effectively monitor, manage, or sustain aquatic species.

Mapping spatial morbidity patterns for bronchiolitis related to socioeconomic estimators: A spatial epidemiology approach to identify health disparities in Puerto Madryn, Argentina.

To describe the frequency of hospitalizations of infants under 1 year of age with bronchiolitis in Puerto Madryn, Argentina, and to study the spatial distribution of cases throughout the city in relation to socioeconomic indicators. To visualize and better understand the underlying processes behind the local manifestation of the disease by creating a vulnerability map of the city. We performed a cross-sectional study of all patients discharged for bronchiolitis from the local public Hospital in 2017, considering length of hospital stay, readmission rate, patient age, home address and socioeconomic indicators (household overcrowding). To understand the local spatial distribution of the disease and its relationship to overcrowding, we used GIS and Moran's global and local spatial autocorrelation indices. The spatial distribution of bronchiolitis cases was not random, but significantly aggregated. Of the 120 hospitalized children, 100 infants (83.33%) live in areas identified as having at least one unsatisfied basic need (UBN). We found a positive and statistically significant relationship between frequency of cases and percentage of overcrowded housing by census radius. A clear association was found between bronchiolitis and neighborhoods with UBNs, and overcrowding is likely to be a particularly important explanatory factor in this association. By combining GIS tools, spatial statistics, geo-referenced epidemiological data, and population-level information, vulnerability maps can be created to facilitate visualization of priority areas for development and implementation of more effective health interventions. Incorporating the spatial and syndemic perspective into health studies makes important contributions to the understanding of local health-disease processes.

Co-Designing a Farm Safety Gamified Educational Resource With Secondary School Students and Their Teachers: Qualitative Study Protocol

Unintentional injuries are a leading cause of preventable harm among adolescents. Adolescents also experience an increased risk of farm injury, and in Australia, injury-related farm fatalities among adolescents have remained largely unchanged over the past two decades. A third of all incidents involve farm visitors, indicating the need for population-level safety information. This project uses qualitative data to inform a co-design process with adolescents, and their teachers, to develop a game-based farm injury prevention online educational resource. This protocol describes the multi-phase co-design project. Focus group discussions regarding farm injury prevention will be held with students (Year 7 & 8; ∼12–14 years of age) and teachers at high schools with an agricultural focus across two Australian states. Inductive thematic analysis of discussion transcripts, and analysis of farm injury data, will inform the development of the modules and content of the game. User experience testing of the prototype will form the final phase of the project. This process is supported by a Stakeholder Advisory Group, which includes representatives of youth farming organisations, agricultural educators, and national child safety organisations. This group will assist in interpretation and dissemination of findings and promoting the resultant educational resource in schools. Ethical approval has been granted by the University of New South Wales Human Research Ethics Committee. Results will be disseminated through peer-reviewed publications, mass media releases, academic conferences, and the agricultural education sector in Australia via the stakeholder advisory group. This study will provide useful insights into co-designing injury prevention resources for adolescents using gamification and result in a co-designed farm injury prevention educational resource for schools and the general community via mobile and web-based applications.

MORBIDITY AND MORTALITY OF BINTURONGS (ARCTICTIS BINTURONG) IN UNITED STATES ZOOLOGICAL INSTITUTIONS (1986-2019).

Veterinary literature on diseases in binturong (Arctictis binturong) is often limited to case series or reports without population-level information. Morbidity and mortality data were collected from North American institutions through survey completion or submission of medical records. Responses included information about 74 individuals (37 males, 30 females, and 7 unknown neonates) representing 22 institutions, from 1986 to 2019. Antemortem data were available from 39 individuals, and postmortem data were available from 53 individuals. Eighteen individuals had both antemortem and postmortem records available. Age (mean ± SD) at death for adults (n = 41) was 15.2 ± 4.3 yr. Morbidity events were summarized by affected organ system; 160 events were reported. The systems with the most frequently reported events were gastrointestinal (33%; 53/160), integumentary (19%; 31/160), urinary (12%; 20/160), and musculoskeletal (19 [12%] of 160). Excluding neonates, primary causes of mortality included neoplasia (51%; 21/41), infectious or inflammatory diseases (24%; 10/41), and cardiovascular disease (17%; 7/41). Neoplasms (51%; 21/41) confirmed on histopathology included renal adenocarcinoma (47%; 10/21); mammary carcinoma (14%; 3/21); pancreatic islet cell carcinoma (2 [10%] of 21); and single instances of multicentric lymphoma, uterine carcinoma, and submucosal urethral adenoma. There were three additional cases of presumed neoplasia without histopathologic confirmation; masses were detected in the liver, heart base, and pancreas. Metastases were reported in 15 (71%) of 21 neoplasms. Although neoplasia and cardiovascular disease were common causes of mortality, they were rarely diagnosed antemortem. Neoplasia was often malignant and generally diagnosed after metastasis. Preventive medicine protocols with improved renal and cardiovascular evaluation are warranted and may result in earlier detection of subclinical disease in binturong.

An extension of estimating equations to model longitudinal medical cost trajectory with Medicare claims data linked to SEER cancer registry

Insurance claims’ data is an increasingly important health policy research resource, given its longitudinal assessment of cancer care clinical outcomes. Population-level information on medical cost trajectory from disease diagnosis to terminal events, such as death, specifically interests policy makers. Estimating the mean cost trajectory has statistical challenges. The shape of the trajectory is usually highly nonlinear with varying durations, depending on the diagnosis-to-death population time distribution. The terminal event may be right censored, resulting in missing subsequent costs. Medical costs often have skewed distributions with zero inflation and heteroscedasticity which may not fit well with the commonly used parametric family of distributions. In this paper we propose a flexible semiparametric model to address challenges without imposing a cost data distributional assumption. The estimation procedure is based on generalized estimating equations with censored covariates. The proposed model adopts a bivariate surface that quantifies the interrelationship between longitudinal medical costs and survival, and results in the nonlinear population mean cost trajectories given survival time. We develop a novel generalized estimating equations algorithm to accommodate covariates subject to right censoring without fully specifying the joint distribution of the cost and survival data. We provide theoretical and simulation-based justification for the proposed approach and apply the methods to estimate prostate cancer patient cost trajectories from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database.

Conservation Collections at the National Botanic Garden of Nepal – The Franklinia Taxus Project

Three species of Taxus occur in Nepal T. contorta, T. maireii and Taxus wallichiana,. All are under pressure from collection for medicinal use, habitat destruction and changing land use. In 2017 and 2018 fieldwork was carried out to collect seed, herbarium specimens, cuttings and information to improve protection of these species, funded by Fondation Franklinia. Collections were made for propagation, herbarium and molecular studies. Population level Information was also gathered to make national assessments for these species. This article traces the status of the living collections in the National Botanic Garden of Nepal (NBG) and the assessments made by the team comprising staffs of Department of Plant Resources (DPR) and Nepal Academy of Science and Technology (NAST) and Freelance botanist. Reference is made to work done prior to 2017 on the taxonomy and distribution of the species and which enabled efficient fieldwork thereafter. The establishment of a conservation collection at NBG provides a basis for research into yew species in Nepal and highlights the benefits of internationally collaborative projects to maintain conservation collections of threatened species in their country of origin.

A system in crisis: exploring how recent emergency department closures influence potential access to emergency care in Ontario.

Access to emergency medical care in Ontario has been under stress, mainly due to a lack of human resources (staffing of nurses and doctors). Over the past year, several emergency departments in Ontario have closed. Some of these closures are nightly, while others have closed for weeks at a time, leaving Ontario residents without access to emergency medical care which can lead to poor or more severe outcomes. The purpose of this paper was to examine how closures of ED's in Ontario have influenced potential access to emergency medical care. We performed population-level geographic information systems (GIS)-based analysis of potential access to ED hospitals in Ontario. The number of people with access to an ED was calculated when all ED's in Ontario were open, then recalculated with the 14 ED closures. Access was defined by ground travel with 30min, 45min, and 60min travel times used for analysis. Differences in the number of people at the census block level who potentially lost access were compiled and examined by census subdivision. If all 14 ED's had closed at the same time, there would be 35,808 people at 30min, 15,018 at 45min, and 12,131 at 60min travel times in Ontario who lost access to ED care. Certain areas of the province saw more significant decreases in ED access. At 45min travel times, nearly 2000 people in Central Frontenac lost access (44% of population), while 7298 people in Cochrane (North Part) lost access (20% of population). ED closures have led to decreases in potential access to emergency care for predominantly rural populations. Health human resource recovery strategies must focus on areas where lack of overlap exists.

The role of culture in firm-bank matching

We assemble a unique dataset containing population-level information on loan applications in a region hosting two cultural groups to study the role of culture in firm borrowing decisions. We find that firms are more likely to apply for loans from culturally close banks. This effect is stronger for opaque firms, but not for less performing firms, indicating that firms do not expect preferential treatment from same-culture banks. Loan applications to culturally distant banks increase sharply with firms’ size and age, suggesting a role of information asymmetry in firm-bank matching. In contrast, we find no effect of cultural proximity on loan supply. Overall, our results show that demand-side factors play a key role in the formation of same-culture lending relationships.