Open Research Europe

Malaria remains a severe health problem in endemic regions because people lack adequate diagnostic tools, leading to delayed medical care and elevated death rates. This research introduces a dual-mode artificial intelligence system that uses two complementary models to enhance malaria pre-screening and diagnosis. The patient-centered model uses multivariate logistic regression to analyze biosignals, including heart rate, body temperature, and oxygen saturation, collected through a wearable sensor prototype and a mobile interface for symptom analysis. The system enables patients to begin self-assessment to determine their level of need before scheduling a doctor's appointment. The clinician-centered model represents a customized convolutional neural network that uses annotated microscopy images of red blood cells to achieve 94.84% accuracy, 95.71% precision, 93.87% recall, 94.78% F1 score, and 0.84 Area Under Curve (AUC). The patient model achieved 94.6% accuracy and an AUC of 0.985 using a 70/30 train-test split. These systems work together to create a layered diagnostic system that can operate independently or together to detect malaria at an early stage, especially in areas with limited resources. The findings demonstrate that wearable biosignal data integration with image-based deep learning can produce dependable, scalable, and user-friendly systems for malaria pre-screening. Keywords - malaria diagnosis, artificial intelligence (AI), convolutional neural networks (CNN), wearable biosensors, multivariate logistic regression

BACKGROUND: Artificial intelligence (AI) medical scribes rely on speech-to-text (STT) models for transcription. Evaluations of STT models in non-English settings remain scarce. We benchmarked ten STT models on medical consultations from Latin American (LatAm) Spanish and assessed whether fine-tuning improves transcription accuracy. METHODS: Ten YouTube videos depicting medical consultations. Human transcriptions were the ground truth. Five open-source models were evaluated: Whisper Large, Whisper Large v3, Whisper Large v3 Turbo, Voxtral Mini 3B, and Canary 1B v2; and so were five close-source models: gpt-4o-transcribe, gpt-4o-mini-transcribe, gemini-2.5-pro, Eleven Labs, and Assembly AI. Whisper Large v3 was fine-tuned. One video was withheld from training. Performance assessed using Word Error Rate (WER), Character Error Rate (CER), BLEU Score, ROUGE-L, BERT Score, and Semantic Similarity on the one withheld video. RESULTS: None of the fine-tuning iterations outperformed the vanilla Whisper Large v3. With the withheld video, Gemini-2.5-pro was the close-source model with the best performance in four of six metrics. In comparison to the close-source models, the fine-tuned model never outperformed the other models (withheld video); conversely, in comparison to the close-source models, the fine-tuned model showed better performance across metrics, for instance: BLEU score (63% vs to 58% for the second-ranking model), BERT (89% vs to 86%), and semantic similarity (89% vs to 83%), CER (19% vs 20%). CONCLUSIONS: Whisper Large v3 and its fine-tuned variant are the best open-source STT models for transcribing medical conversations in LatAm Spanish. These findings provide an evidence base for developing AI medical scribes tailored to Spanish-speaking LatAm.

Background: Globally, at least 2.6 billion people need rehabilitation services and more than 2.5 billion people need assistive technology (AT). However, reliable data are lacking on population level need for rehabilitation services and assistive products (AP) in different settings for evidence-based policy and programme planning. This first study paper describes the development of the Functional Needs Assessment Tool (FNAT), a new survey tool developed to fill this data gap between 2018 and 2023. Objective: To develop a new multidomain tool to assess population-level functional difficulties and need for service and AP utilising both self-report and clinical assessment methodologies. Development stages: FNAT was developed based upon primary and secondary data analysis, existing survey tools and expert consultation through a series of four steps: Step 1 Inform, Step 2 Build, Step 3 Draft and Step 4 Develop. FNAT uses both self-reported and clinical assessment tools to estimate the prevalence of functional difficulties/impairment and the need for services and AP in the following seven domains: vision, hearing, mobility, communication, cognition, self-care and mental health. It uses a two-stage population-based assessment with data collection through a bespoke tablet-based mobile application and web-based platform. Discussion: FNAT is a new multi-domain modular tool developed to address data gaps by estimating prevalence of functional difficulties and service/AP needs in a population. Potential advantages and disadvantages were highlighted during the development stages, and the tool needs to be pilot tested to assess the feasibility of the methodology and the functionality of the tablet-based mobile data collection application.

This qualitative study evaluated the Life Skills (HpV) training strategy at a public university in Colombia in 2024, analyzing its impact on students positive mental health and psychosocial competencies. The mixed-methods research employed semi-structured interviews with faculty and three student focus groups, using thematic analysis to categorize strengths, weaknesses, and perceived changes. Results highlighted curricular coherence, academic freedom, and participatory methodology as key aspects, fostering self-awareness, emotional management, and the building of support networks. Students reported improvements in well-being, stress management, and academic performance, though challenges such as initial resistance to emotional content and student diversity were identified. The conclusions underscore the value of experiential courses in university education, promoting horizontal relationships and safe spaces for collective reflection. Future studies are recommended to expand participant diversity and incorporate quantitative data triangulation to further explore the interventions effects.

Background: Zoonotic infectious disease risk arises at human-animal-environment interfaces where pathogen spillover can occur. Rural communities living in biodiverse settings may experience frequent contact with wildlife and shared environments through livelihoods, food practices, and economic activities. Reducing spillover risk and strengthening pandemic prevention requires both structural and individual-level change. Community-based interventions that promote awareness, risk perception, self-efficacy, pro-environmental behaviour, and safe coexistence with wildlife may support prevention by shifting behavioural determinants of zoonotic disease risk. The Saan Suk intervention was co-developed with rural communities in Thailand using a Human-Centred Design approach and is grounded in the Health Belief Model and One Health principles. The intervention is intended to be feasible, acceptable, and deliverable through Thailands established Village Health Volunteer (VHV) system. Methods: This protocol describes a parallel-arm, cluster-randomised controlled superiority trial that will be conducted during July - October 2026, in Chanthaburi Province, Thailand. 24 villages will be equally randomised to the Saan Suk intervention or the current practice (control). In intervention villages, trained VHVs will deliver, once a week over four weeks, a multimodal One Health educational intervention designed to improve knowledge of zoonotic spillover, promote protective behaviours, reduce risky wildlife-related contacts, and support respectful coexistence with wildlife. Trained outcome assessment teams will conduct structured interviews with 42 adult participants per village, yielding a total sample size of 1,008 participants. The sample size was calculated for the primary outcome, accounting for clustering, with 90% power to detect a medium effect size (6 points on the 0-100 knowledge scale) at a significance level of 0.05, accounting for a design effect with an ICC of 0.028. The primary outcome is knowledge of zoonotic spillover, transmission pathways, risk factors, protective and risky behaviours, and safe coexistence with wildlife. Secondary outcomes include attitudes, self-efficacy, preventive and risky behaviours, and reported contacts with major local reservoir hosts. A structured questionnaire was developed, expert-reviewed, and piloted for the outcome assessment. Outcomes will be analysed using mixed-effects regression models with random effects for village and adjustment for relevant pre-specified confounders. Primary analyses will follow the intention-to-treat principle. Discussion: This trial will evaluate whether a co-designed, VHV-delivered One Health educational programme can improve knowledge of zoonotic disease prevention and behavioural determinants in rural communities living in close contact with wildlife and shared ecosystems. If effective and feasible, Saan Suk could inform integration into routine VHV training and community-based zoonotic disease and pandemic prevention strategies. Trial Registration: The Saan Suk trial is registered with the German Clinical Trials Register (DRKS). Registration ID: DRKS00038582; date of registration: 11 May 2026.

Larval source management (LSM) is a complementary malaria control intervention, yet evidence to guide context-specific implementation remains limited. Nigeria's recent national commitment to LSM scale-up makes the need for operational evidence particularly urgent. Informal settlements embedded within wards of differing dominant settlement archetypes may present distinct Anopheles larval habitat profiles with implications for how LSM strategies should be tailored. We evaluated Anopheles larval habitats within informal settlement areas across wards with contrasting settlement archetypes in Ibadan metropolis, Nigeria, to inform targeted larval source management. Potential breeding habitats were surveyed in dry and wet seasons within informal settlement areas across three wards -- Olopomewa, Challenge, and Agugu -- representing formal, informal, and slum settlement-dominant archetypes respectively. Habitats were characterized and assessed for Anopheles larval presence. Pareto analysis identified habitats accounting for 80% of larval abundance. Breeding habitat density per km{superscript 2} was estimated using a simulated pathway technique. Associations between mosquito dispersal scale and household malaria infections identified through Rapid Diagnostic Testing were evaluated using kernel-based distance-decay weighting. Environmental drivers of habitat suitability were modeled in MaxEnt. Of 420 potential breeding habitats identified, 31 (7.4%) contained Anopheles larvae, predominantly during the wet season (26, 83.9%). Puddles, dug wells, drainages/gutters/ditches and canals accounted for 80% of site-level larval abundance when standardized by sampling effort. Larval and breeding habitat density were highest in Agugu, the slum-dominant ward, across both seasons. Modeled mosquito dispersal scale showed best fit at 30-32m in Challenge (OR 1.41, 95% CI: 1.05-1.89) during the wet season and 16-18m in Agugu (OR 1.29, 95% CI: 1.04-1.60) during the dry season. Habitat suitability in Agugu was higher farther from large water bodies and in areas with higher population density and positive Normalized Difference Water Index values. In Challenge, suitability was higher in areas with lower nighttime light levels, positive Normalized Difference Water Index values, and negative Normalized Difference Moisture Index values. Further studies incorporating multiple wards across diverse urban settings are needed to determine whether differences in larval ecology between settlement archetypes provide a reliable basis for planning larval source management.

ABSTRACT Background Breastfeeding practices vary across populations and are influenced by a range of social-cultural, and healthcare-related factors. Evidence on early initiation of breastfeeding (EIBF) and exclusive breastfeeding (EBF) among indigenous communities in India remains limited. This study aimed to identify factors associated with EIBF and EBF among Bhumij mothers in eastern India. Method A community-based cross-sectional study of 306 Bhumij mother-child pairs was conducted in Purulia, West Bengal, India (2023-2024). Socio-demographic and breastfeeding-related data were collected through structured interviews and analysed using bivariate and multivariable logistic regression. Results Almost all children (99.3%) had been breastfed; 72.9% initiated breastfeeding within one hour of birth, and 65.2% were exclusively breastfed during the first six months. In multivariable analyses, mode of delivery, pre-lacteal feeding, and colostrum discarding were significantly associated with EIBF. Maternal knowledge of EBF was positively associated with EBF practice (adjusted OR: 6.14; 95% CI: 2.80-13.46). Maternal perception of milk production was also associated with EBF, with higher odds observed among mothers reporting adequate (adjusted OR: 6.12; 95% CI: 3.00-12.48) or profuse (adjusted OR: 7.71; 95% CI: 2.56-23.25) milk production compared with those reporting insufficient milk production. Conclusion This study provides evidence on breastfeeding practices among Bhumij mothers and identifies healthcare-related, maternal, and caregiving factors associated with EIBF and EBF. The findings contribute to the limited literature on infant feeding practices among indigenous populations in India and may inform breastfeeding promotion and nation-wide maternal-child health programmes in similar settings.

Purpose This study aimed to examine the association between screen time and depressive symptoms among Chinese college students, and to investigate the mediating roles of sleep quality and emotion regulation in this relationship. Furthermore, a serial mediation model was constructed to elucidate the underlying psychological mechanisms linking screen exposure to depression. Methods A stratified cluster sampling method was employed to recruit 10,999 college students for a cross-sectional questionnaire survey. Data were collected on screen time, sleep quality, emotion regulation ability, and depressive symptoms. Descriptive statistics, correlation analyses, and regression analyses were conducted using SPSS 26.0 A serial mediation model was tested using the PROCESS macro (Model 6), and bootstrapping procedures were applied to estimate the significance of indirect effects. Results Correlation analyses indicated that screen time was significantly positively associated with depressive symptoms (r = 0.16, p < 0.01) and sleep quality (r = 0.15, p < 0.01), and significantly negatively associated with emotion regulation (r = -0.13, p < 0.01). Sleep quality was positively correlated with depressive symptoms (r = 0.31, p < 0.01), whereas emotion regulation was negatively correlated with depressive symptoms (r = -0.42, p < 0.01). Regression analyses further showed that screen time significantly positively predicted depressive symptoms ({beta} = 0.712, p < 0.001), positively predicted sleep quality ({beta} = 0.217, p < 0.001), and negatively predicted emotion regulation ({beta} = -0.085, p < 0.001). In addition, both sleep quality ({beta} = 1.318, p < 0.001) and emotion regulation ({beta} = -0.424, p < 0.001) were significant predictors of depressive symptoms. Mediation analyses demonstrated that sleep quality significantly mediated the association between screen time and depressive symptoms (95% CI [0.239, 0.332]), as did emotion regulation (95% CI [0.269, 0.416]). Moreover, a significant serial mediation effect of sleep quality and emotion regulation was observed in the relationship between screen time and depressive symptoms (95% CI [0.082, 0.117]). Conclusion Screen time is significantly associated with depressive symptoms among college students, with sleep quality and emotion regulation serving as important mediating mechanisms. Extended screen exposure may be linked to higher levels of depressive symptoms by impairing sleep quality and weakening emotion regulation capacity.

Introduction: District-level estimates of fertility are required by policymakers and programme planners in sub-Saharan Africa (SSA) to guide decision making at the local level. Existing approaches to produce fertility estimates at the district level use age-structures or total fertility trends over time from higher administrative levels which prevents representation of district-level heterogeneity in fertility estimates. Methods: We extracted observed numbers of births and person-years stratified by five-year age group, single calendar year, and district from 194 nationally-representative household surveys. We constructed a spatiotemporal Bayesian hierarchical model that reconciles point and areal data and adjusts for non-sampling biases to estimate age-specific (ASFR) and total fertility rates (TFR) in 36 countries between 2000-2025. Results: Fertility rates were calibrated to three million births from two million women over fifteen million person-years. TFR declined in the majority of countries 2000-2020 (median -15%, interquartile range (IQR) -3 to -24%). Substantial subnational heterogeneity in TFR levels was observed in most countries, exceeding that of differences between national fertility levels. ASFR heterogeneity was observed, though to a lesser degree than variation in total fertility. Teenage fertility was unchanged in several countries, with fertility declines driven by older age groups. Conclusion: District-level fertility dynamics can differ greatly from national TFR trends and age-patterns of fertility. Use of national fertility rates will produce inaccurate estimates of births in the majority of SSA districts, leading to inappropriate resource management for key global public health objectives.

ABSTRACT Background: Vaccination coverage in Brazil declined between 2015 and 2022, followed by a recovery in 2023 and 2024. Given this instability, driven by multiple determinants, we sought to identify factors associated with childhood vaccination and group Brazilian municipalities into scenarios that could guide interventions to improve coverage. Methods: In this ecological study of 5,274 Brazilian municipalities, we assessed the rate of children under 1 year unvaccinated with the third dose of the Inactivated Poliovirus Vaccine (IPV) in 2024, chosen for its high correlation with other tracer vaccines such as Diphtheria, Tetanus and Pertussis (DTP) and Measles, Mumps and Rubella (MMR). We applied a hierarchical model with three levels of determinants (socioeconomic, health service structure, and operational), using Poisson regression to estimate standardized Rate Ratios (RR), followed by a K-means cluster analysis to identify municipal profiles. Results: Several determinants were associated with higher rates of unvaccinated children, most notably the proportion of the population not covered by Community Health Workers (CHW) (RR = 1.15; 95% CI 1.14-1.15) and inequality measured by the Gini Index (RR = 1.33; 95% CI 1.32-1.34). We identified six municipal profiles that differed in tracer-vaccine coverage up to four years of age and in the composite Vaccination Needs Index (VNI). Conclusion: Multiple socioeconomic, structural and operational factors were associated with unvaccinated rates, highlighting the relevance of healthcare service organization even in favorable social contexts. Classifying municipalities into risk profiles may support more targeted interventions aligned with local needs. Keywords: Vaccination coverage, Childhood vaccination, Primary Health Care, Determinants, Scenarios, Profiles.

Histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) are central to malaria case management in Africa but fail when Plasmodium falciparum parasites lack the pfhrp2 or pfhrp3 genes. Widespread deletions have been reported in Eritrea, Ethiopia, and Djibouti, yet no systematic data have been available from Somalia. Between May and October 2023, we collected 7148 dried blood spot (DBS) samples from patients with suspected malaria attending eight health facilities across seven regions in Somalia. Field HRP2/pan-lactate dehydrogenase (LDH) RDTs and microscopy were performed, and DNA was extracted from 301 RDT-positive and 173 RDT-negative DBS samples. A multiplex quantitative PCR assay targeting pfldh, pfhrp2, and pfhrp3 was used to identify deletions in pfldh-positive samples lacking pfhrp2 or pfhrp3 amplification, with mixed infections inferred from delta cycle threshold ({Delta}Ct) differences. Of 474 analysed samples, 301 (4.2%, 95% CI 3.7-4.7) were RDT or microscopy positive, and 159 (33.5%) were confirmed pfldh-positive by qPCR. Among these, six (3.8%, 95% CI 1.4-8.1) carried pfhrp2 deletions and 59 (37.1%, 95% CI 29.6-45.1) carried pfhrp3 deletions. Eleven infections (6.9%, 95% CI 3.5-12.1) produced discordant RDT outcomes, HRP-/LDH+ or RDT-negative despite pfldh positivity. Deletions were most frequent in Dolow, Luq, and Bosaso. A single isolate carried the pfk13 R622I mutation, confirming the first report of the emergence of an artemisinin partial resistance-associated in Dolow, Gedo region, Somalia. Pfhrp2/3 deletions causing false RDT results remain low in Somalia and the confidence interval overlaps with the 5% policy threshold for changing RDTs, indicating uncertainty that warrants larger-scale assessment. Pfhrp3 deletions are widespread and compromise the diagnostic redundancy of HRP2-based tests. Most deletion-carrying parasites remain detectable through the pan-LDH line, minimising immediate clinical risk but leading to systematic misclassification of P. falciparum as non-falciparum malaria. These findings support the continued use of HRP2/Pan-LDH RDTs but highlight high risk areas and emphasise the need for periodic and expanded molecular surveillance for prevalence trends to guide timely future diagnostic policy.

Each year, over 50 million children receive preventive malaria treatment. However, to date there has been no consensus on the most effective antimalarial drugs to use, especially given geographic differences in drug resistance. Here, we conduct a systematic review comparing the effectiveness of the most commonly used antimalarial chemopreventive regimen, sulfadoxine-pyrimethamine plus amodiaquine (SP+AQ), with other antimalarial drugs in preventing new infections. We searched MEDLINE, Embase, Global Health, PubMed and WWARN clinical trial databases until 06 December 2025 for studies satisfying the inclusion criteria. Studies were included if they were peer-reviewed, randomised-controlled studies in Africa, measuring incidence of infection or clinical episodes of Plasmodium falciparum malaria for at least 28 days post-treatment. We also compiled data on the prevalence of markers of resistance in the parasite dhfr, dhps and mdr1 genes in the study areas. We conducted meta-analyses of incidence rates, with subgroup analyses by drug resistance levels. This review is registered on PROSPERO (CRD42024577149). We identified 27 studies representing 38,252 participants in 32 sites across 13 countries. In pooled analysis, SP+AQ reduced incidence of malaria by 54.6% (95% CI: 33.8-68.8%) compared to SP alone, including significantly outperforming SP even in areas with low SP resistance. These findings suggest that countries currently using SP alone for chemoprevention should consider switching to SP+AQ. Where AQ resistance remains low, available evidence suggests SP+AQ remains efficacious for malaria chemoprevention. SP+AQ was comparable to the artemisinin-based treatment, dihydroartemisinin-piperaquine across all studies (incidence rate ratio 0.93; 95% CI 0.78-1.11). By resistance levels, SP+AQ had slightly higher efficacy in areas with low SP and AQ resistance but had comparable or slightly lower efficacy in areas with higher resistance. Using artemisinin-based treatments for chemoprevention must be balanced against the risk of worsening artemisinin resistance in Eastern and Southern Africa. This study was funded by the UK Royal Society.

Controlled human infection models (CHIMs) are increasingly used in infectious disease research to study pathogen dynamics and evaluate interventions under controlled conditions. However, these studies are resource-intensive and involve ethical and safety constraints, making efficient study design critical. Dose-finding is a key early component in CHIMs, where the aim is to identify a challenge dose that achieves a target infection probability. Traditional rule-based designs are commonly used but can be inefficient, motivating the use of model-based adaptive approaches such as the Bayesian Continual Reassessment Method (CRM). Although CRM has been extensively studied and widely adopted in Phase I oncology trials for identifying the maximum tolerated dose of therapeutics, its application in CHIM settings remains limited, particularly when the endpoint of interest is infection. This tutorial provides step-by-step guidance for implementing a Bayesian CRM in dose-finding CHIMs, using an oropharyngeal Neisseria gonorrhoeae challenge as a motivating case study. The framework outlines key design components, including dose-grid specification, dose-response model, prior elicitation, Bayesian updating, decision rules, and stopping criteria, with particular emphasis on a clinically interpretable parameterisation. Trial operating characteristics are evaluated through simulation studies under multiple dose-response scenarios and prior-predictive analyses, and compared with a commonly used '3+3' type rule-based design. This work highlights the advantages of Bayesian model-based designs for dose-finding in CHIMs over classic rule-based designs and provides a structured, reproducible framework for implementing CRM, supporting their application in future CHIM studies.

Background Traumatic brain injury (TBI) affects 69 million individuals globally each year, yet care remains fragmented across complex, multi-specialty pathways and settings. Digital health technologies offer potential to bridge care gaps, particularly in resource-limited settings, yet existing frameworks do not adequately address the complexities of the TBI care pathway or the diverse global contexts in which care occurs. Methods A cross-sectional qualitative study using critical realist-informed thematic analysis was conducted with practising neurosurgeons recruited internationally via National Institute for Health and Care Global Health Research Group on Acquired Brain and Spine Injury (NIHR ABSI) collaborating centres, social media, and society newsletters. Semi-structured interviews were conducted by a single researcher (OM) via Microsoft Teams (March-July 2024), exploring technology availability, healthcare infrastructure, clinical pathways, and contextual challenges, with a systems thinking approach guiding identification of current and potential technology integration points. Fourteen neurosurgeons from twelve countries participated, representing six lower-middle, two upper-middle, and four high-income countries. Results Six inductive themes emerged: Availability, Acceptability, Applicability, Capability, Feasibility, and Possibility- forming a novel conceptual framework visualised as a hexagonal chart for guiding digital health technology design and implementation in TBI care. Marked disparities in technology availability and utilisation were identified across urban/rural settings and income levels. Conclusions This framework offers a practical, context-sensitive tool for researchers, policymakers, and clinicians developing or implementing digital health technologies in TBI care globally. Visualisation in a similar style to a radar-chart enables simultaneous consideration of factors- including digital literacy, infrastructure, and cultural attitudes- whose neglect frequently underlies implementation failures.

Background: Travellers visiting friends and relatives (VFRs) experience a disproportionate burden of travel-associated infectious diseases, yet little is known about the complexity of pre-travel consultations required to support their care. We compared enquiries relating to VFR travellers and tourists received by the UK National Travel Health Network and Centre (NaTHNaC) specialist Advice Line to identify differences in traveller characteristics, destinations and clinical complexity. Methods: We conducted a retrospective observational study of enquiries to the NaTHNaC Advice Line between 1 January 2019 and 31 December 2025. Enquiries relating to VFR travellers and tourists were compared using descriptive statistics and appropriate statistical tests. Traveller demographics, travel characteristics, destinations and enquiry management were analysed. Results: Of 16,367 enquiries relating to specific travellers, 3,090 (18.9%) concerned VFR travellers and 7,237 (44.2%) concerned tourists. Compared with tourists, VFR travellers were younger (median age 24 vs 52 years, P<0.001), more likely to undertake long-stay (8.4% vs 1.8%, P<0.001) and last-minute travel (5.0% vs 1.1%, P<0.001), and more frequently travelled to the WHO African Region (56.6% vs 29.2%, P<0.001) and Eastern Mediterranean Region (12.7% vs 2.8%, P<0.001). Pregnancy was substantially more common among VFR travellers (11.6% vs 4.3%, P<0.001). Enquiries concerning VFR travellers were more likely to require a call-back (16.1% vs 13.8%, P=0.012) and escalation to a specialist doctor (13.1% vs 10.5%, P<0.001), indicating greater consultation complexity. General practice generated a higher proportion of VFR-related enquiries than tourist enquiries (69.5% vs 63.9%, P<0.001). Conclusions: VFR travellers generate disproportionately complex pre-travel consultations characterised by higher rates of specialist escalation, distinct travel patterns and travel to destinations associated with the greatest burden of imported infectious diseases. These findings highlight the importance of specialist travel medicine support for healthcare professionals managing VFR travellers and reinforce the need for equitable access to timely, high-quality pre-travel healthcare for this high-risk population.

The World Health Organization (WHO) validated Sri Lanka had eliminated lymphatic filariasis as a public health problem in 2016, the second country in Southeast Asia to attain this status. However, post-validation surveillance has identified sporadic cases of brugian filariasis. The reemergence of Brugia malayi infections in Sri Lanka warrants urgent investigations. Recent studies have shown that the parasite responsible for the reemergence is a novel zoonotic Brugia sp. maintained among dogs that is closely related but distinct to the human-infecting B. malayi species. The current study employed morphological and morphometric assessments, revealing that this novel zoonotic Brugia sp. is within the B. malayi morphological range. Molecular characterization of three genomic regions, the nuclear genomic region SLXI, the non-coding region HhaI, and the mitochondrial genomic region COXI confirmed it as a genetic variant more closely related to B. malayi than to B. pahangi. Phylogenetic analysis further indicated it as a distinct genomic variant, closely related to a B. malayi-like parasite reported from India. Notably, that same parasite was identified in infected humans, animals, and potential vector mosquitoes. This, together with the detection of both human and animal blood within the same brugian infective mosquitoes, and delineating the canine origin of the parasites in human infections, provides compelling evidence supporting zoonotic transmission of this parasite. To our knowledge, this is the first report demonstrating the presence of the same brugian parasite in humans, domestic animals, and potentially infective mosquitoes in Sri Lanka, supported by multi-genomic evidence. The recent identification of multiple potential mosquito vector species suggests that this parasite may have undergone adaptive changes, facilitating its ability to overcome the species barrier. These findings substantiate the long-held hypothesis of zoonotic transmission of the reemerged brugian parasite, highlighting significant implications for ongoing surveillance and control strategies.

Background: Guidelines on pre-pregnancy counselling are primarily clinical, and although recommendations and policy documents on preconception care exist in Australia, they place little or no emphasis on the preconception health of adolescents and young adults. Objective: To identify and prioritise unanswered questions and evidence uncertainties concerning preconception health needs of adolescents and young adults residing in Australia. Design: Research priority exercise Setting and Participants: Participants included young interest-holders (18-24 years) and professional interest-holders from the academics, healthcare, policy, community and government sectors residing in Australia. Methods: We followed the James Lind Alliance (JLA) methodology to identify research priorities for preconception health of adolescents and young adults. The process was led by a multidisciplinary steering committee comprising young interest-holders and professional interest-holders (including academics and clinicians). A rapid literature review was conducted from which 80 research questions were developed across ten domains, which were refined through consultation and prioritised via two rounds of online surveys on Qualtrics using a 9-point Likert scale. Results: The participants included 14 young interest-holders in each survey round, with 22 professional interest-holders in the first round and 33 in the second. Participants from across Australia participated in the survey, but most were from South Australia. In the first survey round, 28 questions across seven domains were prioritised by both professional and young interest-holders. This was followed by a reprioritisation exercise, resulting in the final top 10 research questions spanning five domains. The highest-priority research questions identified by the interest-holders concentrated in the domains of violence and mental health; early intervention and prevention; smoking, tobacco, alcohol, and substance use; access to preconception care and the healthcare system; and priority populations. Conclusion: The study identified the top 10 priority research questions informed by professional and young interest-holders. It promotes new research and collaboration while offering guidance on future research investments and on designing preconception interventions for adolescents and young adults in Australia. Turning these priorities into research could improve the health outcomes for adolescents and their future generations.

Objectives: To compare the effectiveness of povidone-iodine ear wash compared to no ear wash and oral cotrimoxazole compared to placebo given in addition to standard topical antibiotic treatment (ciprofloxacin drops) for chronic suppurative otitis media (CSOM) in Australian Aboriginal children. Methods: A randomised, parallel, 2 x 2 factorial design, assessor-blinded clinical trial in the remote Northern Territory of Australia. Aboriginal children with confirmed CSOM were eligible to be randomised into four treatment groups, allowing two primary treatment comparisons in a 2-in-1 trial approach. Participants received standard treatment (twice daily cleaning and topical ciprofloxacin drops) plus: i) either 16 weeks of pre-treatment povidone-iodine ear wash or no povidone-iodine ear wash; and ii) either 16 weeks of oral cotrimoxazole or placebo. Central randomisation with allocation concealment and triple-blinding of the oral antibiotic treatment arms was used. The relative risk (RR) and risk difference (RD) were estimated after adjustment for age, community, and the other intervention. The primary outcome was the proportion of children with any otorrhoea (clinical failure) after 16 weeks of treatment. Secondary outcomes included size of tympanic membrane (TM) perforation and amount of discharge, time to cessation of discharge, proportion of children with respiratory and other pathogens in ear discharge (at baseline and 16 weeks) and hearing levels (at 12 months). Findings: 280 children with CSOM were randomised and 270 had their primary outcome assessed. Clinical failure (presence of any ear discharge) after 16 weeks of treatment was 66/134 (49%) in the povidone-iodine group versus 69/136 (51%) in the no povidone-iodine group (RD= -1% (-12,11), p= 0.93) and 56/134 (42%) in the cotrimoxazole group versus 79/136 (58%) in the placebo group (RD=-16% (-28,-4), p=0.007). The amount of discharge, TM perforation size, the level of hearing impairment, and serious adverse events were not significantly different in both treatment comparisons. Anaerobic growth (24%), Pseudomonas aeruginosa (21%) and Haemophilus influenzae (17%) were the most common pathogens found in the ear discharge before treatment. Fungi or yeast (24%), Staphylococcus aureus (15%), and anaerobic growth (10%) were the common pathogens after 16 weeks of treatment, with no significant differences between groups. At 12 months post-randomisation, 55-60% of children had at least one discharging ear and there was no difference between treatment groups. Interpretation: Povidone-iodine ear washes did not contribute to better ear outcomes in this study. Cotrimoxazole for 16 weeks resulted in more children with clinical improvement to dry ears. Oral cotrimoxazole may play a role in reducing the burden of CSOM in populations with high rates of persistent disease.

Antimicrobial resistance (AMR) is an ever-increasing threat to population health. Industrial, environmental and societal factors are increasingly recognized as important contributors to AMR within communities. Here, we investigated the spatial distribution of AMR genes (ARGs) across Alberta, Canada and their association with socio-economic, immigration-related, and agro-industrial characteristics using municipal wastewater-based surveillance. We analyzed monthly wastewater metagenomes collected between March 2022 and March 2023 across eleven municipalities, representing 39% of Alberta's population. Integration with census data enabled multivariate analysis, revealing that municipal resistome profiles were strongly structured along income and immigration-related population gradients. ARGs spanning 14 resistance classes exhibited distinct distributional patterns across income and immigration gradients, including contrasting associations among beta-lactam, aminoglycoside, and macrolide-lincosamide-streptogramin ARGs, consistent with heterogeneous selection pressures across sub-populations. These findings demonstrate the capacity of longitudinal wastewater surveillance to identify persistent population-level resistome patterns and highlight the importance of incorporating sociodemographic context into AMR surveillance and mitigation strategies.

Aims: The COVID-19 pandemic has significantly impacted global mental health. At the onset of the pandemic (2020), Belgians experienced increased anxiety, depression, and psychological distress compared to 2018 due to the outbreak and the associated public health measures. Understanding the drivers of this distress is crucial for mitigating mental health effects in future crises. This study examines determinants of psychological distress in Belgium during the March 2020 lockdown, using data from the Great Corona Study (GCS). Methods: Data were drawn from the second wave of the GCS, a citizen science initiative conducted in Belgium on March 24, 2020, with 332,169 respondents. Psychological distress was measured using the General Health Questionnaire-12 (GHQ-12), applying a 2/3 cutoff to classify distress levels. To identify predictor variables, a random forest algorithm and literature review reduced 207 initial variables to 16. A generalized linear model was then used to examine associations between predictors and psychological distress Results: Psychological distress was significantly associated with various demographic, social, occupational, and health-related factors. Younger individuals, women, and residents of Wallonia or Brussels exhibited higher odds of distress. Household composition, and the frequency of real-life social interactions significantly influenced distress levels. Occupational status played a key role, with part-time employees and working students exhibiting higher levels of distress. At the same time retired individuals with no current occupation showed lower odds. Perceived workplace safety and compliance with public health measures also significantly impacted distress levels. Lastly, individuals experiencing influenza-like or COVID-19 symptoms had substantially higher odds of psychological distress. Conclusions: Our findings highlight significant sociodemographic, occupational, and health-related predictors of psychological distress during the initial COVID-19 lockdown in Belgium. Young adults, women, individuals with limited in-person interactions, and those experiencing influenza-like illness or COVID-19 symptoms were particularly vulnerable. Additionally, perceptions of others' adherence to preventive measures played a crucial role in mental well-being. These results highlight the complex interplay between individual and environmental factors in shaping psychological distress, providing valuable insights for future public health policies and mental health interventions during crises.