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PubMed2026

Integration of ear and hearing care services in low- and middle-income health systems: a systematic review and qualitative synthesis.

Hearing loss is a global public health burden and mostly affects those living in low- and middle-income countries (LMICs). One approach to address ongoing challenges is the World Health Organization's recommendation for the integration of ear and hearing care (EHC) services into healthcare packages. However, little is known about EHC integration approaches, particularly in LMICs additionally, these approaches have not been investigated through a health systems lens. This qualitative review aimed to describe the various approaches to the EHC service integration in LMICs and to identify enabling and constraining factors. We reviewed 17 studies, with a focus on LMICs, using adaptations of the Valentijn integration and World Health Organization EHC frameworks, following the PRISMA guidelines. Our investigation showed that most integration approaches were at micro or individual level. Enabling factors for integration of EHC services were training, mentorship, collaboration, technology, inclusion of EHC in healthcare packages and investment in EHC services. Barriers were challenges with training, facilities and equipment, policy implementation and resourcing of EHC services. We further described factors influencing healthcare seeking behaviour and the use of integrated EHC services, such as access and ability to pay, referral systems and communication and awareness. This study describes the complex nature of EHC integration and ways to support integration. Key considerations are the level of integration, training to address workforce issues and factors influencing service utilisation as we work towards health system strengthening.

Humans↗

PubMed2026

A tiled amplicon protocol for culture-free whole-genome sequencing of M. tuberculosis from clinical specimens.

Whole-genome sequencing of Mycobacterium tuberculosis can be a valuable tool for TB surveillance and treatment, providing insights into transmission patterns and comprehensive drug susceptibility testing. However, the slow growth of M. tuberculosis means traditional culture-based sequencing methods can take weeks to return results, which has limited the widespread adoption of these techniques and limited their use in clinical decision-making. Tiled amplicon sequencing is a fast, reliable, and cost-effective method of whole-genome sequencing that can be done directly on clinical specimens and has been implemented at scale in academic and public health laboratories across the world; it was the cornerstone of SARS-CoV-2 sequencing and has been adapted for a wide range of viral pathogens. However, similar methods are not yet available for far larger bacterial genomes. Extending this approach to M. tuberculosis would significantly reduce the cost, labor, and turnaround time for whole-genome sequencing. We designed a tiled amplicon panel consisting of 5,128 primers that covers the entire M. tuberculosis genome, the largest tiled amplicon sequencing panel we are aware of to date. Applying our amplicon panels to clinical samples of sputum, we show the ability to recover whole-genome bacterial sequences without the need for culture. The resulting sequence data can be used to determine M. tuberculosis lineage and reliably identify markers of drug resistance. Using this approach in clinical settings could reduce the time needed for comprehensive drug susceptibility testing from weeks to days and enable genomic epidemiology to be performed at scale, even in resource-limited settings.IMPORTANCEWe have developed and tested an amplicon panel, TB-seq, for the priority pathogen Mycobacterium tuberculosis, demonstrating recovery of near-full genomes directly from patient sputum, including mixed and low-concentration samples. This approach significantly reduces the turnaround time for this slow-growing bacterium while maintaining high accuracy in detecting clinically relevant mutations, including those associated with drug resistance. Given the global burden of tuberculosis and the critical need for faster diagnostic solutions, we believe our method has the potential to improve clinical decision-making and public health strategies.

Mycobacterium tuberculosis↗

PubMed2026

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans↗

PubMed2026

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination↗

PubMed2025

Multiplex PCR assay for the rapid detection of Klebsiella pneumoniae pathotypes.

Introduction. Klebsiella pneumoniae (Kp) is a major cause of nosocomial infections, with its evolving pathotypes including multidrug-resistant, hypervirulent (hvKp) and convergent strains posing significant diagnostic and treatment challenges due to combined antimicrobial resistance and virulence.Gap Statement. While there is a pressing requirement for thorough detection of Kp pathotypes, current assays in resource-limited environments are unable to effectively focus on essential carbapenemase and hypervirulence genes with the necessary reliability and precision.Aim. To develop and validate a multiplex PCR (m-PCR) assay capable of simultaneously detecting Kp isolates including those carrying partial or full virulence markers, alongside antimicrobial resistance.Methodology. In this study, an m-PCR assay was designed and optimized for the simultaneous detection of key biomarkers associated with hypervirulent (rmpA, rmpA2, iucA, peg344 and iroB), carbapenem-resistant (bla NDM, bla OXA-48-like and bla KPC) and convergent Kp pathotypes in clinical isolates. The assay was evaluated on clinical isolates and validated against whole-genome sequencing (WGS) data for accuracy, specificity and sensitivity.Results. The developed m-PCR assay exhibited 100% specificity when compared to WGS data, successfully detecting all target genes without cross-amplification in ATCC control strains. The assay demonstrated high sensitivity, efficiently amplifying bacterial genomes from minimal DNA input as low as 1 ng µl-1. Additionally, validation through sequencing confirmed the accuracy of detected amplicons.Conclusion. This m-PCR assay offers a rapid, sensitive and specific diagnostic tool for differentiating Kp pathotypes in clinical settings, aiding in timely intervention and improved infection control measures.

Klebsiella pneumoniae↗