Burden assessment of antimicrobial use and resistance in livestock in data-scarce contexts.

Misuse and overuse of antimicrobials in livestock production are identified as drivers for antimicrobial resistance (AMR). To improve decision-making concerning livestock health, it is important to understand the impact of AMR in livestock and aquaculture, within and beyond farm level, as well as expenditure on antimicrobial use (AMU). Such understanding provides grounds for systematic disease prioritisation and establishes a baseline for understanding the value of different strategies to mitigate animal health problems and for the monitoring and evaluation of the impact of those strategies. Yet limited data availability and quality surrounding AMU and AMR create barriers to furthering the knowledge of such impact. These data constraints are also more prevalent in contexts that lack the necessary resources to develop and maintain systematic and centralised data collection and collation systems. Even in regions with robust AMU and AMR monitoring systems in place, data limitations remain, such that the expenditure on antimicrobials and impacts of AMR remain unclear. Additionally, the current research funding strategies have been less focused on primary data collection, adding further barriers to filling the data void and reducing the global AMU/AMR knowledge gap. To work around the data scarcity and leverage previous and ongoing research efforts, it is vital to gain comprehensive knowledge of the people, projects and research consortia dedicated to the topic of AMU/AMR.

Les utilisations incorrecte et excessive d'agents antimicrobiens dans la production animale figurent parmi les facteurs connus de développement de résistances aux agents antimicrobiens (RAM). Pour améliorer la prise de décision relative à la santé des cheptels, il est essentiel de comprendre l'impact de la RAM chez les animaux d'élevage terrestres et aquatiques, aussi bien au niveau des élevages qu'au-delà, et de pouvoir quantifier les dépenses consacrées à l'utilisation d'agents antimicrobiens (UAM). Cette compréhension apporte les éléments d'information pour la priorisation systématique des maladies et établit un cadre de référence pour comprendre la valeur respective des différentes stratégies d'atténuation des problèmes de santé animale et pour assurer le suivi et l'évaluation d'impact de ces stratégies. Cependant, la disponibilité et la qualité limitées des données relatives à l'UAM et à la RAM font obstacle à une connaissance plus poussée de cet impact. Ces contraintes liées aux données sont plus répandues dans les contextes dépourvus des ressources nécessaires pour élaborer et entretenir des systèmes de collecte de données systématiques et centralisés. Même dans les régions où des systèmes robustes de suivi de l'UAM et de la RAM sont en place, le problème de l'insuffisance de données reste posé de sorte que la réalité des coûts induits par les agents antimicrobiens et l'impact de la RAM demeurent incertains. De plus, les stratégies actuelles de financement de la recherche ont été moins axées sur la collecte de données primaires, ce qui ajoute des obstacles supplémentaires pour l'obtention des données manquantes et compromet les efforts visant à réduire les écarts de connaissances sur l'UAM et la RAM à l'échelle mondiale. Afin de remédier à la pénurie de données et de mettre à profit les recherches antérieures et en cours, il est indispensable de savoir quels sont les acteurs, les projets et les consortiums de recherche qui travaillent sur l'UAM et la RAM.

El uso incorrecto y excesivo de antimicrobianos en la producción ganadera se considera un impulsor de la resistencia a los antimicrobianos (RAM). Para mejorar la toma de decisiones relativas a la sanidad del ganado, es importante comprender el impacto de la RAM en la ganadería y la acuicultura, a nivel de las granjas y más allá, así como el coste con el uso de antimicrobianos (UAM). Tal comprensión permite una priorización sistemática de enfermedades y establece una línea base para comprender el valor de las distintas estrategias destinadas a mitigar los problemas de sanidad animal, así como para supervisar y evaluar el impacto de esas estrategias. Sin embargo, la limitada disponibilidad y calidad de los datos en torno al UAM y a la RAM crean barreras que impiden ampliar la comprensión de dicho impacto. Estas limitaciones de datos también son más frecuentes en contextos que carecen de los recursos necesarios para desarrollar y mantener sistemas sistemáticos y centralizados de recopilación y cotejo de datos. Incluso en las regiones que cuentan con sistemas sólidos de seguimiento del UAM y la RAM, los datos siguen siendo limitados, de modo que los costes con antimicrobianos y las repercusiones de la resistencia a estos siguen sin estar claros. Además, las actuales estrategias de financiación de la investigación se han centrado menos en la recopilación de datos primarios, lo que añade más obstáculos a la hora de llenar el vacío de datos y reducir la brecha mundial de conocimientos sobre el UAM y la RAM. Para superar la escasez de datos y aprovechar las iniciativas de investigación previas y en curso, es fundamental adquirir un conocimiento detallado de las personas, los proyectos y los consorcios de investigación dedicados al tema del uso de antimicrobianos y la resistencia a estos.

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee.

The year 2020 has marked the spread of a global pandemic, COVID-19, challenging many aspects of our daily lives. Different organizations have been involved in controlling this outbreak. The social distancing intervention is deemed to be the most effective policy in reducing face-to-face contact and slowing down the rate of infections. Stay-at-home and shelter-in-place orders have been implemented in different states and cities, affecting daily traffic patterns. Social distancing interventions and fear of the disease resulted in a traffic decline in cities and counties. However, after stay-at-home orders ended and some public places reopened, traffic gradually started to revert to pre-pandemic levels. It can be shown that counties have diverse patterns in the decline and recovery phases. This study analyzes county-level mobility change after the pandemic, explores the contributing factors, and identifies possible spatial heterogeneity. To this end, 95 counties in Tennessee have been selected as the study area to perform geographically weighted regressions (GWR) models. The results show that density on non-freeway roads, median household income, percent of unemployment, population density, percent of people over age 65, percent of people under age 18, percent of work from home, and mean time to work are significantly correlated with vehicle miles traveled change magnitude in both decline and recovery phases. Also, the GWR estimation captures the spatial heterogeneity and local variation in coefficients among counties. Finally, the results imply that the recovery phase could be estimated depending on the identified spatial attributes. The proposed model can help agencies and researchers estimate and manage decline and recovery based on spatial factors in similar events in the future.

Information Needs Assessment for Coastal and Marine Management and Policy: Ecosystem Services Under Changing Climatic, Land Use, and Demographic Conditions.

Changing climatic, demographic, and land use conditions are projected to alter the provisioning of ecosystem services in estuarine, coastal, and nearshore marine ecosystems, necessitating mitigation and adaptation policies and management. The current paradigm of research efforts occurring in parallel to, rather than in collaboration with, decision makers will be insufficient for the rapid responses required to adapt to and mitigate for projected changing conditions. Here, we suggest a different paradigm: one where research begins by engaging decision makers in the identification of priority data needs (biophysical, economic, and social). This paper uses synthesized interview data to provide insight into the varied demands for scientific research as described by decision makers working on coastal issues in Oregon, USA. The findings highlight the need to recognize (1) the differing framing of ecosystem services by decision makers versus scientists; and (2) the differing data priorities relevant to inland versus coastal decision makers. The findings further serve to highlight the need for decision makers, scientists, and funders to engage in increased communication. This research is an important first step in advancing efforts toward evidence-based decision making in Oregon and provides a template for further research across the US.

A multi-stakeholder participatory pilot study of the data demands of the future Ethiopian dairy sector.

Background:  This paper describes a pilot study undertaken in 2018, to determine the key data needs of each of the different Ethiopian dairy sector stakeholder groups.  The study aimed to characterise the emerging trends of dairy product production, processing, retailing and consumption in Ethiopia, and to identify and characterise current and future data needs of different stakeholders. Methods:  The study undertook a mapping of the interactions between different stakeholders in the dairy sector, and an interactive evaluation of the institutional data repository and access options.  Focus group discussions and interviews were held in three regions of the country prior to a two-day workshop in the capital Addis Ababa.  Data needs were characterised by type, availability, format, level of detail, methods of dissemination, uptake and use, and the institutional arrangement, including the different roles of public and private sectors in decision making processes. Results:  The study highlighted the main data needs and identified several broader institutional issues constraining the further development of the Ethiopian dairy sector.  The stakeholder groups endorsed the reactivation of a national dairy board, independent of government but closely incorporating government, and with the buy-in and membership of private sector enterprises, including producers, processers, service providers and consumers, to provide clearer facilitative leadership on the dairy industry. Conclusions:  The study workshop provided a timely discussion between diverse stakeholders, including government, and several potential organisations were suggested to host and manage a national dairy database. Importantly, the reactivation of a national dairy board was strongly endorsed.  It was recommended that stakeholder links be established, sector-specific data needs be elevated to higher detail, and a national roll out of herd-specific data recording schemes was called for, to allow for effective evidence-based policies and decision making.

Mercury transport and fate models in aquatic systems: A review and synthesis.

Mercury contamination in aquatic systems has been an issue to the natural ecosystem and human health. Environmental models have become a valuable decision-making tool and play a significant role in mercury pollution control and management. This paper gives an overview of currently available models for simulating mercury transport and fate in aquatic systems. The mercury transformation mechanisms included in these models were identified, as well as data limitations in the models' application. Future advances in understanding mercury transport, cycling, and biogeochemistry in both water column and sediment will improve the robustness of current modeling applications. Moreover, additional field data are critically needed to better predict the concentrations of multi-phase mercury species in various aquatic systems, including measurements in the water column, benthic sediments, and organisms. Field data are also crucial for model calibration and validation. Without this information it will not be possible to adequately understand the environmental factors controlling mercury fate in aquatic systems. The insufficient quantity of adequate measurements and the unsatisfactory accuracy of mercury models are, in numerous cases, supplemented by mass balances since they diminish the unreliability of models. Mercury science evolves gradually with the advancement of science and technology, which requires that mathematical modeling of mercury transport and transformation should be consistently updated.

Developing new systems of data to advance a culture of health.

INTRODUCTION: The system dynamics that are driving changes in health and health care in the United States are not well captured by standard data-collection activities. We need data systems that can inform policy and program development and can reflect the increasing recognition that all aspects of people's lives-their work, families, and communities and not just formal health and health care services-support active and healthy living. CULTURE OF HEALTH ACTION AREAS: Within the Culture of Health (COH) framework, four action areas are further upstream in the sequence of change and point to additional need for more nuanced approaches to data collection: building a shared value of health; fostering collaborations to improve well-being; creating health in more equitable community environments; and transforming health and health care systems. These action areas define the COH framework that we hope will spur research and strategies across sectors to improve health. CONCLUSION: The action framework for advancing a COH will guide the Robert Wood Johnson Foundation's (RWJF) grant making and strategic collaborations. It is hoped that the framework will also catalyze changes in how researchers and organizations collect health-related data at all levels.