One Health最新文献

With its compact size, resilience at high altitudes, and high feed efficiency, the guinea pig (Cavia porcellus) is a sustainable and high-quality protein option for people in resource restrictive areas of South America's Andean region. Each year in Ecuador, 47 million guinea pigs, destined for sale or household consumption, are produced. Despite the reported presence and anticipated growth of guinea pig production in the region, husbandry standards in this industry have not been fully documented. A qualitative study was conducted to explore the thoughts, attitudes, and practices of guinea pig producers in three rural parishes of Pichincha, Ecuador regarding guinea pig production, health, and welfare. During October-December 2024, a focus group was held in each parish with discussion including the basic principles of animal production and husbandry (i.e., breeding, feeding, treatment, preventative activities, euthanasia). Focus group transcripts underwent thematic analysis. Inductive codes were identified via an iterative open coding process with two independent coders, until a unifying theme was identified. Nineteen guinea pig producers participated across the three focus groups. A One Health approach was identified as the primary domain under which the identified themes fell. The main unifying theme mapped back to the concepts of traditional and modern medicine. The rural Ecuadorian guinea pig producers included in this study implement a combination of traditional and modern medicine and production practices to ensure the humane production of this species. When developing and implementing future studies and educational programs, researchers, veterinarians, and agricultural educators should consider blending these two strategies to ensure the industry can improve in a One Health-One Welfare way.

Climate change poses critical risks to humans and animals, particularly during outdoor events. The Soma Nomaoi Festival in Fukushima, Japan, with a thousand-year history involving horses and riders, has become vulnerable to rising summer temperatures. In 2023, during a record high of 35.2 °C, 83 heatstroke cases occurred, including 74 among spectators and nine among horse riders, with two horse fatalities and 111 horses requiring medical care. In response, organizers rescheduled the 2024 festival to May, resulting in a maximum temperature of 24 °C. Human heatstroke cases dropped by 83 % (to 18 cases), and equine cases fell from 111 to 38. Although injuries from heightened horse activity increased, overall welfare improved. This case illustrates how traditional festivals can adapt to climate change while preserving cultural integrity. The experience demonstrates the value of the One Health approach in balancing cultural tradition, human safety, and animal welfare.

Background: Guinea-Bissau is a fragile state marked by political instability, weak governance, and fragmented institutions. Despite these challenges, recent international support and policy initiatives have promoted a growing interest in adopting a One Health (OH) approach to integrated human, animal, and environmental health surveillance.

Objectives: To explore the feasibility of developing a national One Health surveillance (OHS) system in Guinea-Bissau through stakeholder insights into governance, system integration, and technological and community factors.

Methods: A qualitative study, specifically a focus group discussion with seven purposively selected professionals from human, animal, and environmental health sectors, was conducted. Participants were experienced stakeholders from national institutions, non-governmental organizations, and international agencies. Discussions were guided by a pre-tested script, recorded in Creole, transcribed into Portuguese, and analyzed using inductive Thematic Analysis.

Results: Key barriers identified included: (1) political instability and lack of legal frameworks undermining long-term governance; (2) fragmented and uncoordinated health programs with limited territorial reach; (3) poor integration of surveillance systems and technological infrastructure; and (4) insufficient funding and training. However, participants highlighted opportunities, such as leveraging digital technologies (e.g., drones, artificial intelligence, big data), public-private partnerships, and increasing international engagement. Emphasis was placed on developing inclusive, interoperable platforms across different sectors and ensuring ethical data governance. Community involvement and tailored capacity building were deemed essential to system resilience and effectiveness.

Discussion: Findings align with regional and global evidence on the structural and operational barriers to OH implementation in fragile contexts. Despite major challenges, a phased, multisectoral strategy supported by legal reforms, sustainable financing, technological adaptation, and inclusive stakeholder engagement could enable Guinea-Bissau to build a functional OHS system.

Conclusion: Developing a OHS system in Guinea-Bissau is feasible if supported by institutional reforms, digital integration, sustained funding, capacity building, and strong community and civil society participation. Strategic coordination across sectors, grounded in ethical and equitable frameworks, is essential for long-term success.

This systematic review investigates how One Health systems, integrated digital platforms combining human, animal, and environmental health data, are currently designed and implemented for infectious disease detection and management. The study aims to identify integration patterns, functional purposes, and user interactivity across 202 reviewed systems published between 2015 and 2024. It categorized these systems by their purpose, diseases addressed, data types (human, animal, environmental), and user groups, such as public health officials and researchers. The tasks performed include data collection, analysis, visualization, and decision-making. Interactive techniques range from interactive filtering to predictive modeling, with varying levels of user interactivity, and note whether functional systems are available online. The search strategy utilized the keywords "one health dashboard visualization system OR one health dashboard OR one health system" across various databases Including IEEE xplore ScienceDirect PubMed And google scholar As well as other sources. While a significant portion of studies still rely on single-domain data, i.e., 20% of studies use only human data, 12% use only animal data, and 10% use only environmental data. The largest group (30%) integrates human and animal data, followed by 12% combining human and environmental data, and a smaller portion (1%) integrating animal and environmental data. The details of this comprehensive survey can be found on this webpage: https://onlylinks.cc/DjHH. There is a clear trend toward integrating multiple datasets, especially Human and Animal data. However, fully integrated One Health systems that combine all three domains remain relatively limited and often take the form of commentaries rather than applied systems, highlighting an opportunity for more comprehensive, data-driven implementations in future research.

Antimicrobial resistance (AMR) in foodborne bacteria is an escalating global public health challenge, threatening the effectiveness of antibiotics and food safety. This review examines AMR trends in foodborne bacteria, compares management strategies across different regions, and explores policies aligned with the One Health approach. Data from Taiwan, the United States, the European Union, Japan, and Africa indicate that foodborne pathogens exhibit significant resistance to antibiotics, posing serious challenges to public health and food systems. In response to this growing challenge, nations have implemented surveillance programs, national action plans, and public awareness campaigns, often guided by the World Health Organization (WHO) and international frameworks. It also proposes key management strategies, including risk assessment, environmental monitoring of food production and processing, and enhanced cross-sector collaboration. By integrating national AMR management efforts with global best practices, countries can strengthen their capacity to address this pressing challenge. Collaborative actions, including policy alignment, research innovation, and cross-sector cooperation, are essential for achieving more effective control of foodborne AMR pathogens worldwide.

Blastocystis is one of the most prevalent intestinal protists, colonizing more than one billion people worldwide. Nevertheless, its role in health and disease remains blurred. Blastocystis was historically dismissed as a commensal. However, it can have pathogenic or protective effects. This review synthesizes molecular epidemiology, clinical research, microbiome studies, and experimental models through a One Health approach to reassess Blastocystis. Subtypes ST1-ST4 are dominant in humans, but their health outcomes vary. ST4 is associated with irritable bowel syndrome and inflammatory responses. However, it has also been shown to exert protective effects on murine colitis models. In contrast, ST3 is frequently detected in healthy individuals with a diverse gut microbiota. Blastocystis is also widespread in animals, untreated water, wastewater, and food, reflecting complex transmission dynamics and raising concerns in low- and middle-income countries where poverty-related exposures increase risks. Diagnostic advances have improved detection, although mixed infections and inconsistent clinical interpretations persist, and treatment guidelines remain absent. Rather than being a uniform pathogen or benign passenger, Blastocystis emerges as a context-dependent component of the gut ecosystem and environmental microbiota. Its ubiquity across humans, animals, and the environment requires integrated surveillance, subtype-informed research, and interdisciplinary health strategies. Recognizing the ecological complexity of Blastocystis is essential for equitable diagnostics, treatment, and public health responses within the One Health framework.

Vibrio has emerged as one of responsive pathogens to the conditions imposed by global warming, with an increasing impact in northern Europe. The epidemiological significance of these pathogens remains undetermined in the south of Europe. We analyzed clinical and epidemiological data from cases in southern Spain, a well-established climate hotspot. A 13-year retrospective analysis identified 167 clinical infection cases. Monthly seawater temperatures since 2010 were also evaluated to assess their correlation with infection occurrence. V. alginolyticus, Shewanella putrefaciens, S. algae, V. parahaemolyticus, V. fluvialis, and V. vulnificus were the most frequently isolated species from clinical cases such as otitis, gastroenteritis, infected wounds, and sepsis. An increase in incidence was observed over the study period in parallel to the warming trend in coastal waters. While this suggests an association between environmental change and Vibrio infections, additional factors such as population exposure patterns may likely also contribute. These findings underscore the need for surveillance systems to monitor the burden of these infections.

Global escalation of infectious disease outbreak risks necessitates advanced predictive models. Despite methodological advances, errors in initial states and parameters of epidemiological dynamic models remain a key limitation to prediction reliability. To address this limitation, we propose an optimized data assimilation framework for combined state-parameter optimization based on Ensemble Kalman Filter. We design space transformations and adaptive covariance inflation driven by epidemic development and prediction errors, achieving a more stable update process and rapid response to epidemic changes. Through synthetic experiments and real-world case studies, the proposed scheme significantly reduces initial state and parameter errors, leading to a substantial improvement in prediction accuracy during the early stages of an epidemic. Compared with predictions without data assimilation, the average prediction error rate decreased by more than 50 % for 1-day predictions and by approximately 15 % for 7-day predictions. The prediction accuracy rate for the peak day of the epidemic and the peak number of infected cases reached more than 70 % in advance by 3 days. Critically, simple dynamical model integrated with our data assimilation framework outperform complex models without data assimilation. This study establishes data assimilation as an essential tool for epidemic forecasting and provides an extensible framework adaptable to multiple infectious diseases, offering critical support for public health decision making.