This study presents an advanced airborne transmission risk assessment model that integrates both short- and long-range routes in the spread of respiratory viruses, building upon the CERN Airborne Model for Indoor Risk Assessment (CAiMIRA) and aligned with the new World Health Organization (WHO) terminology. Thanks to a two-stage exhaled jet approach, the model accurately simulates short-range exposures, thereby improving infection risk predictions across diverse indoor settings. Key findings reveal that in patient wards, the short-range viral dose is 10-fold higher than the long-range component, highlighting the critical role of close proximity interactions. Implementation of FFP2 respirators resulted in a remarkable 13-fold reduction in viral dose, underscoring the effectiveness of personal protective equipment (PPE). Additionally, the model demonstrated that an 8 h exposure in a poorly ventilated office can equate to the risk of a 15 min face-to-face, mask-less interaction, emphasizing the importance of physical distancing and source control. We also found in high-risk or low-occupancy settings, that secondary transmission is driven more by overall epidemic trends than by the presence of individual superspreaders. Monte Carlo simulations across various scenarios, including classrooms and offices, validate the model’s robustness in optimizing infection prevention strategies. These findings support targeted interventions for short- and long-range exposure to reduce airborne transmission.

Marburg virus disease (MVD) is a severe and often fatal illness caused by the Marburg or Ravn virus. Given the remote areas affected and the infrequency of the disease, the MVD presenting syndromes are unclear, and this may limit timely recognition. We conducted 333 a literature review of published case reports and outbreak investigations from January 1st, 1967 to October 30th, 2024, to describe the prevalence of MVD-associated symptoms and syndromes. 722 cases of MVD occurred across 18 outbreaks, with detailed clinical data available for 325 cases. Common symptoms include fever, headache, fatigue, and myalgia; gastrointestinal symptoms are also frequently reported. Haemorrhagic symptoms, mainly hematemesis and bloody diarrhoea, are more specific but less frequent. The overall lethality rate is 72% (95% CI: 68.8–75.0%), dropping to 44% (95% CI: 37.1–50.9%) among PCR-confirmed cases. Variability in prevalent symptoms across different outbreaks complicates early recognition. The lower lethality observed in PCR-confirmed cases may reflect earlier access to appropriate care once Marburg virus disease was recognized, as well as potential misclassification of non-MVD febrile illnesses among unconfirmed cases. This work was supported by the Italian Ministry of Health, Project P3 - Ricerca Corrente Linea1 - Malattie infettive tropicali e neglette: aspetti patogeneteci, immunologici e diagnostici del Ministero della salute-INMI L.Spallanzani I.R.C.C.S.

Background This case study describes and analyses an action research initiative undertaken by management, staff and WHO at the St. Orsola-Malpighi Polyclinic in Bologna, Italy. The initiative utilised staff engagement approaches developed during the COVID-19 pandemic to rethink and reshape future development plans. The initiative provides a ‘how-to’ case study for complex health facilities on ways to create similar multisectoral, inclusive and holistic processes in planning structural, functional and organizational solutions for their ‘hospitals of tomorrow’.Methods The case study utilised an action research approach coordinated by a team of WHO facilitators in close collaboration with the Board of Hospital Directors. Heterogeneous and multidisciplinary working groups were created, with members from different levels of the hospital staff. In the context of facilitated group meetings held weekly over a one-year period, participants were asked to review topics of interest to future plans of the hospital and make recommendations on effective/innovative ways of addressing these in the short and long term. Working groups focused on different challenges.Results The initiative was successful in creating and sustaining broad staff engagement in the future planning processes. 80% groups maintained high staff participation throughout the entire project year. Participating staff reported enhanced communication and cooperation between departments represented in different groups. 87% of the proposed plans suggested by the working groups were approved by the Board for implementation.Conclusion Key factors contributing to the high approval rate of plans, strong engagement record of staff and enhanced cooperation between involved departments; included: multisectoral/cross hierarchal staff involvement, group attention to defining time-bound contextual goals, flexible implementation monitoring approaches, personnel skills and profiles of participants, direct and open communication at all levels and times, member commitment and clear exit strategy. The case study is presented as a model to stimulate similar actions in other complex health care facilities.

Chlorine spraying was widely used during filovirus outbreaks, but concerns about occupational health risks led to a shift toward wiping. This systematic review aimed to evaluate the health risks associated with exposure to disinfectants among healthcare workers (HCWs), with a specific focus on chlorine-based products and spraying compared to alternative disinfectants and general disinfection tasks (GDTs). PubMed, Embase, and Scopus were searched from inception to March 2025. Eligible studies included observational or experimental research on HCWs exposed to chemical disinfectants. Two reviewers independently screened studies, assessed the risk of bias using a validated occupational health tool, and evaluated evidence certainty with the GRADE approach. Meta-analyses used fixed- and random-effects models; heterogeneity was assessed with I² statistics. Out of 7154 records, 29 studies were included. Most studies were cross-sectional with a high bias risk. Odds ratios (ORs) were calculated using non-exposed groups as reference. Significant associations with respiratory conditions were found for chlorine-based products (OR 1.71), glutaraldehyde (OR 1.44), spraying (OR 2.25), and GDTs (OR 2.20). Exposure to chlorine-based products, glutaraldehyde, spraying, and GDTs likely increases respiratory risk in HCWs, as supported by moderate-certainty evidence. These findings support prioritizing safer disinfectants and strengthening protective measures over banning specific application methods.

Background: Public health events of international concern highlight the need for up‐to‐date evidence curated using sustainable processes that are accessible. In development of the Global Repository of Epidemiological Parameters (grEPI) we explore the performance of an agentic‐AI assisted pipeline (GREP‐Agent) for screening evidence which capitalizes on recent advancements in large language models (LLMs). Methods: In this study, the performance of the GREP‐Agent was evaluated on a data set of 2000 citations from a systematic review on measles using four LLMs (GPT4o, GPT4o‐mini, Llama3.1, and Phi4). The GREP‐Agent framework integrates multiple LLMs and human feedback to fine‐tune its performance, optimize workload reduction and accuracy in screening research articles. The impact on performance of each part of this Agentic‐AI system is presented and measured by accuracy, precision, recall, and F1‐score metrics. Results: The results show how each phase of the GREP‐Agent system incrementally improves accuracy regardless of the LLM. We found that GREP‐Agent was able to increase sensitivity across a broad range of open source and proprietary LLMs to 84.2%–88.9% after fine‐tuning and to 86.4%–95.3% by varying workload reduction strategies. Performance was significantly impacted by the clarity of the screening questions and setting thresholds for optimized workload reduction strategies. Conclusions: The GREP‐Agent shows promise in improving the efficiency and effectiveness of evidence synthesis in dynamic public health contexts. Further development and refinement of adaptable human‐in‐the‐loop AI systems for screening literature are essential to support future public health response activities, while maintaining a human‐centric approach.