The Costs, Benefits and Human Behaviours for Antimicrobial Use in Small Commercial Broiler Chicken Systems in Indonesia

There are growing concerns over the threat to human health from the unregulated use of antimicrobials in livestock. Broiler production is of great economic and social importance in Indonesia. This study used a structured questionnaire approach to explore the human behaviours and economic drivers associated with antimicrobial use in small commercial broiler systems in Indonesia (n = 509). The study showed that antimicrobial use was high with farmers easily able to access antimicrobials through local animal medicine, however, it was difficult for farmers to access veterinary advice on responsible antimicrobial use. The most significant finding was that the relative cost of antimicrobials was low, and farmers observed improvements in productivity rates from routine antimicrobial administration. However, farmers seldom kept detailed records on farm productivity or economic costs; this is a hurdle to undertaking a more detailed economic analysis of antimicrobial use. There is a need for further research on the cost-effectiveness of alternative methods of preventing disease and ensuring that feasible alternatives are easily available. Farm-level economics and securing the food supply chain need to be central to any future policy interventions to reduce antimicrobial use in broiler systems in Indonesia and this observation is relevant at a regional and global level.</jats:p

Exploring the Socioeconomic Importance of Antimicrobial Use in the Small-Scale Pig Sector in Vietnam

Antimicrobial resistance (AMR) is influenced by antimicrobial use in human and animal health. This use exerts selection pressure on pathogen populations with the development of resistance and the exchange of resistance genes. While the exact scale of AMR in Vietnam remains uncertain, recent studies suggest that it is a major issue in both human and animal health. This study explored antimicrobial use behaviors in 36 pig farms in the Nam Dinh Province (North) and the Dong Nai Province (South) of Vietnam (with a median of 5.5 breeding sows and 41 fattening pigs). It also estimated the economic costs and benefits of use for the producer. Data were collected through a structured face-to-face interview with additional productivity data collected by farmers during a six-week period following the initial interview. Overall, antimicrobial use was high across the farms; however, in-feed antimicrobial use is likely to be under-reported due to misleading and imprecise labelling on premixed commercial feeds. An economic analysis found that the cost of antimicrobials was low relative to other farm inputs (~2% of total costs), and that farm profitability was precariously balanced, with high disease and poor prices leading to negative and low profits. Future policies for smallholder farms need to consider farm-level economics and livestock food supply issues when developing further antimicrobial use interventions in the region

The need for One Health systems-thinking approaches to understand multiscale dissemination of antimicrobial resistance

Although the effects of antimicrobial resistance (AMR) are most obvious at clinical treatment failure, AMR evolution, transmission, and dispersal happen largely in environmental settings, for example within farms, waterways, livestock, and wildlife. We argue that systems-thinking, One Health approaches are crucial for tackling AMR, by understanding and predicting how anthropogenic activities interact within environmental subsystems, to drive AMR emergence and transmission. Innovative computational methods integrating big data streams (eg, from clinical, agricultural, and environmental monitoring) will accelerate our understanding of AMR, supporting decision making. There are challenges to accessing, integrating, synthesising, and interpreting such complex, multidimensional, heterogeneous datasets, including the lack of specific metrics to quantify anthropogenic AMR. Moreover, data confidentiality, geopolitical and cultural variation, surveillance gaps, and science funding cause biases, uncertainty, and gaps in AMR data and metadata. Combining systems-thinking with modelling will allow exploration, scaling-up, and extrapolation of existing data. This combination will provide vital understanding of the dynamic movement and transmission of AMR within and among environmental subsystems, and its effects across the greater system. Consequently, strategies for slowing down AMR dissemination can be modelled and compared for efficacy and cost-effectiveness

The attitudes of owners and veterinary professionals in the United Kingdom to the risk of adverse events associated with using non- steroidal anti-inflammatory drugs (NSAIDs) to treat dogs with osteoarthritis

Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed by veterinary surgeons for the treatment of canine osteoarthritis, and affected dogs may receive these drugs for long periods of time. Whilst short term administration of NSAIDs to dogs is linked to adverse events such as gastrointestinal haemorrhage and renal injury, reports of adverse events associated with their long-term administration are limited in the veterinary literature. This study aimed to investigate the attitudes towards the long term use of NSAIDs for canine osteoarthritis held by three groups who manage osteoarthritic dogs in the United Kingdom: dog owners, veterinary surgeons and veterinary nurses. A qualitative methodology was adopted, using semi-structured interviews and focus groups. Thematic analysis of these data identified three themes: awareness of potential risks; recognition of adverse events; and influence of risk perception on the use of NSAIDs. Awareness of, and concern about, the risk of adverse events associated with NSAID administration to dogs with osteoarthritis was high in all groups, with veterinary surgeons being one of a variety of information sources used by owners to acquire this knowledge. Veterinary surgeons described difficulty in recognising, managing and avoiding adverse events associated with NSAIDs. When adverse events occurred, a wide range of management approaches were adopted ranging from a brief drug respite to permanent cessation of administration of any NSAIDs to that dog. Commonly employed approaches to minimise risk included dose reduction and screening blood tests. This study describes a high level of concern about the risks associated with long term NSAID administration to dogs with osteoarthritis and highlights a diverse range of strategies employed to minimise these risks. The evidence base for these strategies is poor, and this may present a risk to animal welfare if the affected dogs are not receiving adequate analgesia. In order to address this, more accurate and comprehensive data must be supplied to both veterinary professionals and owners on the true frequency of adverse events associated with long term administration of veterinary NSAIDs and how best to avoid them

The need for One Health systems-thinking approaches to understand multiscale dissemination of antimicrobial resistance

Although the effects of antimicrobial resistance (AMR) are most obvious at clinical treatment failure, AMR evolution, transmission, and dispersal happen largely in environmental settings, for example within farms, waterways, livestock, and wildlife. We argue that systems-thinking, One Health approaches are crucial for tackling AMR, by understanding and predicting how anthropogenic activities interact within environmental subsystems, to drive AMR emergence and transmission. Innovative computational methods integrating big data streams (eg, from clinical, agricultural, and environmental monitoring) will accelerate our understanding of AMR, supporting decision making. There are challenges to accessing, integrating, synthesising, and interpreting such complex, multidimensional, heterogeneous datasets, including the lack of specific metrics to quantify anthropogenic AMR. Moreover, data confidentiality, geopolitical and cultural variation, surveillance gaps, and science funding cause biases, uncertainty, and gaps in AMR data and metadata. Combining systems-thinking with modelling will allow exploration, scaling-up, and extrapolation of existing data. This combination will provide vital understanding of the dynamic movement and transmission of AMR within and among environmental subsystems, and its effects across the greater system. Consequently, strategies for slowing down AMR dissemination can be modelled and compared for efficacy and cost-effectiveness

Characterizing Antimicrobial Use in the Livestock Sector in Three South East Asian Countries (Indonesia, Thailand, and Vietnam)

A framework was developed to characterize the antimicrobial use/antimicrobial resistance complex in livestock systems in Indonesia, Vietnam, and Thailand. Farm profitability, disease prevention, and mortality rate reduction were identified as drivers toward antimicrobial use in livestock systems. It revealed that antimicrobial use was high in all sectors studied, and that routine preventative use was of particular importance to broiler production systems. Misleading feed labeling was identified as a hurdle to the collection of accurate antimicrobial use data, with farmers being unaware of the antimicrobials contained in some commercial feed. Economic analysis found that the cost of antimicrobials was low relative to other farm inputs, and that farm profitability was precariously balanced. High disease and poor prices were identified as potential drivers toward economic loss. The research indicates that antimicrobial use in small-scale poultry production systems improves feed conversion ratios and overall productivity. However, data were limited to quantify adequately these potential gains and their impacts on the food supply. During the study, all countries embraced and implemented policies on better management of antimicrobial use in livestock and surveillance of antimicrobial resistance. Future policies need to consider farm-level economics and livestock food supply issues when developing further antimicrobial use interventions in the region

Using priorities between human and livestock bacterial antimicrobial resistance (AMR) to identify data gaps in livestock AMR surveillance.

BackgroundBacterial antimicrobial resistance (AMR) is a global threat to both humans and livestock. Despite this, there is limited global consensus on data-informed, priority areas for intervention in both sectors. We compare current livestock AMR data collection efforts with other variables pertinent to human and livestock AMR to identify critical data gaps and mutual priorities.MethodsWe globally synthesized livestock AMR data from open-source surveillance reports and point prevalence surveys stratified for six pathogens (Escherichia coli, Staphylococcus aureus, non-typhoidal Salmonella, Campylobacter spp., Enterococcus faecalis, Enterococcus faecium) and eleven antimicrobial classes important in human and veterinary use, published between 2000 and 2020. We also included all livestock species represented in the data: cattle, chickens, pigs, sheep, turkeys, ducks, horses, buffaloes, and goats. We compared this data with intended priorities calculated from: disability-adjusted life years (DALYs), livestock antimicrobial usage (AMU), livestock biomass, and a global correlation exercise between livestock and human proportion of resistant isolates.ResultsResistance to fluoroquinolones and macrolides in Staphylococcus aureus were identified as priorities in many countries but, less than 10% of these reported livestock AMR data. Resistance data for Escherichia coli specific to cattle, chickens, and pigs, which we prioritized, were also well collected. AMR data collection on non-typhoidal Salmonella and other livestock species were often not prioritized. Of 232 categories prioritized by at least one country, data were only collected for 48% (n = 112).ConclusionsThe lack of livestock AMR data globally for broad resistance in Staphylococcus aureus could underplay their zoonotic threat. Countries can bolster livestock AMR data collection, reporting, and intervention setting for Staphylococcus aureus as done for Escherichia coli. This framework can provide guidance on areas to strengthen AMR surveillance and decision-making for humans and livestock, and if done routinely, can adapt to resistance trends and priorities

Network analysis of sea turtle movements and connectivity: A tool for conservation prioritization

Aim: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location: Global. Methods: We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.Fil: Kot, Connie Y.. University of Duke; Estados UnidosFil: Åkesson, Susanne. Lund University; SueciaFil: Alfaro Shigueto, Joanna. Universidad Cientifica del Sur; Perú. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Amorocho Llanos, Diego Fernando. Research Center for Environmental Management and Development; ColombiaFil: Antonopoulou, Marina. Emirates Wildlife Society-world Wide Fund For Nature; Emiratos Arabes UnidosFil: Balazs, George H.. Noaa Fisheries Service; Estados UnidosFil: Baverstock, Warren R.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Blumenthal, Janice M.. Cayman Islands Government; Islas CaimánFil: Broderick, Annette C.. University of Exeter; Reino UnidoFil: Bruno, Ignacio. Instituto Nacional de Investigaciones y Desarrollo Pesquero; ArgentinaFil: Canbolat, Ali Fuat. Hacettepe Üniversitesi; Turquía. Ecological Research Society; TurquíaFil: Casale, Paolo. Università degli Studi di Pisa; ItaliaFil: Cejudo, Daniel. Universidad de Las Palmas de Gran Canaria; EspañaFil: Coyne, Michael S.. Seaturtle.org; Estados UnidosFil: Curtice, Corrie. University of Duke; Estados UnidosFil: DeLand, Sarah. University of Duke; Estados UnidosFil: DiMatteo, Andrew. CheloniData; Estados UnidosFil: Dodge, Kara. New England Aquarium; Estados UnidosFil: Dunn, Daniel C.. University of Queensland; Australia. The University of Queensland; Australia. University of Duke; Estados UnidosFil: Esteban, Nicole. Swansea University; Reino UnidoFil: Formia, Angela. Wildlife Conservation Society; Estados UnidosFil: Fuentes, Mariana M. P. B.. Florida State University; Estados UnidosFil: Fujioka, Ei. University of Duke; Estados UnidosFil: Garnier, Julie. The Zoological Society of London; Reino UnidoFil: Godfrey, Matthew H.. North Carolina Wildlife Resources Commission; Estados UnidosFil: Godley, Brendan J.. University of Exeter; Reino UnidoFil: González Carman, Victoria. Instituto National de Investigación y Desarrollo Pesquero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Harrison, Autumn Lynn. Smithsonian Institution; Estados UnidosFil: Hart, Catherine E.. Grupo Tortuguero de las Californias A.C; México. Investigacion, Capacitacion y Soluciones Ambientales y Sociales A.C; MéxicoFil: Hawkes, Lucy A.. University of Exeter; Reino UnidoFil: Hays, Graeme C.. Deakin University; AustraliaFil: Hill, Nicholas. The Zoological Society of London; Reino UnidoFil: Hochscheid, Sandra. Stazione Zoologica Anton Dohrn; ItaliaFil: Kaska, Yakup. Dekamer—Sea Turtle Rescue Center; Turquía. Pamukkale Üniversitesi; TurquíaFil: Levy, Yaniv. University Of Haifa; Israel. Israel Nature And Parks Authority; IsraelFil: Ley Quiñónez, César P.. Instituto Politécnico Nacional; MéxicoFil: Lockhart, Gwen G.. Virginia Aquarium Marine Science Foundation; Estados Unidos. Naval Facilities Engineering Command; Estados UnidosFil: López-Mendilaharsu, Milagros. Projeto TAMAR; BrasilFil: Luschi, Paolo. Università degli Studi di Pisa; ItaliaFil: Mangel, Jeffrey C.. University of Exeter; Reino Unido. Pro Delphinus; PerúFil: Margaritoulis, Dimitris. Archelon; GreciaFil: Maxwell, Sara M.. University of Washington; Estados UnidosFil: McClellan, Catherine M.. University of Duke; Estados UnidosFil: Metcalfe, Kristian. University of Exeter; Reino UnidoFil: Mingozzi, Antonio. Università Della Calabria; ItaliaFil: Moncada, Felix G.. Centro de Investigaciones Pesqueras; CubaFil: Nichols, Wallace J.. California Academy Of Sciences; Estados Unidos. Center For The Blue Economy And International Environmental Policy Program; Estados UnidosFil: Parker, Denise M.. Noaa Fisheries Service; Estados UnidosFil: Patel, Samir H.. Coonamessett Farm Foundation; Estados Unidos. Drexel University; Estados UnidosFil: Pilcher, Nicolas J.. Marine Research Foundation; MalasiaFil: Poulin, Sarah. University of Duke; Estados UnidosFil: Read, Andrew J.. Duke University Marine Laboratory; Estados UnidosFil: Rees, ALan F.. University of Exeter; Reino Unido. Archelon; GreciaFil: Robinson, David P.. The Aquarium and Dubai Turtle Rehabilitation Project; Emiratos Arabes UnidosFil: Robinson, Nathan J.. Fundación Oceanogràfic; EspañaFil: Sandoval-Lugo, Alejandra G.. Instituto Politécnico Nacional; MéxicoFil: Schofield, Gail. Queen Mary University of London; Reino UnidoFil: Seminoff, Jeffrey A.. Noaa National Marine Fisheries Service Southwest Regional Office; Estados UnidosFil: Seney, Erin E.. University Of Central Florida; Estados UnidosFil: Snape, Robin T. E.. University of Exeter; Reino UnidoFil: Sözbilen, Dogan. Dekamer—sea Turtle Rescue Center; Turquía. Pamukkale University; TurquíaFil: Tomás, Jesús. Institut Cavanilles de Biodiversitat I Biologia Evolutiva; EspañaFil: Varo Cruz, Nuria. Universidad de Las Palmas de Gran Canaria; España. Ads Biodiversidad; España. Instituto Canario de Ciencias Marinas; EspañaFil: Wallace, Bryan P.. University of Duke; Estados Unidos. Ecolibrium, Inc.; Estados UnidosFil: Wildermann, Natalie E.. Texas A&M University; Estados UnidosFil: Witt, Matthew J.. University of Exeter; Reino UnidoFil: Zavala Norzagaray, Alan A.. Instituto politecnico nacional; MéxicoFil: Halpin, Patrick N.. University of Duke; Estados Unido