Trends in opioid use following balloon kyphoplasty or vertebroplasty for the treatment of vertebral compression fractures.

This retrospective analysis of insurance claims evaluated real-world trends in prescription fills among patients treated with balloon kyphoplasty (N = 6,656) or vertebroplasty (N = 2,189) following diagnosis of vertebral compression fracture. Among those with evidence of opioid use, nearly half of patients discontinued or reduced prescription fills relative to pre-operative levels. INTRODUCTION: Vertebral compression fractures (VCF) are associated with debilitating pain, spinal misalignment, increased mortality, and increased healthcare-resource utilization in elderly patients. This study evaluated the effect of balloon kyphoplasty (BKP) or vertebroplasty (VP) on post-procedure opioid prescription fills and payer costs in patients with VCF. METHODS: This was a retrospective analysis of a large, nationally representative insurance-claims database. Clinical characteristics, opioid prescription patterns, and payer costs for subjects who underwent either BKP or VP to treat VCF were evaluated beginning 6 months prior to surgery through 7-month follow-up that included a 30-day, postoperative medication washout. Patient demographics, changes in opioid utilization, and payer costs were analyzed. RESULTS: A total of 8,845 patients met eligibility criteria (75.3% BKP and 24.7% VP) with a mean of age 77 and 74% female. Among the 75% of patients who used opioids, 48.7% of patients discontinued opioid medication and 8.4% reduced prescription fills versus preoperative baseline. Patients who reduced or discontinued prescriptions exhibited a decrease in all-cause payer costs relative to pre-intervention levels, which was a significantly greater change relative to patients with no change, increase, or new start of opioids. CONCLUSIONS: Interventional treatment for VCF was associated with decreased or discontinued opioid prescription fills and reduced payer costs in follow-up in a significant proportion of the study population. Reduction of opioid-based harms may represent a previously unrecognized benefit of vertebral augmentation for VCF, especially in this elderly and medically fragile population.

Information Gathering in Investigative and Medical Interviewing: Drawing Parallels Across Contexts.

Information gleaned from a patients' medical history is a core determinant of a medical diagnosis. Accurate and effective history-taking is, therefore, a foundational skill for medical practitioners and is introduced early in medical training. Recognizing and developing the skills of effective medical interviewing is an ongoing challenge for medical students and experienced clinicians alike. Important parallels exist between the information gathering skills required in medicine and health, and those required in investigative interviewing. Qualitative interviews were conducted with 19 experienced medical professionals from a range of specialty areas. They were asked about the role of the medical interview in their discipline, and about challenges they experience when gathering information from patients. Both theory-driven and grounded-theory approaches were used in combination to identify common themes. The interviews were rich with themes including approaches to introductory phases of the interview, eliciting a narrative account, and several topics that specifically paralleled issues in interviewing of vulnerable witnesses. We explore these themes through a lens of investigative interviewing by applying the knowledge of effective interviewing skills and structures to the data gained from the medical context. In general, themes indicated that there are numerous parallels to information gathering approaches in both contexts. As such, there may be scope for medical education to adopt some of the training techniques employed in the investigative interviewing field. Further, it is hoped that the present findings be used to spark an interdisciplinary conversation about communication from which both sides can learn.

What a Difference a Stochastic Process Makes: Epidemiological-Based Real Options Models of Optimal Treatment of Disease.

The real options approach has been used within environmental economics to investigate the impact of uncertainty on the optimal timing of control measures to minimise the impacts of invasive species, including pests and diseases. Previous studies typically model the growth in infected area using geometric Brownian motion (GBM). The advantage of this simple approach is that it allows for closed form solutions. However, such a process does not capture the mechanisms underlying the spread of infection. In particular the GBM assumption does not respect the natural upper boundary of the system, which is determined by the maximum size of the host species, nor the deceleration in the rate of infection as this boundary is approached. We show how the stochastic process describing the growth in infected area can be derived from the characteristics of the spread of infection. If the model used does not appropriately capture uncertainty in infection dynamics, then the excessive delay before treatment implies that the full value of the option to treat is not realised. Indeed, when uncertainty is high or the disease is fast spreading, ignoring the mechanisms of infection spread can lead to control never being deployed. Thus the results presented here have important implications for the way in which the real options approach is applied to determine optimal timing of disease control given uncertainty in future disease progression.

Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia.

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa's largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different 'what-if' scenarios of disease outbreaks in potential source countries in different months of the wheat season.

Determination of the absolute intensity of the 1205 keV γ-ray emission from 91Y.

A radiochemically pure solution of 91Y was produced by the thermal neutron fission of 235U followed by successive chemical separations to remove fission product impurities. The gamma emission rate of the 91Y 1205 keV gamma was measured using multiple high purity germanium gamma spectrometers previously calibrated for counting efficiency using a certificated mixed nuclide gamma standard. The activity concentration of the 91Y was subsequently standardised by liquid scintillation counting. From the combination the activity concentration and gamma emission intensity, the absolute intensity of the 1205 keV gamma emission was derived as 0.2297(39)%. This data agrees within the quoted uncertainties with the absolute intensity of 0.26(4)% published in nuclear data sheets A=91 (Baglin, 2013), but reduces the uncertainty by an order of magnitude.

Percolation-based risk index for pathogen invasion: application to soilborne disease in propagation systems.

Propagation systems for seedling growth play a major role in agriculture, and in notable cases (such as organic systems), are under constant threat from soil and seedborne fungal plant pathogens such as Rhizoctonia solani or Pythium spp. Yet, to date little is known that links the risk of disease invasion to the host density, which is an agronomic characteristic that can be readily controlled. We introduce here, for the first time in an agronomic system, a percolation framework to analyze the link. We set up an experiment to study the spread of the ubiquitous fungus R. solani in replicated propagation systems with different planting densities, and fit a percolation-based epidemiological model to the data using Bayesian inference methods. The estimated probability of pathogen transmission between infected and susceptible plants is used to calculate the risk of invasion. By comparing the transmission probability and the risk values obtained for different planting densities, we are able to give evidence of a nonlinear relationship between disease invasion and the inter-plant spacing, hence to demonstrate the existence of a spatial threshold for epidemic invasion. The implications and potential use of our methods for the evaluation of disease control strategies are discussed.

Rational design of a survey protocol for avocado sunblotch viroid in commercial orchards to demonstrate pest freedom.

Avocado sunblotch viroid (ASBVd) is a subcellular pathogen of avocado that reduces yield from a tree, diminishes the appearance of the fruit by causing unsightly scarring and impedes trade because of quarantine conditions that are imposed to prevent spread of the pathogen via seed-borne inoculum. For countries where ASBVd is officially reported, permission to export fruit to another country may only be granted if an orchard can be demonstrated to be a pest free production site. The survey requirements to demonstrate pest freedom are usually defined in export protocols that have been mutually agreed upon by the trading partners. In this paper, we introduce a flexible statistical protocol for use in optimizing sampling strategies to establish pest free status from ASBVd in avocado orchards. The protocol, which is supported by an interactive app, integrates statistical considerations of multistage sampling of trees in orchards with a RT-qPCR assay allowing for detection of infection in pooled samples of leaves taken from multiple trees. While this study was motivated by a need to design a survey protocol for ASBVd, the theoretical framework and the accompanying app have broader applicability to a range of plant pathogens in which hierarchical sampling of a target population is coupled with pooling of material prior to diagnosis.

Prominent effect of soil network heterogeneity on microbial invasion.

Using a network representation for real soil samples and mathematical models for microbial spread, we show that the structural heterogeneity of the soil habitat may have a very significant influence on the size of microbial invasions of the soil pore space. In particular, neglecting the soil structural heterogeneity may lead to a substantial underestimation of microbial invasion. Such effects are explained in terms of a crucial interplay between heterogeneity in microbial spread and heterogeneity in the topology of soil networks. The main influence of network topology on invasion is linked to the existence of long channels in soil networks that may act as bridges for transmission of microorganisms between distant parts of soil.

Time-dependent infectivity and flexible latent and infectious periods in compartmental models of plant disease.

Compartmental models have become the dominant theoretical paradigm in mechanistic modeling of plant disease and offer well-known advantages in terms of analytic tractability, ease of simulation, and extensibility. However, underlying assumptions of constant rates of infection and of exponentially distributed latent and infectious periods are difficult to justify. Although alternative approaches, including van der Plank's seminal discrete time model and models based on the integro-differential formulation of Kermack and McKendrick's model, have been suggested for plant disease and relax these unrealistic assumptions, they are challenging to implement and to analyze. Here, we propose an extension to the susceptible, exposed, infected, and removed (SEIR) compartmental model, splitting the latent and infection compartments and thereby allowing time-varying infection rates and more realistic distributions of latent and infectious periods to be represented. Although the model is, in fact, more general, we specifically target plant disease by demonstrating how it can represent both the van der Plank model and the most commonly used variant of the Kermack and McKendrick (K & M) model (in which the infectivity response is delay Gamma distributed). We show how our reformulation retains the numeric and analytic tractability of SEIR models, and how it can be used to replicate earlier analyses of the van der Plank and K & M models. Our reformulation has the advantage of using elementary mathematical techniques, making implementation easier for the nonspecialist. We show a practical implication of these results for disease control. By taking advantage of the easy extensibility characteristic of compartmental models, we also investigate the effects of including additional biological realism. As an example, we show how the more realistic infection responses we consider interact with host demography and lead to divergent invasion thresholds when compared with the "standard" SEIR model. An ever-increasing number of analyses purportedly extract more biologically realistic invasion thresholds by adding additional biological detail to the SEIR model framework; we contend that our results demonstrate that extending a model that has such a simplistic representation of the infection dynamics may not, in fact, lead to more accurate results. Therefore, we suggest that modelers should carefully consider the underlying assumptions of the simplest compartmental models in their future work.

Culturally and linguistically diverse students in health professional programs: an exploration of concerns and needs.

INTRODUCTION: Cultural diversity among students in tertiary institutions in Australia and globally has increased rapidly in the last decade, and is continuing to do so. METHODS: Focus groups were held at the University of Newcastle, NSW to: (1) examine the specific needs of international students in the Master of Pharmacy, Bachelor of Medicine and Bachelor of Nursing programs in relation to language and cultural considerations and (2) to understand the attitudes of domestic students to the cultural issues faced among their peers. The project explored these issues with the intention to inform curricula changes to accommodate the needs of culturally and linguistically diverse students. RESULTS: The key themes emerging from international students were: difficulties in spoken language, differences in professional roles and expectations, differences in methods of learning, inadequate social interaction outside the classroom and acceptance of differences in cultural and religious practices. The domestic student views reinforced the comments from international students both in regard to social interaction and in regard to participation in class discussions. Although local students were interested in learning from international students about their culture and religious beliefs, there were limited initiatives from both sides. DISCUSSION: There is a need for tertiary institutions that benefit economically from increasing the numbers of international students to help them to study and live in a new environment. Assistance needs to go beyond learning the English language to helping students understand its use in a professional context (health terminology and slang used by patients), the nuances of the health professional disciplines in a western society, the approach to study and problem-based learning styles and skills to assist with social interaction. The results of the present exploration have led to a series of proposed actions for the University of Newcastle. These recommendations are applicable to any "Western" teaching institution with a large number of international students from developing countries enrolled in their health programs.

Determination of the 161Tb half-life.

There is significant interest in the use of terbium radioisotopes for applications in cancer therapy and diagnosis. Of these, 161Tb, as a medium energy beta-emitter, is being investigated as a potential alternative to 177Lu. The relatively high proportion of conversion electron and Auger electron emissions per decay make 161Tb an attractive targeted therapeutic. As a product of nuclear fission, 161Tb is also of importance to nuclear forensics. The standard uncertainty of the current evaluated half-life of 6.89(2) d contributes significantly to the standard uncertainty of any decay corrected activity determination made. Furthermore, the accuracy of this evaluated half-life has been called into question by measurements reported in 2020 at the Institute of Radiation Physics (IRA), Switzerland, who reported a half-life of 6.953(2) d. In the current work, the half-life of the 161Tb ground state decay has been measured at three independent laboratories located in the United Kingdom and the United States of America for a total of six determinations using three independent measurement techniques; gamma-ray spectrometry, ionisation chamber measurement and liquid scintillation counting. The half-life determined for 161Tb of 6.9637(29) d confirms the observed 1% relative increase observed by IRA, though the reported half-lives in this work and at IRA are significantly different (ζ-score = 3.1).

Spatial sampling to detect an invasive pathogen outside of an eradication zone.

Invasive pathogens are known to cause major damage to the environments they invade. Effective control of such invasive pathogens depends on early detection. In this paper we focus on sampling with the aim of detecting an invasive pathogen. To that end, we introduce the concept of optimized spatial sampling, using spatial simulated annealing, to plant pathology. It has been mathematically proven (15) that this optimization method converges to the optimum allocation of sampling points that give the largest detection probability. We show the benefits of the method to plant pathology by (i) first illustrating that optimized spatial sampling can easily be applied for disease detection, and then we show that (ii) combining it with a spatially explicit epidemic model, we can develop optimum sample schemes, i.e., optimum locations to sample that maximize the probability of detecting an invasive pathogen. This method is then used as baseline against which other sampling methods can be tested for their accuracy. For the specific example case of this paper, we test (i) random sampling, (ii) stratified sampling as well as (iii) sampling based on the output of the simulation model (using the most frequently infected hosts as sample points), and (iv) sampling the hosts closest to the outbreak point.

Wheat rust epidemics damage Ethiopian wheat production: A decade of field disease surveillance reveals national-scale trends in past outbreaks.

Wheat rusts are the key biological constraint to wheat production in Ethiopia-one of Africa's largest wheat producing countries. The fungal diseases cause economic losses and threaten livelihoods of smallholder farmers. While it is known that wheat rust epidemics have occurred in Ethiopia, to date no systematic long-term analysis of past outbreaks has been available. We present results from one of the most comprehensive surveillance campaigns of wheat rusts in Africa. More than 13,000 fields have been surveyed during the last 13 years. Using a combination of spatial data-analysis and visualization, statistical tools, and empirical modelling, we identify trends in the distribution of wheat stem rust (Sr), stripe rust (Yr) and leaf rust (Lr). Results show very high infection levels (mean incidence for Yr: 44%; Sr: 34%; Lr: 18%). These recurrent rust outbreaks lead to substantial economic losses, which we estimate to be of the order of 10s of millions of US-D annually. On the widely adopted wheat variety, Digalu, there is a marked increase in disease prevalence following the incursion of new rust races into Ethiopia, which indicates a pronounced boom-and-bust cycle of major gene resistance. Using spatial analyses, we identify hotspots of disease risk for all three rusts, show a linear correlation between altitude and disease prevalence, and find a pronounced north-south trend in stem rust prevalence. Temporal analyses show a sigmoidal increase in disease levels during the wheat season and strong inter-annual variations. While a simple logistic curve performs satisfactorily in predicting stem rust in some years, it cannot account for the complex outbreak patterns in other years and fails to predict the occurrence of stripe and leaf rust. The empirical insights into wheat rust epidemiology in Ethiopia presented here provide a basis for improving future surveillance and to inform the development of mechanistic models to predict disease spread.

Development of a reference material for analysing naturally occurring radioactive material from the steel industry.

Accurate measurement of naturally occurring radionuclides in blast furnace slag, a by-product of the steel industry, is required for compliance with building regulations where it is often used as an ingredient in cement. A matrix reference blast furnace slag material has been developed to support traceability in these measurements. Raw material provided by a commercial producer underwent stability and homogeneity testing, as well as characterisation of matrix constituents, to provide a final candidate reference material. The radionuclide content was then determined during a comparison exercise that included 23 laboratories from 14 countries. Participants determined the activity per unit mass for 226Ra, 232Th and 40K using a range of techniques. The consensus values obtained from the power-moderated mean of the reported participant results were used as indicative activity per unit mass values for the three radionuclides: A0(226Ra) = 106.3 (34) Bq·kg-1, A0(232Th) = 130.0 (48) Bq·kg-1 and A0(40K) = 161 (11) Bq·kg-1 (where the number in parentheses is the numerical value of the combined standard uncertainty referred to the corresponding last digits of the quoted result). This exercise helps to address the current shortage of NORM industry reference materials, putting in place infrastructure for production of further reference materials.

Periodicity in host availability does not account for evolutionary branching as observed in many plant pathogens: an application to Gaeumannomyces graminis var. tritici.

Periodicity in host availability is common in agricultural systems. Although it is known to have profound effects on plant pathogen abundance, the evolutionary consequences of periodicity for the pathogen population have not previously been analyzed. An epidemiological model incorporating periodic absence of the host crop is combined with the theory of adaptive dynamics to determine whether or not seasonality in host presence plays a role in the occurrence of evolutionary branching, leading to coexisting yet genetically distinct pathogen phenotypes. The study is motivated and illustrated by the specific example of take-all disease of wheat, caused by the pathogen Gaeumannomyces graminis var. tritici, for which two coexisting but genetically distinct types and a trade-off related to seasonality in host presence have been identified. Numerical simulations are used to show that a trade-off between the pathogen transmission rate and the survival of the pathogen between cropping seasons cannot account for the evolutionary branching observed in many pathogens. Model elaborations show that this conclusion holds for a broad range of putative mechanisms. Although the analysis is motivated and illustrated by the specific example of take-all of wheat, the results apply to a broad range of pathogens.

The effect of landscape pattern on the optimal eradication zone of an invading epidemic.

A number of high profile eradication attempts on plant pathogens have recently been attempted in response to the increasing number of introductions of economically significant nonnative pathogen species. Eradication programs involve the removal of a large proportion of a host population and can thus lead to significant social and economic costs. In this paper we use a spatially explicit stochastic model to simulate an invading pathogen and show that it is possible to identify an optimal control radius, i.e., one that minimizes the total number of hosts removed during an eradication campaign that is effective in eradicating the pathogen. However, by simulating the epidemic and eradication processes in multiple landscapes, we demonstrate that the optimal radius depends critically on landscape pattern (i.e., the spatial configuration of hosts within the landscape). In particular, we find that the optimal radius, and also the number of host removals associated with it, increases with both the level of aggregation and the density of hosts in the landscape. The result is of practical significance and demonstrates that the location of an invading epidemic should be a key consideration in the design of future eradication strategies.

Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic.

Forecasting whether or not initial reports of disease will be followed by a severe epidemic is an important component of disease management. Standard epidemic risk estimates involve assuming that infections occur according to a branching process and correspond to the probability that the outbreak persists beyond the initial stochastic phase. However, an alternative assessment is to predict whether or not initial cases will lead to a severe epidemic in which available control resources are exceeded. We show how this risk can be estimated by considering three practically relevant potential definitions of a severe epidemic; namely, an outbreak in which: (i) a large number of hosts are infected simultaneously; (ii) a large total number of infections occur; and (iii) the pathogen remains in the population for a long period. We show that the probability of a severe epidemic under these definitions often coincides with the standard branching process estimate for the major epidemic probability. However, these practically relevant risk assessments can also be different from the major epidemic probability, as well as from each other. This holds in different epidemiological systems, highlighting that careful consideration of how to classify a severe epidemic is vital for accurate epidemic risk quantification.

Epidemiological analysis of take-all decline in winter wheat.

Take-all dynamics within crops differing in cropping history (the number of previous consecutive wheat crops) were analyzed using an epidemiological model to determine the processes affected during take-all decline. The model includes terms for primary infection, secondary infection, inoculum decay, and root growth. The average rates of root production did not vary with cropping history. The force of primary infection increased from a low level in 1st wheat crops, to a maximum in 2nd to 4th wheat crops, and then to intermediate levels thereafter. The force of secondary infection was low but increased steadily during the season in first wheat crops, was delayed but rose and fell sharply in 2nd to 4th wheat crops, and for 5th and 7th wheat crops returned to similar dynamics as that for 1st wheat crops. Chemical seed treatment with silthiofam had no consistent effect on the take-all decline process. We conjecture that these results are consistent with (i) low levels of particulate inoculum prior to the first wheat crop leading to low levels of primary infection, low levels of secondary infection, and little disease suppression; (ii) net amplification of inoculum during the first wheat crop and intercrop period; (iii) increased levels of primary and secondary infection in subsequent crops, but higher levels of disease suppression; and (iv) an equilibrium between the pathogen and antagonist populations by the 5th wheat, reflected by lower overall rates of primary infection, secondary infection, disease suppression and hence, disease severity.

Optimal strategies for the eradication of asiatic citrus canker in heterogeneous host landscapes.

ABSTRACT The eradication of nonnative plant pathogens is a key challenge in plant disease epidemiology. Asiatic citrus canker is an economically significant disease of citrus caused by the bacterial plant pathogen Xanthomonas citri subsp. citri. The pathogen is a major exotic disease problem in many citrus producing areas of the world including the United States, Brazil, and Australia. Various eradication attempts have been made on the disease but have been associated with significant social and economic costs due to the necessary removal of large numbers of host trees. In this paper, a spatially explicit stochastic simulation model of Asiatic citrus canker is introduced that describes an epidemic of the disease in a heterogeneous host landscape. We show that an optimum eradication strategy can be determined that minimizes the adverse costs associated with eradication. In particular, we show how the optimum strategy and its total cost depend on the topological arrangement of the host landscape. We discuss the implications of the results for invading plant disease epidemics in general and for historical and future eradication attempts on Asiatic citrus canker.