Baiting and Feeding Revisited: Modeling Factors Influencing Transmission of Tuberculosis Among Deer and to Cattle

Although tuberculosis caused by Mycobacterium bovis (bTB) is endemic in white-tailed deer (Odocoileus virginianus) in northeastern Michigan, USA, baiting and feeding of deer continue despite a regulatory ban. Previous modeling suggests aggregation at bait sites slows the rates at which harvest and/or vaccination decrease bTB prevalence, prolongs time to eradication, and increases the likelihood that once eradicated, bTB will re-establish following an incursion. However, the extent to which specific factors such as food density, attractiveness to deer, and persistence on the landscape influence bTB transmission is unknown. We used an individual-based, spatially-explicit stochastic simulation model of bTB in deer and cattle to investigate effects of feed density, attractiveness, and spatial and temporal persistence on bTB prevalence in deer and the probability of breakdowns in adjacent cattle herds. Because hunter harvest remains key to controlling bTB in deer, and harvest rates are in long term decline, we modeled these feeding-associated factors at harvest rates prevailing both when the model was developed (2003–2007) and in 2018. Food placement at randomized locations vs. fixed sites had little effect on bTB prevalence in deer, whereas increasing the probability that deer move to food piles (attractiveness) had the greatest effect of factors studied on both prevalence and herd breakdowns. Reducing food pile density reduced prevalence, but decreased herd breakdowns only modestly. Consistent availability of food over longer periods of time, as would occur with supplemental winter feeding or persistent recreational feeding, increased both prevalence in deer and cattle herd breakdowns dramatically. Though perhaps implausible to the public, altering how bait and feed for deer are used can reduce cattle herd breakdowns. Baiting and feeding bans have contributed to declining bTB prevalence, but non-compliance and continued legal sales of feed impede eradication. Requiring hunters to move food piles is unlikely to mitigate effects on transmission and is not a useful management tool. Compared to baiting, winter supplemental feeding or extended recreational feeding is likely to magnify bTB transmission by prolonging temporal availability. Because attractiveness of feed is influenced both by type of feed and deer behavior, research to quantify factors influencing deer movement to food should be a priority

WHO global research priorities for antimicrobial resistance in human health

The WHO research agenda for antimicrobial resistance (AMR) in human health has identified 40 research priorities to be addressed by the year 2030. These priorities focus on bacterial and fungal pathogens of crucial importance in addressing AMR, including drug-resistant pathogens causing tuberculosis. These research priorities encompass the entire people-centred journey, covering prevention, diagnosis, and treatment of antimicrobial-resistant infections, in addition to addressing the overarching knowledge gaps in AMR epidemiology, burden and drivers, policies and regulations, and awareness and education. The research priorities were identified through a multistage process, starting with a comprehensive scoping review of knowledge gaps, with expert inputs gathered through a survey and open call. The priority setting involved a rigorous modified Child Health and Nutrition Research Initiative approach, ensuring global representation and applicability of the findings. The ultimate goal of this research agenda is to encourage research and investment in the generation of evidence to better understand AMR dynamics and facilitate policy translation for reducing the burden and consequences of AMR

Evaluation of Blood Assays for Detection of \u3ci\u3eMycobacterium bovis\u3c/i\u3e in White-Tailed Deer (\u3ci\u3eOdocoileus virginianus\u3c/i\u3e) in Michigan

Surveillance and control activities related to bovine tuberculosis (TB) in free-ranging, Michigan white-tailed deer (Odocoileus virginianus) have been underway for over a decade, with significant progress. However, foci of higher TB prevalence on private lands and limited agency ability to eliminate them using broad control strategies have led to development and trial of new control strategies, such as live trapping, testing, and culling or release. Such strategies require a prompt, accurate live animal test, which has thus far been lacking. We report here the ability of seven candidate blood assays to determine the TB infection status of Michigan deer. Our aims were twofold: to characterize the accuracy of the tests using field-collected samples and to evaluate the feasibility of the tests for use in a test-and-cull strategy. Samples were collected from 760 deer obtained via five different surveys conducted between 2004 and 2007. Blood samples were subjected to one or more of the candidate blood assays and evaluated against the results of mycobacterial culture of the cranial lymph nodes. Sensitivities of the tests ranged from 46% to 68%, whereas specificities and negative predictive values were all .92%. Positive predictive values were highly variable. An exploratory analysis of associations among several host and sampling-related factors and the agreement between blood assay and culture results suggested these assays were minimally affected. This study demonstrated the capabilities and limitations of several available blood tests for Mycobacterium bovis on specimens obtained through a variety of field surveillance methods. Although these blood assays cannot replace mass culling, information on their performance may prove useful as wildlife disease managers develop innovative methods of detecting infected animals where mass culling is publicly unacceptable and cannot be used as a control strategy

Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America

Evidence-based guidelines for implementation and measurement of antibiotic stewardship interventions in inpatient populations including long-term care were prepared by a multidisciplinary expert panel of the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. The panel included clinicians and investigators representing internal medicine, emergency medicine, microbiology, critical care, surgery, epidemiology, pharmacy, and adult and pediatric infectious diseases specialties. These recommendations address the best approaches for antibiotic stewardship programs to influence the optimal use of antibiotics

AusTraits: a curated plant trait database for the Australian flora

INTRODUCTION AusTraits is a transformative database, containing measurements on the traits of Australia’s plant taxa, standardised from hundreds of disconnected primary sources. So far, data have been assembled from > 250 distinct sources, describing > 400 plant traits and > 26,000 taxa. To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource are also available on the project’s GitHub repository, http://traitecoevo.github.io/austraits.build/. Further information on the project is available in the associated publication and at the project website austraits.org. Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 CONTRIBUTORS The project is jointly led by Dr Daniel Falster (UNSW Sydney), Dr Rachael Gallagher (Western Sydney University), Dr Elizabeth Wenk (UNSW Sydney), and Dr Hervé Sauquet (Royal Botanic Gardens and Domain Trust Sydney), with input from > 300 contributors from over > 100 institutions (see full list above). The project was initiated by Dr Rachael Gallagher and Prof Ian Wright while at Macquarie University. We are grateful to the following institutions for contributing data Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium, Department of Environment, Land, Water and Planning, Victoria. AusTraits has been supported by investment from the Australian Research Data Commons (ARDC), via their “Transformative data collections” (https://doi.org/10.47486/TD044) and “Data Partnerships” (https://doi.org/10.47486/DP720) programs; fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910), a grant from Macquarie University to Gallagher. The ARDC is enabled by National Collaborative Research Investment Strategy (NCRIS). ACCESSING AND USE OF DATA The compiled AusTraits database is released under an open source licence (CC-BY), enabling re-use by the community. A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors: Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 In addition, we encourage users you to cite the original data sources, wherever possible. Note that under the license data may be redistributed, provided the attribution is maintained. The downloads below provide the data in two formats: austraits-3.0.2.zip: data in plain text format (.csv, .bib, .yml files). Suitable for anyone, including those using Python. austraits-3.0.2.rds: data as compressed R object. Suitable for users of R (see below). Both objects contain all the data and relevant meta-data. AUSTRAITS R PACKAGE For R users, access and manipulation of data is assisted with the austraits R package. The package can both download data and provides examples and functions for running queries. STRUCTURE OF AUSTRAITS The compiled AusTraits database has the following main components: austraits ├── traits ├── sites ├── contexts ├── methods ├── excluded_data ├── taxanomic_updates ├── taxa ├── definitions ├── contributors ├── sources └── build_info These elements include all the data and contextual information submitted with each contributed datasets. A schema and definitions for the database are given in the file/component definitions, available within the download. The file dictionary.html provides the same information in textual format. Full details on each of these components and columns are contained within the definition. Similar information is available at http://traitecoevo.github.io/austraits.build/articles/Trait_definitions.html and http://traitecoevo.github.io/austraits.build/articles/austraits_database_structure.html. CONTRIBUTING We envision AusTraits as an on-going collaborative community resource that: Increases our collective understanding the Australian flora; and Facilitates accumulation and sharing of trait data; Builds a sense of community among contributors and users; and Aspires to fully transparent and reproducible research of the highest standard. As a community resource, we are very keen for people to contribute. Assembly of the database is managed on GitHub at traitecoevo/austraits.build. Here are some of the ways you can contribute: Reporting Errors: If you notice a possible error in AusTraits, please post an issue on GitHub. Refining documentation: We welcome additions and edits that make using the existing data or adding new data easier for the community. Contributing new data: We gladly accept new data contributions to AusTraits. See full instructions on how to contribute at http://traitecoevo.github.io/austraits.build/articles/contributing_data.html

AusTraits, a curated plant trait database for the Australian flora

International audienceWe introduce the austraits database-a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual-and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge