Understanding the spatial distribution and hot spots of collared Bornean elephants in a multi-use landscape.

In the Kinabatangan floodplain, Sabah, Malaysian Borneo, oil palm and settlements have reduced and fragmented lowland tropical forests, home to around 200 endangered Bornean elephants (Elephas maximus borneensis). In this region, elephants range within forests, oil palm and community areas. The degree to which elephants are using these areas remains unclear. We used GPS telemetry data from 2010 to 2020 for 14 collared elephants to map their entire known ranges and highly used areas (hot spots) across four land use categories and estimate time spent within these. The use of land use types across elephants varied significantly. Typically, females had strong fidelity to forests, yet many of these forests are threatened with conversion. For the three males, and several females, they heavily used oil palm estates, and this may be due to decreased landscape permeability or foraging opportunities. At the pooled level, the entire range and hot spot extents, constituted 37% and 34% for protected areas, respectively, 8% and 11% for unprotected forests, 53% and 51% for oil palm estates, and 2% for community areas. Protecting all forested habitats and effectively managing areas outside of protected areas is necessary for the long-term survival of this population.

Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review.

Dengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.

Convergence of marine megafauna movement patterns in coastal and open oceans.

The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals' movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyze a global dataset of ∼2.8 million locations from >2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared with more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal microhabitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise, and declining oxygen content.

Bayesian Networks to Compare Pest Control Interventions on Commodities Along Agricultural Production Chains.

The production of an agricultural commodity involves a sequence of processes: planting/growing, harvesting, sorting/grading, postharvest treatment, packing, and exporting. A Bayesian network has been developed to represent the level of potential infestation of an agricultural commodity by a specified pest along an agricultural production chain. It reflects the dependency of this infestation on the predicted level of pest challenge, the anticipated susceptibility of the commodity to the pest, the level of impact from pest control measures as designed, and any variation from that due to uncertainty in measure efficacy. The objective of this Bayesian network is to facilitate agreement between national governments of the exporters and importers on a set of phytosanitary measures to meet specific phytosanitary measure requirements to achieve target levels of protection against regulated pests. The model can be used to compare the performance of different combinations of measures under different scenarios of pest challenge, making use of available measure performance data. A case study is presented using a model developed for a fruit fly pest on dragon fruit in Vietnam; the model parameters and results are illustrative and do not imply a particular level of fruit fly infestation of these exports; rather, they provide the most likely, alternative, or worst-case scenarios of the impact of measures. As a means to facilitate agreement for trade, the model provides a framework to support communication between exporters and importers about any differences in perceptions of the risk reduction achieved by pest control measures deployed during the commodity production chain.

Using a Bayesian network to clarify areas requiring research in a host-pathogen system.

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease-driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host-pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious-disease systems.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors.

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement ('random error') than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.

Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions.

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to 'empty' reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.

Evaluation of coronary angiographic projections to balance the clinical yield with the radiation risk.

OBJECTIVE: Radiation safety principles dictate that imaging procedures should minimise the radiation risks involved, without compromising diagnostic performance. This study aims to define a core set of views that maximises clinical information yield for minimum radiation risk. Angiographers would supplement these views as clinically indicated. METHODS: An algorithm was developed to combine published data detailing the quality of information derived for the major coronary artery segments through the use of a common set of views in angiography with data relating to the dose-area product and scatter radiation associated with these views. RESULTS: The optimum view set for the left coronary system comprised four views: left anterior oblique (LAO) with cranial (Cr) tilt, shallow right anterior oblique (AP-RAO) with caudal (Ca) tilt, RAO with Ca tilt and AP-RAO with Cr tilt. For the right coronary system three views were identified: LAO with Cr tilt, RAO and AP-RAO with Cr tilt. An alternative left coronary view set including a left lateral achieved minimally superior efficiency (<5%), but with an ~8% higher radiation dose to the patient and 40% higher cardiologist dose. CONCLUSION: This algorithm identifies a core set of angiographic views that optimises the information yield and minimises radiation risk. This basic data set would be supplemented by additional clinically determined views selected by the angiographer for each case. The decision to use additional views for diagnostic angiography and interventions would be assisted by referencing a table of relative radiation doses for the views being considered.

Funnel plots and risk-adjusted count data adverse events. A limitation of indirect standardisation.

Reporting of hospital adverse event data is becoming increasingly mandated and this has motivated work on methods for the analysis and display of these data for groups of institutions. Currently, the method preferred by many workers is the funnel plot. Often, indirect standardisation is employed to produce these plots. It appears that, when used to display binary data such as surgical site infection or mortality data, the method is satisfactory. Increasingly, these data are risk-adjusted. However, risk adjustment of these data usually involves individual patients undergoing the same or similar procedures and the method does not appear to mislead. However, when dealing with count data such as bacteraemias it appears that this method can mislead, particularly where methods for risk adjustment of these data are used. Information about the hospitals or units of interest rather than individual patients is employed. For example, one hospital may have plastic and cardiac surgery units in which bacteraemias occur infrequently whereas another may provide treatment for renal failure (including transplantation) and have a large haematology-oncology unit (also including transplantation), each of which would expect higher bacteraemia rates. Moreover, the hospitals and units within them may differ substantially in size. It is well known that indirect standardisation can give biased results when denominators differ substantially. We illustrate this difficulty with risk-adjusted bacteraemia data from the Queensland Health Centre for Healthcare Infection, Surveillance and Prevention (CHRISP) database.

Role of overcrowding in meticillin-resistant Staphylococcus aureus transmission: Bayesian network analysis for a single public hospital.

The transmission of multiple antibiotic-resistant organisms (MROs) in hospitals is affected by many inter-related factors. These include the background prevalence of the organism (burden), hand hygiene, the efficiency of patient screening, the isolation or cohorting of carriers, the quality of hospital cleaning, and bed occupancy. In addition, the prevalence of one MRO may influence the transmission of another by occupying isolation beds, and thus reducing isolation resources for the latter. For example, the overuse of third generation cephalosporin antibiotics can increase extended-spectrum ß-lactamase-producing Klebsiella pneumoniae, thus indirectly influencing the transmission of meticillin-resistant Staphylococcus aureus (MRSA). In order to study this complex system of interrelationships, we have employed a Bayesian network. We report results of the first two years of analysis for a single public hospital. We conclude that, within this institution, the association between high bed occupancy and increased transmission of MRSA may be subject to a dynamic multidimensional threshold and tipping point. This may be influenced by other factors such as MRSA burden and whether the high bed occupancy interferes with preparation and cleaning of beds for new patients and with hand hygiene and efforts to isolate or cohort carriers.

Perceptions of the ethical conduct of cancer trials by oncology nurses.

Informed consent and subject protection are internationally mandated requirements for the ethical conduct of research; however, the monitoring of the day-to-day conduct of research may be insufficient for ensuring consistent compliance with required ethical ideals. Oncology nurses were surveyed about their perceptions of ethical issues relevant to cancer trials research. Utilising an investigator-developed instrument, multi-item scales assessed six ethical domains. Of 192 respondents, 95% or more held definite views in 12 of 15 items about patient understanding of cancer trials, informed consent and the welfare of participants. Approximately 95% perceived that patients consented freely and knew how to withdraw from a trial, and 81% perceived better monitoring of trial than non-trial patients. However, more than 80% of respondents perceived that at times patients had unrealistic expectations of participation, and more than 50% perceived that participants sometimes did not understand the nature and risk of cancer trials. Although the conative attributes of patients place limits on the goals of bioethics, the results of this study show first that oncology nurses have opinions about ethical constructs directly linked to the daily conduct of cancer clinical trials, and second that this link warrants further investigation in order to benchmark trial conduct against the ideals of ethical research.

Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia.

OBJECTIVE: To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems and spatial scan statistic (SaTScan). METHODS: We obtained BFV disease cases, population and statistical local areas (SLAs) boundary data from Queensland Health and Australian Bureau of Statistics, respectively, during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200 km radius and varying time windows from 1 to 12 months were chosen (for the space-time analysis). RESULTS: The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. CONCLUSIONS: This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing ongoing surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

Test-retest reliability of hand-held dynamometry and functional tests in systemic lupus erythematosus.

The aim of this study was to evaluate the test-retest reliability and determine the degree of measurement error of tests of isometric muscle strength and upper and lower limb function in women with systemic lupus erythematosus (SLE). Twelve women with SLE (age 39.8 ± 10 years) were assessed on two occasions separated by a 7-10-day interval. Strength of six muscle groups was measured using a hand-held dynamometer; function was measured by the 30-s sit to stand test and the 30-s 1 kg arm lift. Relative reliability was estimated using the intraclass correlation coefficient (ICC), model 2,1 (ICC2,1). Absolute reliability was estimated using standard error measurement and the minimal detectable difference was calculated. All ICCs were greater than 0.87. Muscle strength would need to increase by between 18% and 39% in women with SLE to be 95% confident of detecting real changes. The functional tests demonstrated a systematic bias between trials. This study demonstrates that hand-held dynamometry in SLE can be performed with excellent reliability. Further work needs to be completed to determine the number of trials necessary for both the 30-s sit to stand and 30-s 1 kg arm lift to decrease the systematic bias.

Effect of vitamin D supplementation on muscle strength: a systematic review and meta-analysis.

UNLABELLED: This systematic review demonstrates that vitamin D supplementation does not have a significant effect on muscle strength in vitamin D replete adults. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency. INTRODUCTION: The purpose of this study is to systematically review the evidence on the effect of vitamin D supplementation on muscle strength in adults. METHODS: A comprehensive systematic database search was performed. Inclusion criteria included randomised controlled trials (RCTs) involving adult human participants. All forms and doses of vitamin D supplementation with or without calcium supplementation were included compared with placebo or standard care. Outcome measures included evaluation of strength. Outcomes were compared by calculating standardised mean difference (SMD) and 95% confidence intervals. RESULTS: Of 52 identified studies, 17 RCTs involving 5,072 participants met the inclusion criteria. Meta-analysis showed no significant effect of vitamin D supplementation on grip strength (SMD -0.02, 95%CI -0.15,0.11) or proximal lower limb strength (SMD 0.1, 95%CI -0.01,0.22) in adults with 25(OH)D levels > 25 nmol/L. Pooled data from two studies in vitamin D deficient participants (25(OH)D <25 nmol/L) demonstrated a large effect of vitamin D supplementation on hip muscle strength (SMD 3.52, 95%CI 2.18, 4.85). CONCLUSION: Based on studies included in this systematic review, vitamin D supplementation does not have a significant effect on muscle strength in adults with baseline 25(OH)D >25 nmol/L. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency.

Association between indoor air pollution measurements and respiratory health in women and children in Lao PDR.

UNLABELLED: This article presents the results of a study on the association between measured air pollutants and the respiratory health of resident women and children in Lao PDR, one of the least developed countries in Southeast Asia. The study, commissioned by the World Health Organisation, included PM(10), CO and NO(2) measurements made inside 181 dwellings in nine districts within two provinces in Lao PDR over a 5-month period (12/05-04/06), and respiratory health information (via questionnaires and peak expiratory flow rate (PEFR) measurements) for all residents in the same dwellings. Adjusted odds ratios were calculated separately for each health outcome using binary logistic regression. There was a strong and consistent positive association between NO(2) and CO for almost all questionnaire-based health outcomes for both women and children. Women in dwellings with higher measured NO(2) had more than triple of the odds of almost all of the health outcomes, and higher concentrations of NO(2) and CO were significantly associated with lower PEFR. This study supports a growing literature confirming the role of indoor air pollution in the burden of respiratory disease in developing countries. The results will directly support changes in health and housing policy in Lao PDR. PRACTICAL IMPLICATIONS: This is the first study that investigated indoor air quality and its impact within residential dwellings in Lao PDR, which is one of the poorest and least developed countries in south-east Asia, with a life-expectancy of 56 years in 2008. While there have been other studies published on indoor air quality in other developing countries, the situation in Laos is different because the majority of houses in Laos used wood stoves, and therefore, emissions from wood burning are the dominant sources of indoor air pollution. In other countries, and studies, while emission from wood burning was investigated, wood was rarely the main or the only fuel used, as the houses used in addition (or solely) dung, kerosene or coal. The study quantified, for the first time, concentrations in houses two provinces in Laos PDR and shed light on the impact of human activities and urban design on pollutant concentrations and respiratory health. This study contributes to the accumulation of evidence to provide more reliable estimates of risk and a more informed basis for decision-making by concerned governments and communities.

Pollutant concentrations within households in Lao PDR and association with housing characteristics and occupants' activities.

The paper presents the results of a study conducted to investigate indoor air quality within residential dwellings in Lao PDR. Results from PM(10), CO, and NO(2) measurements inside 167 dwellings in Lao PDR over a five month period (December 2005-April 2006) are discussed as a function of household characteristics and occupant activities. Extremely high PM(10) and NO(2) concentrations (12 h mean PM(10) concentrations 1275 ± 98 µg m(-3) and 1183 ± 99 µg m(-3) in Vientiane and Bolikhamxay provinces, respectively; 12 h mean NO(2) concentrations 1210 ± 94 µg m(-3) and 561 ± 45 µg m(-3) in Vientiane and Bolikhamxay, respectively) were measured within the dwellings. Correlations, ANOVA analysis (univariate and multivariate), and linear regression results suggest a substantial contribution from cooking and smoking. The PM(10) concentrations were significantly higher in houses without a chimney compared to houses in which cooking occurred on a stove with a chimney. However, no significant differences in pollutant concentrations were observed as a function of cooking location. Furthermore, PM(10) and NO(2) concentrations were higher in houses in which smoking occurred, suggestive of a relationship between increased indoor concentrations and smoking (0.05 < p < 0.10). Resuspension of dust from soil floors was another significant source of PM(10) inside the house (634 µg m(-3), p < 0.05).

Analysis of aggregated hospital infection data for accountability.

Analysis and reporting of among-institution aggregated hospital-acquired infection data are necessary for transparency and accountability. Different analytical methods are required for ensuring transparency and accountability for within-institution sequential analysis. In addition, unbiased summary information is needed for planning and informing the public. We believe that implementation of systems based on evidence is the key to improving institutional performance and safety. This must be accompanied by compliance, outcome audit and sequential analysis of outcome data, e.g. using statistical process control methods. Checklists can be a valuable aid for ensuring implementation of evidence-based systems. Aggregated outcome data analysis for transparency and accountability should concentrate primarily on accurately presenting the outcomes together with their precision. We describe tabulations, funnel plots and random-effects (shrinkage) analysis and avoid comparisons using league tables, star ratings and confidence intervals.

Limiting risk of hospital adverse events: avoiding train wrecks is more important than counting and reporting them.

Targets implemented at national or state levels have been employed in response to excessive numbers of adverse events (AEs) such as multiple antibiotic-resistant Staphylococcus aureus bacteraemias. Hospital resources are limited and setting such targets can result in resource diversion to dealing with the targeted AEs. There may be initial success as judged by decreasing counts but underlying problems are not necessarily addressed, and there is evidence that other non-targeted AEs may increase. Moreover, the values of individual observations can be greatly influenced by random variation. This can make it difficult using comparisons and targets to draw conclusions about the work of an institution. Although counting AEs is essential, the key to avoiding episodes of patient harm is prevention. This requires the implementation of evidence-based systems. These are already available for many AEs in the form of 'bundles' and checklists. When these systems are properly implemented and sustained, AE rates tend to occur at minimum predictable levels. Unfortunately, in spite of widespread knowledge and aggressive promotion, high levels of compliance have often been difficult to achieve and sustain. Better understanding and implementation of methods to sustain evidence-based systems are needed. Checklists, used as part of an overall system involving leadership and empowerment, application of evidence, culture change and measurement, may help to overcome this problem.

Sequential analysis of uncommon adverse outcomes.

Sequential analysis of uncommon adverse outcomes (AEs) such as surgical site infections (SSIs) is desirable. Short postoperative lengths of stay (LOS) result in many SSIs occurring after discharge and they are often superficial. Deep and organ space (complex) SSIs occur less frequently but are detected more reliably and are suitable for monitoring wound care. Those occurring post-discharge usually require readmissison and can be counted accurately. Sequential analysis of meticillin-resistant Staphylococcus aureus bacteraemia is also needed. The key to prevention is to implement systems based on evidence, e.g. using 'bundles' and checklists. Regular mortality and morbidity audit meetings are required and these may need to be followed by independent audits. Sequential statistical analysis is desirable for data presentation, to detect changes, and to discourage tampering with processes when occasional AEs occur in a reliable system. Tabulations and cumulative observed minus expected (O-E) charts and funnel plots are valuable, supplemented in the presence of apparent 'runs' of AEs by cumulative sum analysis. Used prospectively, they may enable staff to visualise and detect patterns or shifts in rates and counts that might not otherwise be apparent.