Anti-microbial Use in Animals: How to Assess the Trade-offs

Antimicrobials are widely used in preventive and curative medicine in animals. Benefits from curative use are clear – it allows sick animals to be healthy with a gain in human welfare. The case for preventive use of antimicrobials is less clear cut with debates on the value of antimicrobials as growth promoters in the intensive livestock industries. The possible benefits from the use of antimicrobials need to be balanced against their cost and the increased risk of emergence of resistance due to their use in animals. The study examines the importance of animals in society and how the role and management of animals is changing including the use of antimicrobials. It proposes an economic framework to assess the trade-offs of anti-microbial use and examines the current level of data collection and analysis of these trade-offs. An exploratory review identifies a number of weaknesses. Rarely are we consistent in the frameworks applied to the economic assessment anti-microbial use in animals, which may well be due to gaps in data or the prejudices of the analysts. There is a need for more careful data collection that would allow information on (i) which species and production systems antimicrobials are used in, (ii) what active substance of antimicrobials and the application method and (iii) what dosage rates. The species need to include companion animals as well as the farmed animals as it is still not known how important direct versus indirect spread of resistance to humans is. In addition, research is needed on pricing antimicrobials used in animals to ensure that prices reflect production and marketing costs, the fixed costs of anti-microbial development and the externalities of resistance emergence. Overall, much work is needed to provide greater guidance to policy, and such work should be informed by rigorous data collection and analysis systems

A Delphi study to explore and gain consensus regarding the most important barriers and facilitators affecting physiotherapist and pharmacist non-medical prescribing

Non-medical prescribing was introduced into the United Kingdom to improve patient care, but early research indicated a third of Allied Health Professionals may not use their prescribing qualification. A previous literature review, highlighting factors influencing prescribing, identified only papers with nursing and pharmacy participants. This investigation explored consensus on factors affecting physiotherapist and pharmacist non-medical prescribers. A three round Delphi study was conducted with pharmacist and physiotherapist prescribers. Round One comprised information gathering on facilitators and barriers to prescribing participants had experienced, and underwent content analysis. This was followed by two sequential consensus seeking rounds with participants asked to rate the importance of statements to themselves. Consensus criteria were determined a priori, including median, interquartile range, percentage agreement and Kendall's Coefficient of Concordance (W). Statements reaching consensus were ranked for importance in Round Three and analysed to produce top ten ranks for all participants and for each professional group. Participants, recruited October 2018, comprised 24 pharmacists and 18 physiotherapists. In Round One, content analysis of 172 statements regarding prescribing influences revealed 24 themes. 127 statements were included in Round Two for importance rating (barriers = 68, facilitators = 59). After Round Two, 29 statements reached consensus (barriers = 1, facilitators = 28), with no further statements reaching consensus following Round Three. The highest ranked statement in Round Three overall was: "Being able to prescribe to patients is more effective and really useful working [in my area]". Medical support and improved patient care factors appeared the most important. Differences were noted between physiotherapist and pharmacist prescribers regarding the top ten ranked statements, for example team working which pharmacists ranked higher than physiotherapists. Differences may be explained by the variety of practice areas and relative newness of physiotherapy prescribing. Barriers appear to be post or person specific, whereas facilitators appear universal

Landscape as a Model: The Importance of Geometry

In all models, but especially in those used to predict uncertain processes (e.g., climate change and nonnative species establishment), it is important to identify and remove any sources of bias that may confound results. This is critical in models designed to help support decisionmaking. The geometry used to represent virtual landscapes in spatially explicit models is a potential source of bias. The majority of spatial models use regular square geometry, although regular hexagonal landscapes have also been used. However, there are other ways in which space can be represented in spatially explicit models. For the first time, we explicitly compare the range of alternative geometries available to the modeller, and present a mechanism by which uncertainty in the representation of landscapes can be incorporated. We test how geometry can affect cell-to-cell movement across homogeneous virtual landscapes and compare regular geometries with a suite of irregular mosaics. We show that regular geometries have the potential to systematically bias the direction and distance of movement, whereas even individual instances of landscapes with irregular geometry do not. We also examine how geometry can affect the gross representation of real-world landscapes, and again show that individual instances of regular geometries will always create qualitative and quantitative errors. These can be reduced by the use of multiple randomized instances, though this still creates scale-dependent biases. In contrast, virtual landscapes formed using irregular geometries can represent complex real-world landscapes without error. We found that the potential for bias caused by regular geometries can be effectively eliminated by subdividing virtual landscapes using irregular geometry. The use of irregular geometry appears to offer spatial modellers other potential advantages, which are as yet underdeveloped. We recommend their use in all spatially explicit models, but especially for predictive models that are used in decisionmaking

Barriers to and facilitators of independent non-medical prescribing in clinical practice:a mixed-methods systematic review

Question: What are the factors that affect the implementation or utilisation of independent non-medical prescribing (iNMP)? Design: Mixed-methods systematic review. Two reviewers independently completed searches, eligibility and quality assessments. Data sources: Pre-defined search terms were utilised to search electronic databases. Reference lists, key journals and grey literature were searched alongside consultation with authors/experts. Eligibility criteria for included studies: Qualitative and quantitative studies investigating independent prescribing by any non-medical professional group. Study participants included any stakeholders involved in actual or proposed iNMP. Measurements reported on data describing stakeholders’ perceptions and experiences of the barriers to/facilitators of iNMP. Results: A total of 43 qualitative and seven quantitative studies from three countries (n = 12, 117 participants) were included. Quality scores varied from 9 to 35 (Quality Assessment Tool for Studies with Diverse Designs, 0 to 48). Qualitative data were synthesised into four themes (and subthemes): systems (government and political, organisational, formulary); education and support (non-medical prescribing (NMP) courses/continuous professional development (CPD)); personal and professional (medical profession, NMP professions, service users); and financial factors. Quantitative data corroborated the qualitative themes. Integration of the qualitative themes and quantitative data enabled the development of a NMP implementation framework. Conclusion: Barriers to and facilitators of the implementation and utilisation of iNMP are evident, demonstrating multifactorial and context-specific variables within four explicit themes. Professional bodies, politicians, policy and healthcare managers and clinicians could use the resulting NMP implementation framework to ensure the safe and successful implementation and utilisation of NMP. Clinical physiotherapists and other clinicians should consider whether these variables have been adequately addressed prior to adopting NMP into their clinical practice. Registration: PROSPERO CRD42015017212. [Noblet T, Marriott J, Graham-Clarke E, Rushton A (2017) Barriers to and facilitators of independent non-medical prescribing in clinical practice: a mixed-methods systematic review. Journal of Physiotherapy 63: 221–234

Non-medical prescribing in the United Kingdom National Health Service:a systematic policy review

IntroductionNon-medical prescribing was introduced into the United Kingdom (UK) to improve patient care, through extending healthcare professionals' roles. More recent government health service policy focuses on the increased demand and the need for efficiency. This systematic policy review aimed to describe any changes in government policy position and the role that non-medical prescribing plays in healthcare provision.MethodThe systematic policy review included policy and consultation documents that describe independent non-medical prescribing. A pre-defined protocol was registered with PROSPERO (CRD42015019786). Professional body websites, other relevant websites and the following databases were searched to identify relevant documents: HMIC, Lexis Nexis, UK Government Web Archive, UKOP, UK Parliamentary Papers and Web of Science. Documents published between 2006 and February 2018 were included.Results and discussionFollowing exclusions, 45 documents were selected for review; 23 relating to policy or strategy and 22 to consultations. Of the former, 13/23 were published 2006-2010 and the remainder since 2013. Two main themes were identified: chronological aspects and healthcare provision. In the former, a publication gap for policy documents resulted from a change in government and associated major healthcare service reorganisation. In the later, the role of non-medical prescribing was found to have evolved to support efficient service delivery, and cost reduction. For many professions, prescribing appears embedded into practice; however, the pharmacy profession continues to produce policy documents, suggesting that prescribing is not yet perceived as normal practice.ConclusionPrescribing appears to be more easily adopted into practice where it can form part of the overall care of the patient. Where new roles are required to be established, then prescribing takes longer to be universally adopted. While this review concerns policy and practice in the UK, the aspect of role adoption has wider potential implications

Zoonosis emergence linked to agricultural intensification and environmental change

A systematic review was conducted by a multidisciplinary team to analyze qualitatively best available scientific evidence on the effect of agricultural intensification and environmental changes on the risk of zoonoses for which there are epidemiological interactions between wildlife and livestock. The study found several examples in which agricultural intensification and/or environmental change were associated with an increased risk of zoonotic disease emergence, driven by the impact of an expanding human population and changing human behavior on the environment. We conclude that the rate of future zoonotic disease emergence or reemergence will be closely linked to the evolution of the agriculture–environment nexus. However, available research inadequately addresses the complexity and interrelatedness of environmental, biological, economic, and social dimensions of zoonotic pathogen emergence, which significantly limits our ability to predict, prevent, and respond to zoonotic disease emergence

Predicting tree distributions in an East African biodiversity hotspot : model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix. (C) 2008 Elsevier B.V. All rights reserved

Preeclampsia and Future Cardiovascular Health

Background—Preeclampsia is a pregnancy-specific disorder resulting in hypertension and multiorgan dysfunction. There is growing evidence that these effects persist after pregnancy. We aimed to systematically evaluate and quantify the evidence on the relationship between preeclampsia and the future risk of cardiovascular diseases.Methods and Results—We studied the future risk of heart failure, coronary heart disease, composite cardiovascular disease, death because of coronary heart or cardiovascular disease, stroke, and stroke death after preeclampsia. A systematic search of MEDLINE and EMBASE was performed to identify relevant studies. We used random-effects meta-analysis to determine the risk. Twenty-two studies were identified with >6.4 million women including >258?000 women with preeclampsia. Meta-analysis of studies that adjusted for potential confounders demonstrated that preeclampsia was independently associated with an increased risk of future heart failure (risk ratio [RR], 4.19; 95% confidence interval [CI], 2.09–8.38), coronary heart disease (RR, 2.50; 95% CI, 1.43–4.37), cardiovascular disease death (RR, 2.21; 95% CI, 1.83–2.66), and stroke (RR, 1.81; 95% CI, 1.29–2.55). Sensitivity analyses showed that preeclampsia continued to be associated with an increased risk of future coronary heart disease, heart failure, and stroke after adjusting for age (RR, 3.89; 95% CI, 1.83–8.26), body mass index (RR, 3.16; 95% CI, 1.41–7.07), and diabetes mellitus (RR, 4.19; 95% CI, 2.09–8.38).Conclusions—Preeclampsia is associated with a 4-fold increase in future incident heart failure and a 2-fold increased risk in coronary heart disease, stroke, and death because of coronary heart or cardiovascular disease. Our study highlights the importance of lifelong monitoring of cardiovascular risk factors in women with a history of preeclampsia