Swiss Medical Weekly

Background. The recent approval of long-acting monoclonal antibodies (la-mAbs) and a maternal vaccine (MV) in the EU enables universal RSV prevention in infants. Modelling studies are widely used to quantify the population-level impact of alternative immunisation strategies. However, existing assessments of new RSV immunisation products focus on national or sub-national settings. Methods. We developed an age-stratified, stochastic compartmental model of RSV transmission for 28 EU/EEA countries. It combines literature-based parameters on RSV natural history and product efficacy with country-specific demographic and contact patterns. After model calibration against age- and country-specific RSV hospitalisation rates, we designed scenarios for both la-mAbs and MV at four coverage levels, with and without catch-up immunisation for infants under six months at season onset. We then evaluated each scenario against a no-immunisation baseline. Results. At 95% coverage, the cross-country median reduction in RSV hospitalisations over one season in infants under 12 months is 29.9% for la-mAbs (country median range: 27.7-33.9%) and 22.4% for MV (20.0-25.6%), scaling linearly with coverage. Out of all averted hospitalisations, 78.3% (90% CI: [67.3, 92.7]%) are concentrated in infants aged 0-2 months for la-mAbs and 72.7% (90\% CI: [61.4, 88.6]%) for MV. A catch-up campaign nearly doubles the overall reduction in RSV hospitalisations. Conclusions. Despite country-specific heterogeneities, impact of la-mAbs and MV is comparable across settings and herd-immunity effects are largely negligible. This supports harmonised European guidelines on coverage targets. Seasonal catch-up campaigns emerge as an effective lever to maximise the impact of immunisation programmes.

Background During infectious disease outbreaks, characteristics of reported cases are routinely collected. These give information on becoming infected but not on infecting others. We assess whether linking infectees to infectors, together with their characteristics, can help understand transmission. Methods From the start of the COVID-19 pandemic in the Netherlands, reported cases were asked to identify their most probable infector in routine surveillance, enabling the linking of cases. We assess for the period 27 February 2020 - 11 April 2022 whether the infectees of these transmission pairs are representative of all reported cases, whether the transmission pairs yield verifiable estimates of epidemiological characteristics (here the serial interval), and whether they provide information on transmission that cannot be obtained otherwise. Results Of 8,003,008 reported cases, 678,482 (8.5%) could be linked to their most probable infector. These infectees were largely representative of the reported cases regarding age group, sex, and geographical location. The mean serial interval of 3.6 days (sd 3.4 days) from transmission pairs aligns with literature. Transmissions between age groups largely follow known contact patterns. Most transmissions in September 2021 occurred between persons who were not (fully) vaccinated, indicating the effectiveness of the vaccine, and relatively few between persons with different vaccination status, indicating assortative mixing in vaccination status. Conclusion Transmission pairs can be efficiently collected in routine surveillance, providing insight into disease transmission. The current post-pandemic period provides an excellent opportunity to adjust reporting systems for linking infectees to their most probable infector as preparation for future outbreaks.

Background: Mass gathering events (MGEs) are associated with several public health challenges and may cause a strain on healthcare services. Literature findings on the impact of MGEs on emergency departments (EDs) are heterogeneous. Objectives: To examine shifts in ED attendance characteristics during a major sporting tournament, namely the UEFA European Football Championship 2024 held in Germany. Methods: We conducted a retrospective observational study using ED data from the Emergency Department Data Registry. We compared baseline ED attendance characteristics between the tournament and the reference period, defined as two weeks before and two weeks after the tournament, and between Germany game days and non-Germany game days. Hourly attendance patterns were analysed for all Germany games using a reference range. Results: We included data from 41 EDs, totalling 253,493 attendances during the study period. A 1.57% increase in attendance was observed during the tournament compared to the reference period, with baseline characteristics remaining similar. The median daily attendance within all EDs was slightly lower on Germany game days (4066) compared to non-Germany game days (4128). Modest changes were observed in the hourly attendance on Germany game days, most notable during the last Germany game where a decrease in attendance below the reference range extended over three hours. Conclusions: The observed shifts in ED attendance were minimal, suggesting that no major changes of public health relevance occurred in ED attendance during the tournament. We highlight the utility of using ED data for monitoring and for enhancing the understanding of the public health risks and challenges associated with MGEs.

This study mapped the age- and region-specific risks of eye diseases in the Brazilian population, evaluating temporal trends and geographical inequalities in access to healthcare. Secondary data from DATASUS, covering the 27 Brazilian federative units from 2010 to 2024, were used, employing hierarchical negative binomial regression. A significant national increase in hospital admission rates was observed during the studied period, with increases of 160.8% for retinopathy, 126.4% for eye and appendage diseases, and 122.8% for glaucoma. State-level heterogeneity was extreme, with variations spanning from -93.1% to +3588% for glaucoma, for example. Even so, regional disparities were observed throughout the period; the South region reported an average 43.2% higher than the national average for retinopathies, and the Southeast 28.5% higher for eye and adnexal diseases, while the North region reported the lowest rates. Projections up to 2036 predict a further national increase of up to +377.0% for retinopathies, with interventions covering more than an order of magnitude. In addition to the temporal projection, rates in state, age, and year components on a logarithmic scale with calibrated uncertainty were verified. Out-of-sample tests show that the chosen modeling outperforms the last observed value maintenance method and naive linear extrapolation in all three diseases considered. Thus, the escalating, age-driven burden of ophthalmological diseases and profound geographic disparities highlight an urgent need to decentralize specialized care and target resource allocation within the public health system.

Abstract Background: Schools are widely recognised as key settings for promoting childrens health behaviours. However, many schools struggle with the implementation and especially sustainment of health promotion programmes e.g. due to limited resources. Strengthening schools capacity for health promotion has therefore been identified as a central strategy for achieving better implementation and ultimately behaviour change outcomes among children. The fit4future Kids programme was developed as a large-scale, multi-component initiative in Germany that aims to promote childrens physical activity, nutrition, mental health, and responsible digital media use while simultaneously supporting schools in building structures for sustainable health promotion. Methods: This paper describes the intervention and evaluation protocol of the nationwide fit4future Kids programme implemented in several cohorts of German primary schools from Sept. 2022 to Sept. 2027. The intervention is based on the Health Promoting Schools framework and integrates established implementation and behaviour change frameworks, including the Consolidated Framework for Implementation Research, the COM-B model, and Behaviour Change Techniques. The programme combines curricular materials, environmental components, and structured implementation support to facilitate the integration of health promotion into everyday school practice. The evaluation follows a mixed-methods design involving multiple stakeholder groups, including school staff, parents, and children. Quantitative and qualitative data are collected to assess implementation processes, contextual factors, and programme outcomes. The large and diverse sample of 1,153 participating primary schools allows for the exploration of different implementation trajectories and the investigation of potential equity-related effects. Discussion: By combining evidence-based health promotion strategies with implementation science approaches, fit4future Kids provides a large-scale real-world example of how schools can be supported in implementing sustainable health promotion. The evaluation is expected to generate important insights into the implementation and potential effectiveness of multi-component school-based interventions and to inform future initiatives aiming to strengthen health-promoting school environments.

Introduction Education is a core social determinant of health for children and adolescents. Unfortunately, academic achievement, health, and wellbeing of adolescents have decreased in many developed countries in the past decade. The purpose of the Wellbeing and Education linkages in school-aged children (WELL-ED) study is to examine associations of school absences and academic achievement with use of school-based and community-based health and social welfare services. In addition, we will assess user experiences and multi-sector services pathways of school-aged children for a better understanding of how the service system could respond to the needs of children. Methods and analysis WELL-ED is a large population-based study that combines register data on school absences and educational support from municipalities with register data on healthcare and social service use collected from wellbeing services counties in Finland. The study cohort includes all children who attended mandatory education in public schools in Southern Finland in school year 2023-2024. A smaller cohort of adolescents in school year 8 was invited to complete a user experience survey. The primary outcomes of this study are related to equity of service use. Ethics and dissemination The Regional Committee on Medical Research Ethics of the Helsinki and Uusimaa Hospital District (2803/2024) has approved the WELL-ED study protocol. For the survey, adolescents in year 8 and parents of adolescents younger than 15 provided informed consent. Results will be published in peer-reviewed journals, summaries will be sent to participating municipalities and wellbeing services counties and press releases will be written on key findings.

Background: Many mental health problems originate in childhood, highlighting the need for early preventive approaches. Preventive services to promote children's mental health are offered in the health, education, and social sectors (H-E-S) but are often not used by certain at-risk groups or early enough. To identify children at-risk and provide needs-oriented support, professionals from all sectors must be well trained, collaborate closely to refer to specialized services for specific mental health problems or risk factors, and understand the regional psychosocial support system and its services. A comprehensive approach to preventing mental health problems requires structured planning and a systematic overview of all institutions and services in the region and their collaboration. This study aims to map the preventive mental health and psychosocial support service system and the collaboration between institutions across three sectors (H-E-S) in two exemplary city districts. The study is integrated into a whole-district approach to child mental health promotion that is being implemented in one of the researched city districts, and its results will inform further activities there. Methods: We use a mixed-methods approach, combining qualitative interviews with a quantitative survey to map psychosocial services for children aged 4 to 10 and their families across the H-E-S sectors in two socioeconomically disadvantaged city districts in East and West Germany. All institutions that potentially offer psychosocial services for children and families will be approached to recruit professionals (e.g., schools, practices, counseling centers). To understand the regional psychosocial support system, we will analyze existing services and their characteristics (e.g., target groups, intervention types) descriptively. Social network analysis will be applied to gain an in-depth understanding of collaboration between institutions, to identify potential gaps in services and pathways, and to inform an intervention aimed at improving interinstitutional and intersectoral collaboration. Discussion: To our knowledge, this is the first study to comprehensively analyze regional preventive psychosocial support systems for children and families across sectors at the community level. Previous mappings of psychosocial services have focused on a single sector (e.g., health) or specific diagnoses only. The psychosocial preventive landscape spanning the H-E-S sectors involves complex financing structures and referral logics. Understanding the characteristics of the existing support landscape requires a systematic and comprehensive approach. Our study advances service mapping and operationalization methods in public health research. Additionally, the findings will inform recommendations for improving comprehensive prevention approaches in the selected city districts.

An ongoing outbreak of Bundibugyo virus disease (BVD) in the Democratic Republic of the Congo was deemed a public health emergency of international concern in May 2026. To prevent cross-border importation, many countries, including the United States, Canada, India, Thailand, and Kenya have already proposed containment strategies, and others are likely to follow suit. How well (or poorly) are screening and quarantine containment measures are likely to work? We leverage established epidemiological theory and develop a mathematical model of traveler screening and post-arrival quarantine for BVD to answer this question. We find that traveler screening via symptom screening or molecular testing will miss the majority of infected travelers, and should be complemented by post-arrival quarantine and monitoring of sufficient duration to detect those with long incubation periods. Our findings underscore the limitations of border screening and the importance of complementary measures like post-arrival quarantine to prevent local importation of BVD.

Background. Cross-validation (CV) is widely used to estimate predictive performance, but can overestimate performance when applied at the observation level to repeated-measures data. When continuous predictor variables are measured repeatedly within subjects and the binary outcome is defined at the subject level, naive observation-level CV introduces data leakage through within-subject dependence, producing optimistically biased estimates of the area under the receiver operating characteristic curve (AUROC). The magnitude of this bias and the performance of alternative partitioning strategies have not been formally characterized for this data structure. Methods. Three CV strategies were compared for estimating subject-level AUROC in ridge logistic regression models: naive observation-level 10-fold CV, subject-level 10-fold CV, and leave-one-cluster-out (LOCO) CV. The framework was applied to a motivating clinical dataset of daily oxygenation measures and retinopathy of prematurity outcomes among 101 extremely low birth weight infants. A factorial simulation study was conducted across 162 parameter combinations varying cluster count (20-150), intraclass correlation (0.1-0.5), within-cluster autocorrelation (0.2-0.8), and outcome prevalence (10-35%), with 500 simulated datasets per condition (76,389 valid datasets total). Results. In the motivating dataset, naive CV produced optimism of +0.078 AUROC units for severe ROP prediction (15 events, 101 subjects) and +0.031 for any ROP prediction (48 events). Subject-level 10-fold CV closely approximated LOCO (deviation [≤] 0.015). In the simulation, naive CV optimism ranged from +0.039 to +0.204 across all conditions, increasing monotonically with higher ICC, higher autocorrelation, fewer clusters, and lower event rates. Subject-level 10-fold CV was essentially unbiased relative to LOCO across all 162 conditions (mean absolute deviation = 0.002). Conclusions. Naive observation-level CV meaningfully overestimates discriminative performance in the repeated-measures binary outcome setting and should not be used. Subject-level CV partitioning effectively eliminates this bias. Accordingly, subject-level partitioning should be considered essential, not optional, when validating prediction models using repeated-measures data with subject-level outcomes.

Background Differential contributions to transmission across age groups have been reported for many respiratory infections, including SARS-CoV-2. They are crucial for estimating the impact of age-specific interventions. Disentangling these age-dependent contributions remains challenging, as they may reflect differences in contact rates, biological susceptibility, or infectiousness. Aim We aim to jointly estimate age-specific per-contact infectiousness and susceptibility and their effect on the impact of age-specific interventions. Methods The age-specific infectiousness and susceptibility were jointly estimated in a Bayesian framework by combining contact data with transmission pair data (who-infected-whom). We applied this approach to 197,840 self-reported household transmission pairs collected in the Netherlands during the COVID-19 pandemic. Using these estimates, we projected the expected impact of school closure and work-from-home measures during the early stages of an epidemic in the absence of other interventions. Results Both infectiousness and susceptibility to SARS-CoV-2 infection were lowest in children aged 0-9 years and highest in adults over 30 years old, with 2- to 4.5-fold differences between these groups. Projected impacts of age-specific interventions indicated that school closures would reduce the reproduction number by 8% or 29% when age-specific susceptibility and infectiousness were or were not considered, respectively. Conversely, working-from-home policies would lead to reductions of 41% with and 20% without age-specific infectiousness and susceptibility. Conclusion Our method enables robust estimation of age-specific infectiousness and susceptibility. Accounting for these age heterogeneities is essential for projecting the impact of age-targeted interventions. Our approach is adaptable to other respiratory infections and can guide more tailored public health responses.

Pooled testing programs were introduced during the COVID-19 pandemic to expand surveillance capacity while preserving testing resources, but evidence on their epidemiological impact in schools under real-world conditions remains limited. We analyzed data from the pooled testing program implemented in public primary schools of the canton of Basel-Landschaft, Switzerland, during the Fall-Winter 2021 Delta wave. We used an agent-based transmission model informed by pooled and individual testing results, school characteristics, contact networks, and community incidence. The model was fitted to pooled positivity ratios in four clusters of administrative areas with similar epidemic trajectories. We compared pooled testing with alternative protocols in terms of school transmission, testing volume, and student-days lost. During the study period, pooled testing was offered to 21'187 students across 62 public primary schools, with high and stable participation across clusters (mean 71-79%). The fitted model reproduced observed pool positivity trends well. Compared with pooled testing, reactive class closure, reactive screening, and symptomatic testing were associated with higher in-school transmission, with excess ranging from 50% to 87%, 63% to 104%, and 72% to 133% across clusters. Weekly individual screening achieved similar reductions in transmission but required 15-25 times more tests. Relaxing class closure after depooling substantially reduced student-days lost without increasing transmission. Under real-world conditions, pooled testing provided an effective and resource-efficient strategy to reduce SARS-CoV-2 transmission in primary schools. Combining early detection of asymptomatic infections with low testing demands, pooled testing offers a scalable approach to school surveillance and control for pandemic response in educational settings.

We used a stochastic simulation model to estimate the effectiveness of combined exit and entry airport screening for Bundibugyo ebolavirus disease (BVD), using natural-history parameters from a Bayesian re-analysis of the 2012 Isiro outbreak. For a 12-hour international flight from DRC or Uganda at 86% screening sensitivity, we estimate 65% of infected travellers would arrive undetected (95% CrI: 38 - 76%). The main driver of this outcome is the relative duration of the the incubation period (approximately 7.7 days) and the onset-to-severe-disease interval (approximately 4 days): most infected travellers board before symptom onset and are undetectable by any syndromic screen, whilst those who are symptomatic progress rapidly to illness severe enough to preclude travel. This is compounded during active epidemic growth, when recently exposed (and therefore pre-symptomatic) cases are overrepresented among travellers. Syndromic airport screening offers limited protection against BVD spread via air travel, and should be complemented by outbreak control at source and strengthened clinical surveillance in receiving countries with high travel connectivity to affected areas.

The multinational Andes virus outbreak linked to the MV Hondius has exposed contacts across several countries, but the absence of further confirmed cases remains difficult to interpret given the long incubation period. We estimate the probability that secondary clusters may emerge using a stratified branching-process model parameterized with country-level tracing and isolation indicators. The risk of sustained spread is low, but secondary clusters remain plausible under imperfect isolation or pre-symptomatic transmission. These results support coordinated contact tracing and effective isolation while exposed contacts remain within the risk window.

Infections at the animal-human or wildlife-livestock interfaces have severe health and socio-economic consequences. Combined with empirical data, mathematical models can contribute to a better understanding of the reservoirs of these infections, which is a priority for mitigating their impact by using appropriate management interventions. Taking brucellosis in the Bargy massif (French Alps) as an example of a zoonosis at the wildlife-livestock interface, we developed and calibrated a multi-host model integrating data on direct and environment-mediated cross-species contacts from field observations. Estimates of the basic reproduction number (R0) allowed to identify the population of Alpine ibex (Capra ibex) and its environment as an essential host in the reservoir, driving both pathogen maintenance (within-species R0[≥]1: 1.66, 95% credible interval: 1.42-2.03) and its transmission to livestock (between-species R0>0: 0.035, 0.01-0.05). Our approach can be adapted to other multi-host pathogens, which will contribute to improve the understanding and management of these complex systems.

Human metapneumovirus (HMPV) causes acute lower respiratory infections, primarily affecting young children and older adults, with seasonal outbreaks peaking annually in March or April in the United States and other temperate regions in the Northern hemisphere. However, the factors driving HMPV seasonality in the United States remain poorly understood. We analyzed laboratory-confirmed HMPV cases and age-specific emergency department visits across 10 US regions, fitting an age-stratified dynamic transmission model to assess spatiotemporal patterns and investigate the influence of environmental variables and viral interference from RSV on HMPV transmission rates. We found that models incorporating climate variables into the transmission rate, including vapor pressure, precipitation, potential evapotranspiration, and minimum temperature, could not capture the timing of HMPV activity across all regions. Instead, HMPV timing was associated with RSV activity, with the HMPV transmission rate reduced in the presence of RSV. We showed that, unlike RSV, only models incorporating viral interference could reproduce the biennial pattern of HMPV observed in some regions, characterized by alternating late-small and early-large epidemics. Furthermore, our model successfully reproduced post-COVID-19 HMPV and RSV epidemics and predicted that RSV interventions are not likely to lead to a substantial increase in HMPV activity despite decreasing competition from RSV. Our work unravels the spatiotemporal dynamics of HMPV and its interaction with RSV, informing future seasonal forecasting and intervention strategies for HMPV.

Objective: Lyme disease diagnosis in children is challenging due to atypical presentations and testing limitations. We sought to evaluate the association between Lyme disease and socio-geographic risk factors in children. Materials and methods: We enrolled children undergoing evaluation for acute Lyme disease at one of eight Pedi Lyme Net pediatric emergency departments located in high Lyme disease incidence states over a ten-year period (2015-2024). We defined a case of Lyme disease with an erythema migrans (EM) lesion or a positive two-tier serology result in a child with signs and/or symptoms of acute disease. We linked each childs primary residential county to the following factors: urban-rural residence, socioeconomic status, population-level disease incidence, wildland-urban interface, and "Lyme disease" Google searches. We performed a multi-level logistic regression analysis to evaluate associations between Lyme disease and county factors after adjusting for individual demographics. Results: Among 5,529 children enrolled, 1,396 (25.2%) had Lyme disease: 101 (7.2%) with early-localized disease, 584 (41.8%) with early-disseminated disease, and 711 (50.9%) with late-disseminated disease. Rural residence (aOR 1.9, 95% CI 1.3-2.9), higher socioeconomic advantage (aOR 1.3, 95% CI 1.1-1.4), more "Lyme disease" Google searches (aOR 1.1, 95% CI 1.0-1.2), and higher wildland urban interface (aOR 1.2, 95% CI: 1.0-1.4) were independently associated with Lyme disease. Conclusion: Incorporating socio-geographic factors alongside clinical data may augment diagnostic risk assessment in children with suspected Lyme disease. However, these factors should be incorporated carefully to ensure clinical assessments are not based on a childs geographic location alone.

Background. The ongoing Andes hantavirus outbreak linked to the cruise ship MV Hondius (April-May 2026, seven confirmed cases, three deaths, patients hospitalised across six countries including France) highlights the urgent need for mechanistic tools to predict which hantavirus pulmonary syndrome (HPS) patients will progress to fatal cytokine storm. Methods. We present a 14-variable antigen-gated ordinary differential equation (ODE) model integrating viral dynamics, CD8+ cytotoxic T lymphocyte (CTL) expansion, four cytokines (TNF-alpha, IFN-gamma, IL-6, IL-10), VEGF-mediated vascular permeability, and platelets. We derive two reproduction numbers: the viral invasion number R0 and the immunopathological loop gain Rip. We apply Villani's hypocoercivity theory and the HWI optimal transport inequality to prove that the spectral gap of the CTL-IFN-gamma feedback loop collapses to zero at a critical infected endothelial cell count Ic*, providing a computable early-warning threshold. We define a Wasserstein patient stratification score from six clinically observable variables. Results. At default parameters (R0 = 0.396, Rip = 1.875): (1) the disease-free equilibrium is locally asymptotically stable - the virus self-limits - but the CTL-IFN-gamma loop has sufficient gain to amplify autonomously once established; (2) the storm-block spectral gap collapses exactly to zero at Ic* = 2.23 cells/uL, a threshold attained within hours of infection onset, confirming that immunopathological amplification is essentially unavoidable; (3) the Wasserstein score rises 1-2 days before vascular permeability reaches clinical threshold, providing an early-warning window; (4) exogenous IL-10 supplementation is the single most effective intervention (predicted 40% reduction in peak permeability), outperforming corticosteroid immunosuppression and ECMO; the combination of all three applied at day 7 reduces peak permeability below the fatal threshold. Conclusions. This framework predicts that HPS cytokine storm is a structural consequence of Rip > 1 rather than excessive viral load, explaining death after viral clearance. For clinicians managing MV Hondius Andes virus patients, the model identifies a six-variable triage score and a day-7 IL-10-centred therapeutic window as the highest-priority clinical targets. A live simulator and bedside triage tool are available at xvirus.org.

Background Appendicitis is a readily treatable surgical emergency, yet it remains a cause of preventable death among children in resource-limited settings. While recent studies have documented the global burden of pediatric appendicitis, none have systematically examined its geographic clustering or spatial spillover effects. Understanding whether high-mortality countries cluster geographically, and whether neighboring countries influence each other's outcomes, is essential for designing regional surgical capacity strategies. Methods We conducted a spatial analysis of pediatric appendicitis case fatality rates in children aged 0-14 years across 169 countries from 2000 to 2019. Data were obtained from the Global Burden of Disease Study 2023 and World Bank databases. We calculated global Moran's I to assess spatial autocorrelation, used Getis-Ord Gi* to identify local hotspots, and fitted spatial lag and spatial error regression models to quantify spatial spillovers while adjusting for GDP per capita, physician density, and basic sanitation access. Results Global Moran's I was 0.621 in 2000 (p < 0.001), 0.621 in 2010 (p < 0.001), and 0.592 in 2019 (p < 0.001), indicating strong and persistent spatial clustering. Hotspots at 99% confidence were consistently concentrated in sub-Saharan Africa and parts of South Asia, with little change in geographic distribution over two decades. The spatial error model provided the best fit (AIC = 212.6), with a spatial error coefficient ({lambda}) of 0.663 (p < 0.001), suggesting that approximately 66% of residual variation was explained by unobserved regional factors. In the final model, higher GDP per capita ({beta} = -0.497, p < 0.001) and higher physician density ({beta} = -0.568, p < 0.001) were independently associated with lower case fatality, while basic sanitation access showed no significant association (p = 0.284). Conclusions Pediatric appendicitis case fatality exhibits strong and persistent geographic clustering. The substantial spatial spillover effect suggests that regional coordination of surgical capacity building may be more effective than country-by-country investments. Priority should be given to hotspot countries in sub-Saharan Africa and South Asia, with emphasis on surgical workforce expansion rather than broad economic development alone.

During the 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo and Uganda, we projected potential airline-mediated importation risk using contemporary airline network and an externally calibrated Ebola importation hazard. Effective-distance analyses identified major international hub countries, including Belgium, France, South Africa, Kenya, and the United Arab Emirates, as higher-probability gateways within 30 days. These early projections provide a reproducible framework for real-time international situational awareness, while emphasizing that importation risk does not imply local transmission risk.

Temperate regions of the world, such as southern Australia, often experience increased health burden from respiratory pathogens during winter. The ability to forecast short-term trends in cases of these pathogens is of significant interest to public health. Across the 2024 southern hemisphere winter period, the Australia--Aotearoa Consortium for Epidemic Forecasting and Analytics (ACEFA) ran a pilot respiratory virus forecasting initiative in collaboration with the Victorian Department of Health. Each week from the 9th of May 2024 through to 12th September 2024, the consortium solicited 28-day forecasts of daily case incidence for influenza, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and respiratory syncytial virus (RSV) from multiple research groups. Four component model forecasts were contributed by three different research groups, with a fourth group utilising the component forecasts to generate ensemble forecasts (making a total of six models, four component models and two ensembles). Here we statistically evaluated the performance of each forecast and a baseline model against the observed case data. The two ensemble models were found to be frequently the top performing models. All models performed worse than the baseline model around the epidemic peaks for each pathogen.