One health outlook最新文献

Background: Despite ongoing prevention and control efforts, the mpox outbreak in Africa has persisted. Between 1 January 2024 and 7 December 2025, a total of 60,997 confirmed cases and 244 deaths have been reported across 34 African countries. Notably, 70% of these cases (n = 43,052) occurred in the 2025, indicating a marked escalation in outbreak intensity. The epicentre of transmission has shifted from Central Africa, where clade I (a and b) of the mpox virus predominates to West Africa, where clade II (a and b) is now more prevalent highlighting a widening and more diffuse spread of the outbreak. In this article, we examine the key drivers sustaining transmission using a narrative synthesis approach and propose practical, evidence-based recommendations to halt further spread.

Main text: While several structural and systemic factors are responsible for the persistent transmission of mpox, we argue that the immediate challenge lies in the suboptimal strategic implementation of existing outbreak response interventions. Our analysis identifies seven key drivers of the ongoing spread namely inadequate surveillance and laboratory investigation strategies, weak data management systems and underreporting and insufficient follow-up of contacts. Other drivers are the widespread use of home-based care for confirmed cases, often in settings with poor infection prevention and control, limited community engagement, participation and ownership of outbreak response efforts and poorly targeted vaccination interventions, largely due to weak or incomplete data and the chronic conflicts in some of the affected countries. To address these issues, we recommend a shift toward more evidence-informed and context-specific implementation of traditional prevention and control measures. Specifically, we call for alignment of surveillance strategies with local mpox epidemiology and transmission dynamics, strengthening laboratory capacity, including genomic sequencing and revision of case definitions based on current clinical and epidemiological data. Additionally, we recommend enhancement of outbreak data management systems with digital and innovative technologies, adoption of evidence-based and context-specific risk communication and community engagement and case management models and deployment of data-driven vaccination strategies.

Conclusion: Considering the foregoing, there is an urgent need to rethink and refocus current mpox outbreak response strategies in Africa.

Zoonotic diseases continue to pose significant public health threats worldwide, driven by complex interactions at the human-animal-environment interface. Geospatial modelling has emerged as a critical tool for identifying disease hotspots and supporting One Health-oriented surveillance and intervention strategies. However, a systematic synthesis of how geospatial approaches operationalize One Health principles remains limited. A systematic review was conducted following PRISMA 2021 guidelines to synthesise peer reviewed studies published between 2000 and 2025 that applied geospatial modelling to identify zoonotic disease hotspots. Multiple bibliographic databases were searched, and studies were screened using predefined inclusion criteria. Data were extracted on modelling approaches, predictor variables, geographic focus, and levels of One Health integration, followed by qualitative and quantitative descriptive synthesis. A total of 46 studies met the inclusion criteria. Publication output increased markedly after 2020, with studies concentrated in Africa, Asia, and Europe. Bayesian spatial models, satellite imagery-based analyses, machine learning methods, and ecological niche modelling were most frequently employed. Climatic variables dominated predictor selection, while socio ecological and animal health variables were less consistently integrated. Full integration of human, animal, and environmental domains was observed in only 15.2% of studies, with most exhibiting partial or implicit alignment with One Health principles. Data availability, quality, and spatial and temporal resolution were the most reported limitations. Geospatial modelling plays an increasingly important role in zoonotic disease hotspot identification, yet its capacity to operationalise One Health remains constrained by data fragmentation and uneven domain integration. Strengthening integrated surveillance systems, expanding socio ecological predictor inclusion, and promoting harmonised methodological standards are essential for enhancing the policy relevance and operational impact of geospatial approaches in zoonotic disease prevention and control.