American Journal of Infection Control

Background: Digital antimicrobial stewardship (AMS) interventions, such as clinical decision support systems, audit and feedback platforms, and electronic prescribing tools, have been increasingly adopted to improve antibiotic use. However, the effectiveness of these interventions across healthcare settings remains uncertain, and the certainty of the evidence has not been comprehensively evaluated. The objective of this study was to provide a comprehensive understanding of the role of digital interventions in optimizing antimicrobial use and improving clinical outcomes within a broad spectrum of healthcare settings. Methods: We conducted a systematic review and meta-analysis of randomized controlled trials evaluating digital AMS interventions that followed PRISMA 2020 guidelines and registered in PROSPERO CRD420251178854 and funded by the Wellcome Trust CAMO Net programme. Searches were performed across major databases. Primary outcomes included the appropriateness of antibiotic prescriptions and the antibiotic prescription rate. Secondary outcomes included 30 day mortality, 30 day hospital readmission, and length of hospital stay (LOS). Random effects models were used to pool effect sizes. Risk of bias was assessed RoB 2, and certainty of evidence was rated using GRADE. A Summary of Findings table was prepared to present effect estimates, sample sizes, and evidence certainty. Results: Eleven RCTs met the inclusion criteria, and nine were included in the quantitative synthesis. Digital AMS interventions did not show a significant effect on appropriateness of antibiotic prescribing (RR 0.99, 95%CI 0.93 to 1.05; very low certainty). There was no reduction in antibiotic prescription (RR 0.98, 95%CI 0.88 to 1.09), with substantial statistical heterogeneity and very low certainty. Across clinical outcomes, digital AMS showed no effect on 30 day mortality (RR 0.91, 95%CI 0.77 to 1.09; very low certainty) or 30 day readmission (RR 0.95, 95%CI 0.79 to 1.14; very low certainty). For LOS, results were inconsistent across studies, and the pooled effect showed no clinically meaningful change (MD 0.17 days, 95%CI 0.01 to 0.35; very low certainty). Most trials had some concerns of bias due to deviations from intended interventions. Conclusion: Meta-analyses of digital AMS RCTs showed a lack of evidence with a high level of certainty on antibiotic prescribing or clinical outcomes due to high heterogeneity in interventions and study designs, as well as RCTs' limitations (no adoption/fidelity metrics).

PURPOSE: As the armamentarium of BPH therapies continues to expand, it remains imperative to maximize patient satisfaction and minimize decisional regret. We sought to determine the impact of time from BPH diagnosis to index treatment on symptom improvement and subsequent procedural events. MATERIALS AND METHODS: We queried the American Urological Association Quality Registry for men [&ge;] 40 years old with BPH, available IPSS data, and no receipt of prior BPH treatment. Index treatment included medication, surgery, or minimally invasive surgical therapy (MIST). Outcomes included IPSS over 3 years of follow-up, change in percentage of mild lower urinary tract symptoms (LUTS) by 3 months, and time to procedural event. Patients were stratified by time from index diagnosis to treatment by <12 months, 1-3 years, and >3 years. Outcomes were compared across time-to-treatment cohorts with appropriate statistical tests with p < 0.05 as significant. RESULTS: 43,919 patients met criteria with 19,642 pursuing treatments. Patients pursued treatment at comparably lower baseline IPSS compared to prior prospective series. Patients undergoing surgery and MIST had significantly higher baseline IPSS, while medical comorbidities were significantly more common among men initiating pharmacotherapy. Early surgery and MIST were associated with significant improvement in IPSS within 6-12 months and an increase in mild LUTS by 3 months. All forms of early treatment were associated with delayed time to procedural events, including catheterization and fulguration. CONCLUSIONS: Early procedural intervention for BPH is associated with early symptom improvement and delayed time to procedural events among real-world, contemporary practice.

This study aimed to clarify aerosol exposure risks throughout the workflow of a Biosafety Level 2 (BSL-2) polymerase chain reaction (PCR) laboratory, validate the suitability of the {Phi}X174 bacteriophage as an indicator virus, and provide evidence for biosafety control measures. The {Phi}X174 bacteriophage was used to simulate viral samples, and a concentration-bacteriophage plaque standard curve was constructed (R2=0.998). Five operational steps in a simulated PCR laboratory were quantitatively monitored for aerosol concentration using double-layer agar plates, with blank controls used to eliminate interference. Statistical analysis was employed to identify risk differences. Sample homogenization ((5.67 {+/-} 1.23) x 104 plaque-forming units (PFU)/m3) and nucleic acid extraction ((3.45 {+/-} 0.89) x 104 PFU/m3) were identified as high-/very high-risk steps. The viral load in the samples was strongly positively correlated with the aerosol concentration (r = 0.926, P <0.001), with aerosol levels linearly decreasing with increasing distance in high-risk steps. The {Phi}X174 bacteriophage demonstrated high detection sensitivity (101 PFU/ml) and demonstrated safety compatibility with BSL-2 laboratories. Aerosol risks in PCR laboratories exhibit step-specific differentiation, and {Phi}X174 serves as an ideal indicator virus. Proposed strategies such as equipment upgrades and personal protective equipment (PPE) grading can reduce exposure risks.

ObjectiveRecurrent urinary tract infections (rUTIs) significantly decrease quality of life and antibiotics are becoming increasingly less effective due to antimicrobial resistance. Alternative effective treatment strategies are urgently needed for rUTIs. Prior studies have indicated that women can experience resolved or improved rUTI following electrofulguration (EF). To further investigate these findings, we report on the design and methodology behind a randomized trial examining two treatment arms: standard prolonged antibiotic treatment with nitrofurantoin (NF) alone or in combination with EF. Patients and MethodsThe aim of this randomized trial is to determine, at two institutions, the efficacy of two interventions for rUTI associated with early stages of chronic cystitis (stages 1 and 2): conventional 6 months low-dose (100mg) NF daily antibiotic suppression alone (NF) or conventional NF with EF (EF + NF). The study is also designed to analyze changes in the urinary microbiomes in the two different treatment arms and to determine the durability of clinical outcomes in both treatment arms at 2 years after the end of each intervention. The primary outcomes will be obtained from 6 to 18 months, as well as 18 - 30 months following completion of the original 6-month intervention. Failure is defined based on UTI symptoms documented by a validated questionnaire with a documented urine culture confirming a bacterial strain at each UTI episode following the end of the 6-month intervention. ConclusionsThis randomized trial is designed to examine the efficacy and durability of treating women with rUTIs using the standard of care of NF alone, or an EF procedure with NF.

Background The COVID-19 pandemic has caused significant global mortality. Despite declining infection rates, new variants of SARS-CoV-2 continue to emerge, necessitating new prevention strategies. Objective This study aimed to evaluate the effect of four over-the-counter (OTC) antiseptic mouthwash/gargling solutions in the U.S., compared with a distilled water control, on SARS-CoV-2 viral load across multiple oral and oropharyngeal sample types. Methods This pilot single-center randomized controlled clinical trial enrolled adults in the San Francisco Bay Area, California, who tested positive for COVID-19. Participants were randomized to distilled water, chlorine dioxide, hydrogen peroxide, cetylpyridinium chloride, and essential oils. Participants were instructed to rinse and gargle four times daily for four weeks using standardized instructions to ensure protocol adherence. Samples were collected on Days 1, 7, and 28 and analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The primary outcome was the change in SARS-CoV-2 viral load from baseline to Day 28, assessed using cycle threshold (Ct) values. Secondary outcomes included self-reported clinical symptoms and hospitalization. Results Forty-nine participants completed the study. No mouthwash demonstrated a statistically significant reduction in SARS-CoV-2 viral load over time. Cetylpyridinium chloride showed a transient increase in Ct values on Day 7 that was not sustained on Day 28. At baseline, throat swab samples had the lowest Ct values across all sample types. Due to limited subgroup sample sizes for secondary outcome measures, no statistical or moderator analyses were conducted. Conclusion Further large-scale randomized trials are needed before recommending antiseptic mouthwashes for SARS-CoV-2 prevention or management.

Background: Rising antibiotic resistance challenges empirical therapies for urinary tract infections (UTIs). This study evaluated the microbial etiology, susceptibility profiles, and multidrug resistance (MDR) patterns of uropathogens among outpatients at the Berekum Holy Family Hospital, Ghana. Methods: This cross-sectional study (February to August 2021) screened 263 symptomatic outpatients. Mid-stream urine samples underwent quantitative culture, biochemical identification, and antimicrobial susceptibility testing via the Kirby-Bauer disc diffusion method following the 2021 CLSI guidelines. Results: Significant bacteriuria prevalence was 22.8% (60/263). UTIs predominated in females (78.3%, 47/60; p = 0.1501) and individuals [&ge;]45 years (33.3%, 20/60). Gram-negative rods accounted for 90.0% of isolates, primarily Escherichia coli (26.7%), Citrobacter spp. (25.0%), and Enterobacter spp. (21.7%); Staphylococcus aureus (10.0%) was the only Gram-positive pathogen. Extreme phenotypic resistance was observed against piperacillin/tazobactam (98.3%), cefotaxime (93.3%), tetracycline (88.3%), and cefoperazone (85.0%). Conversely, highest therapeutic susceptibilities were retained by amikacin (78.3%), levofloxacin (61.7%), and gentamicin (58.3%). Conclusion: The high prevalence of MDR uropathogens against advanced beta-lactamase inhibitor combinations and cephalosporins necessitates an immediate re-evaluation of regional empirical protocols. Amikacin, levofloxacin, and gentamicin remain viable options prior to culture confirmation. These findings establish a crucial phenotypic baseline to guide localized prescribing policies and regional antimicrobial resistance tracking strategies.

Manufacturers are adopting propellants for use in pressurized metered-dose inhalers (pMDIs) that have lower global warming potentials (GWPs) than the propellants traditionally used in pMDIs. Hydrofluoroalkane (HFA)-134a has been used as the propellant in the pMDI used to deliver the fixed-dose triple combination of budesonide, glycopyrrolate and formoterol fumarate (BGF); following successful clinical evaluation, the BGF pMDI is now being transitioned to the next generation propellant hydrofluoroolefin (HFO)-1234ze(E), which has near-zero GWP. We describe formulation development efforts that led to selection of HFO-1234ze(E) over another propellant, HFA-152a, for reformulation. Propellant-specific studies evaluated active pharmaceutical ingredient (API) stability and aerodynamic particle size distribution (aPSD). Those analyses have been complemented by in silico regional lung deposition modeling conducted after the clinical evaluation of the reformulated BGF pMDI. HFO-1234ze(E) supported favorable stability and aPSD characteristics for BGF pMDI reformulation, compared with HFA-152a, and modeling predicted regional deposition consistent with therapeutic intent. Given that each pMDI is a unique combination of APIs, device, propellant, and excipients, propellant substitution requires product-specific evidence and regulatory approval, and typically takes several years. Targeted analyses, such as those described here, helped to identify the most suitable candidate propellant for successful substitution in the BGF pMDI. HighlightsO_LIFormulation development efforts that led to evaluation of a budesonide-glycopyrrolate-formoterol fumarate pressurized metered-dose inhaler (BGF pMDI) reformulated with the next generation propellant HFO-1234ze(E) in a clinical trial program are described; the suitability of another propellant, HFA-152a, was also assessed C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% relative humidity [RH]), the HFA-152a formulation approached and, in one replicate, fell below the 90% of formulation label claim threshold of evaluation, whereas the original HFA-134a product and the HFO-1234ze(E) formulation remained above that threshold C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% RH) and 18 months under long-term stability storage conditions (25{degrees}C/60% RH), the fine particle mass and fine particle fraction for all active pharmaceutical ingredients (APIs) showed that the HFO-1234ze(E) formulation tracked more closely than the HFA-152a formulation to the original HFA-134a product C_LIO_LILater in silico modeling, conducted after clinical testing, predicted a trend for greater deposition of APIs in early airway generations with HFA-152a, whereas HFO-1234ze(E) was predicted to more closely match HFA-134a, indicating a greater likelihood of achieving equivalence to the original HFA-134a product with HFO-1234ze(E) than with HFA-152a C_LIO_LIBased on these analyses and other formulation development efforts, HFO-1234ze(E) was identified as the most suitable propellant for reformulation of the BGF pMDI; for HFA-152a, analyses raised concerns about storage stability, and differences in aerosol characteristics that can impact API deposition in the lungs and, in turn, efficacy C_LI

Background Occupational exoskeletons are used to reduce physical workload and prevent work-related musculoskeletal disorders in physically demanding jobs. Although laboratory studies demonstrate reduced muscle load during simulated manual work tasks, evidence from long-term, real-world implementations remains very limited. The RELAX project aims to investigate the long-term effects of a passive back-support exoskeleton (BSE) during manual order-picking work in a Danish warehouse, focusing on health and socio-economic outcomes. Methods This 18-month controlled in-field intervention study compares outcomes at two warehouse departments: one where workers use a passive BSE and a control group where workers perform work tasks as usual. Approximately 90 full-time workers will be followed during the intervention period with questionnaires, interviews and company-registered performance indicators. Primary outcomes include perceived work intensity and musculoskeletal discomfort, while secondary outcomes include sickness absence, employee turnover, productivity and cost effectiveness. Furthermore, a process evaluation will be conducted based on questionnaires, focus-group interviews, and reported exoskeleton use. Quantitative effects will be analysed using difference-in-difference analysis with generalized linear mixed models to account for repeated measures over time. Employee turnover will be analysed using time-to-event analysis, and qualitative focus-group interviews will be analysed using reflexive thematic analysis to explore implementation processes and contextual factors. Cost-effectiveness and return on investment will be assessed by comparing the investment with potential savings in costs and resource use. Discussion By combining longitudinal quantitative outcomes with qualitative process evaluation, the study seeks to provide ecologically valid evidence on the effectiveness, feasibility and sustainability of occupational exoskeleton implementation. This approach will help clarify whether long-term exoskeleton use improves worker health without compromising productivity and may inform future workplace guidelines and large-scale adoption strategies.

Touchscreens have become the dominant interface in consumer electronics, yet interactions with them remain primarily visual. Incorporating haptic feedback that simulates touch sensations could make these interactions more natural and intuitive. Electrostatic actuation, which modulates friction by attracting the finger toward a capacitive surface using an alternating voltage, offers a promising approach. The resulting increase in friction is often attributed to the rise in real contact area; however, direct experimental evidence linking voltage input parameters to real contact area and contact forces remains limited. Here, we use frustrated total internal reflection to directly image the real contact area while simultaneously measuring contact forces during controlled finger sliding under electrostatic actuation. We systematically vary voltage amplitude (75-150 V) and excitation frequency (30-230 Hz) and quantify the changes in contact area and forces as functions of these parameters. Our results reveal a quadratic dependence of real contact area, electro-static attraction, and tangential force on voltage amplitude, with comparatively small effects of excitation frequency. These findings clarify the respective roles of voltage amplitude and frequency in the electrostatic modulation of finger contact mechanics, providing design guidelines for haptic display design.

Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.

Background Outpatient groin hernia repair is widely recommended globally due to clinical and socioeconomic efficiency, yet it remains underutilized in developing healthcare systems like Tunisia. This study aimed to evaluate the feasibility of a newly implemented day-surgery clinical pathway for groin hernias and identify specific predictors associated with outpatient discharge failure. Methods A prospective, observational cohort study was conducted at a Tunisian tertiary hospital between September 2023 and April 2024. A total of 85 consecutive patients scheduled for elective groin hernia repair under an optimized clinical pathway were enrolled. Inclusion criteria spanned ASA classes I-III, age [&ge;]16 years, proximity to the hospital [&le;]50 km), and presence of a literate adult caregiver. Outpatient failure (unanticipated admission) was defined as the inability to achieve discharge within 24 hours post-surgery. Statistical associations were determined using Chi-squared, Fisher's exact, and independent t-tests. Results The cohort primarily comprised males (n = 82, 96.5%) with a mean age of 56 years (range: 19-86). Successful ambulatory discharge was achieved in 80 patients (94.1%), yielding a failure rate of 5.9% (n = 5). Unanticipated admissions were triggered by uncontrolled pain (n = 1), acute anxiety (n = 2), decompensation of comorbidities (n = 1), and a Post-Anesthetic Discharge Scoring System (PADSS) score < 10 (n = 1). Overall 30-day morbidity was low (2.4%), presenting as minor wound or scrotal hematomas managed conservatively; no surgical site infections, acute urinary retention, or mortality occurred. Univariate analysis revealed that a hernial sac size measured at its maximum diameter between 1.5 and 3 cm was significantly associated with ambulatory failure (p = 0.047). General anesthesia showed a trend toward increased failure compared to regional anesthesia (p = 0.08). Conclusion Day-surgery groin hernia repair is highly safe and feasible in resource-constrained environments, even for elderly or stable ASA III patients, provided rigorous social criteria are satisfied. A small hernial sac size (1.5-3 cm) constitutes a major anatomical predictor of failure, likely due to distinct dissection dynamics and localized post-operative pain profiles.

Patients with primary immunodeficiency (PID) often face prolonged diagnostic delays and may increasingly turn to large language models (LLMs) to interpret their symptoms during this period. We evaluated whether an LLM could recognize PID from symptom descriptions derived from interviews with 21 PID patients. In a prior study, we showed that GPT-4o identified PID in 96% of cases when prompted with physician-written patient histories (Rider et al., JACI, 2024). Here, when prompted with symptom descriptions in patients' own words, GPT-5 identified PID in only 7 cases (33%), although it more broadly suggested immune system issues in 18 cases (81%). The gap between these findings indicates that LLMs are sensitive to the language and framing of symptom descriptions, performing substantially worse when patients describe their own symptoms in everyday language than when clinicians summarize patient histories in structured medical terms. This study underscores the need to carefully evaluate how LLMs are used in patient-facing applications.

Background: Multi-drug resistant Bacterial (MDRB) Infections in the intensive care units (ICUs) substantially elevate patient mortality, prolong hospital stays, and impose heavy healthcare cost burdens. Existing predictive models for ICU-acquired MDRB infection predominantly focus on static admission-risk assessment, lacking the capacity to leverage longitudinal treatment data for dynamic risk re-stratification during the ICU stay. Meanwhile, most models suffer from poor clinical interpretability, overreliance on hard-to-collect biomarkers, or absence of deployable clinical tools, limiting real-world translation. Therefore, there is an urgent need to develop a parsimonious, interpretable tool based on routine cumulative data to guide timely intervention. This study aimed to develop a interpretable model with a web calculator to improve clinical applicability. Methods: In this study, we conducted a retrospective analysis of ICU inpatients at the First Affiliated Hospital of Dali University between January 1, 2023, and January 1, 2026. Using the create Data Partition function in R software (random seed = 42), the dataset was stratified and divided into a training group and a validation group in a 7:3 ratio. Feature selection was performed using the Boruta algorithm to validate variable rationality. A multivariable logistic regression model was constructed and visualized as a nomogram, and its performance was compared with six machine learning algorithms (Random Forest, XG Boost, Neural Network, etc.). Model validation was conducted using receiver operating characteristic curves (ROC), Decision Curve Analysis (DCA), and SHAP value interpretation. Finally, an online R Shiny calculator was developed based on the final model. Results: A total of 3,631 patients were enrolled and divided into a training group (n=2,543) and a validation group (n=1,088) using stratified random sampling. Five independent predictors were identified in the training group, which were hypertension combined with diabetes, antibiotic types, ventilator days, urinary catheter days, and PCT abnormality times. The Logistic regression model achieved an AUC of 0.772 (95%CI: 0.733-0.812) in the validation group, outperforming XG Boost (0.763) and Random Forest (0.703). The model demonstrated excellent calibration (Hosmer-Leme show {chi}{superscript 2} = 1.94, P = 0.9829) and positive net clinical benefit across threshold probabilities of 0%-40%. SHAP analysis aligned with regression-derived variable importance rankings, confirming predictor contributions. An open-access online calculator was successfully deployed (https://dongfangshao666.shinyapps.io/MDR_shiny2/), enabling real-time individualized risk stratification at the bedside. Conclusion: This study developed and validated a dynamic, interpretable multi-drug-resistant bacterial infection risk prediction model requiring only five routinely collected clinical indicators. The model balances robust predictive performance with high transparency, overcoming key limitations of prior tools. The accompanying web calculator supports dynamic risk reassessment throughout the ICU stay, facilitating precise antimicrobial stewardship, targeted infection control interventions, and optimized resource allocation, bridging the gap between statistical modeling and frontline clinical decision-making.

Objectives In Quebec, Canada, vaccination against human papillomavirus (HPV) has been publicly-funded since January 2016 for gay, bisexual, and other men who have sex with men (GBM) aged [&le;]26 years. The study aimed to analyze data collected in Greater Montreal (Engage study) to evaluate the HPV vaccination program for GBM in Quebec. Study Design Engage is a cohort of sexually active GBM aged [&ge;]16 recruited via respondent-driven-sampling (RDS) in Canada. Participants completed a questionnaire and tested for sexually transmitted infections. Methods RDS-II weights were applied to adjust for recruitment. Subgroups were compared using standardized mean differences. Odds ratios of HPV vaccination and prevalence ratios of anal HPV infection adjusted for potential confounders were estimated using robust regression models. Results Of 1179 participants, 309 were eligible for free HPV vaccination. Vaccine coverage among eligible GBM was 42%. Among those who disclosed same-sex sexual activity and discussed HPV vaccination with their healthcare provider, coverage reached 82%. Anal HPV prevalence among eligible GBM was 26.5% for [&ge;]1 HPV-6/11/16/18 genotypes without significant difference between vaccinated and unvaccinated individuals. Among unvaccinated GBM aged [&le;]26 who were aware of the vaccine, 60% intended to get vaccinated within the next year. Conclusions One to two years after GBM aged [&le;]26 were included in the Quebec HPV vaccination program, 42% of eligible GBM in Greater Montreal had been vaccinated. Anal HPV prevalence was high among GBM. Vaccinees were more likely to self-report a prior STI diagnosis. Offering vaccination to all preadolescents in schools appears essential to maximize vaccination benefits.

Methicillin-resistant Staphylococcus (MRS) infections are a significant public health concern. Anterior nares serve as a major reservoir and source of spread of MRS ssp. People living with HIV (PLWHIV) tend to be at higher risk of colonisation with MRS organisms due to frequent healthcare exposure. We assessed the prevalence of MRS nasal carriage and associated factors among PLWHIV at the HIV clinic of Kiruddu National Referral Hospital, Kampala, Uganda, from May to July 2024. Nasal swabs from 256 PLWHIV were cultured, and microbiological isolation was performed at MBN Clinical Laboratories. Prevalence was calculated as proportions, and logistic regression identified associations with clinical and socio-demographic factors (p < 0.05). Of 256 participants, 163 (63.7%) carried Staphylococcus, with 82 (32%) identified as MRS carriers (8.9% MRSA, 23% MRCoNS). Frequent hospital visits ([&ge;]3) (adjusted incidence risk ratio [A-IRR] = 1.18 x 107, p < 0.001), second-line antiretroviral therapy (ART) (A-IRR = 3.82, p = 0.041), and unsuppressed viral load (>1000 copies/mL) (adjusted odds ratio [AOR] = 11.3, 95% CI: 2.11-60.58, p = 0.005) were significantly associated with MRS carriage. Mask-wearing was protective against MRCoNS (A-IRR = 1.66, 95% CI: 1.06-2.58, p = 0.026). MRS isolates exhibited high resistance to erythromycin (81.7%) and trimethoprim-sulfamethoxazole (79.3%), but susceptibility to linezolid (93.9%). MRS nasal carriage is prevalent among PLWHIV. Individuals with frequent health care contact and those on second-line ART regimens are more susceptible to MRS colonization, while individuals who wear face masks and those with an undetectable HIV viral load are less susceptible. Antimicrobial Resistance (AMR) surveillance within HIV programs, enhanced infection control, ART adherence, and targeted screening for high-risk groups are critical to mitigate colonization.

Background: Access to dental care remains a significant challenge for many children in Canada, particularly among low-income and underserved populations. The Interim Canada Dental Benefit (CDB), introduced in October 2022, aimed to reduce financial barriers to oral health care for children under 12 years of age while the Canadian Dental Care Plan (CDCP) was being developed. While emerging evidence has examined program uptake, limited qualitative research has explored parents and caregivers experiences with the Interim CDB. Objective: This study aimed to explore parents and caregivers experiences with the Interim CDB in Manitoba, Canada, including awareness, access, perceived benefits, challenges, and recommendations for program improvement. Methods: A qualitative descriptive study was conducted using semi-structured interviews with 30 parents and caregivers of children under 12 years of age. Participants were recruited primarily through community dental clinics. Interviews were conducted between July 2023 and February 2024, audio-recorded, and transcribed verbatim. Data were analyzed using inductive thematic analysis to identify key themes and subthemes. Results: Seven interconnected themes were identified: (1) limited and uneven awareness of the Interim CDB; (2) inadequate and inequitable communication strategies; (3) barriers to accessing the benefit, including misconceptions about eligibility and complex application processes; (4) dental providers as key facilitators of access; (5) financial relief and improved access to care; (6) gaps in coverage and ongoing financial strain; and (7) participant-driven recommendations for improvement. While the benefit was widely perceived as reducing financial barriers and enabling access to care, challenges related to awareness, communication, and adequacy of coverage limited its overall effectiveness. Participants emphasized the need for improved communication from government, simplified application processes, expanded eligibility, and increased financial support. Conclusion: The Interim CDB represents an important step toward improving access to dental care for children in Canada. However, this study highlights critical implementation gaps related to awareness, accessibility, and coverage. Addressing these challenges will be essential to ensuring the success of the new CDCP and advancing equitable access to oral health care.

Nasopharyngeal (NP) swabs remain the dominant gold standard for respiratory infection diagnostics. While there has been increased use of alternative sample types since the COVID-19 pandemic, guidance on their use for detecting respiratory viruses is not yet definitive, especially for children. In this systematic review and meta-analysis, we aimed to compare the diagnostic accuracy and tolerability of multiple respiratory specimen types for detecting respiratory viruses in pediatric populations. Searches were conducted on July 17, 2025 in MEDLINE, Embase, Web of Science, and Scopus, with screening and data extraction performed in Covidence. English-language primary research articles published since 2000 comparing respiratory virus detection rates in children, using nucleic acid amplification tests between paired respiratory specimens, were included. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies criteria. We calculated pooled sensitivities and specificities of index specimens: nasopharyngeal aspirates (NPA), mid-turbinate swabs (MT), anterior nasal swabs (ANS), oropharyngeal swabs (OP), and bronchoalveolar lavage fluid (BAL), as compared to the reference, NP swabs, using random-effects modeling, firstly without discrimination by virus. Index specimens were then grouped by sample collection site as nasal, oral, and lower respiratory tract (LRT) specimens for virus-specific analyses. Overall performance and statistical validity were evaluated by hierarchical summary receiver operating characteristic (HSROC) analysis. Data regarding sampling tolerability was also assessed. We screened 2,448 studies and identified 36 publications (total N participants = 10,687) that reported diagnostic test accuracy using paired index-reference data in children. Of these, 18 (total N participants = 4,310) used NP specimens as the reference and were included in the diagnostic test accuracy analysis. Virus-agnostic pooled sensitivity estimates indicated that MT (0.92%) performed most similarly to NP, though sensitivities of ANS (0.79%) and OP (0.70%) were also moderately high for detection of any respiratory virus. BAL sensitivity was the lowest (0.37%). All sample types demonstrated high specificity (0.98%-0.99%). Group estimates and HSROC statistics found that nasal specimens, when grouped, had the highest sensitivity and accuracy for all examined viruses, including for influenza (92%) and RSV (90%). By comparison, oral and LRT specimens performed less well, with more variability, though both showed moderately high sensitivities for RSV (78%, 76%, respectively) and influenza (82%, 80%, respectively), and LRT samples showed high sensitivity for HMPV (82%). Analysis of sample tolerability found that NP swabs consistently ranked as the least comfortable and least preferred, while nasal swabs and saliva both performed well. Datasets for LRT and oral specimens were sparser than for nasal, and this contributed to greater variability, underscoring the need for further diagnostic accuracy studies on alternatives to NP sampling. These data support the viability of nasal and oral alternatives to NP swabs and affirm their application in pediatric care, particularly in outpatient settings. Such alternatives could greatly improve sampling tolerability and increase global access, including in resource-limited settings, to accurate diagnostic methods for respiratory infections.

Abstract Background: The sanitation crisis poses a significant public health risk, leading to diseases like diarrhea, cholera, and typhoid, which impede children's health and development in developing countries like Uganda. Improving sanitation infrastructure is crucial for safeguarding child health and future generations. However, the link between sanitation and children's health is complex, influenced by various factors. This investigation in Gulu scrutinizes the correlation between sanitation practices and child well-being, considering moderating factors such as age, climate, and consistent water accessibility. Methods: The study used a convergent parallel design with equal priority. The Social Ecological Model, Social Learning Theory, and Diffusion of Innovations Model guided it. Researchers collected data from 10 health facilities and 317 households, using purposive and simple random sampling. They used sampling proportions proportional to village size within strata. The researcher analyzed quantitative data using SPSS with factor analysis, structural equation modeling, and multivariate analysis. To analyze qualitative data, they used DQA Minor Lite software, which facilitated thematic analysis. Results: The finding shows 56.8% of households had low socio-economic status. Sanitation was poor; 24.9% household had improved latrines, 20.5% had handwashing facilities with soap, and 68.1% used basic anal cleansing. For nutrition, 38.5% of children were malnourished by MUAC; by Z-scores, 28.7% were stunted, 16.4% underweight, 13.6% wasted. Diarrhea affected 62% of children. Climate worsened sanitation: 48.3% had latrines collapse from floods, and 63.4% of waterborne diseases occurred in both dry and wet seasons. Moderation analysis on childhood diarrhea shows that sociocultural factors ({beta} = -0.20, p < 0.001), sanitation ({beta} = -0.15, p < 0.001), and health system response ({beta} = -0.18, p < 0.001) reduced diarrhea. Climate change increased risk ({beta} = 0.15, p < 0.001) and moderated sanitation effects ({beta} = 0.01, p < 0.05). Models explained 10-14% variance. Age and water access had no moderating effect. While childhood malnutrition shows that sociocultural factors ({beta} = -0.43, p < 0.001) and health system response ({beta} = -0.13, p < 0.001) reduced malnutrition. Sanitation had no effect ({beta} = 0.01, p > 0.05). Age increased malnutrition risk ({beta} = 0.28, p < 0.01) and moderated sociocultural effects ({beta} = 0.16, p < 0.001), but not sanitation. The model explained 21% variance, R{superscript 2} = 0.21, p < 0.001. Conclusion: Sociocultural improvements and health system responses lower both diarrhea and malnutrition. Climate worsens diarrhea and alters sanitation's impact. Age worsens malnutrition and changes sociocultural effects. These findings are valuable for policymakers, healthcare professionals, and researchers

Wastewater-based epidemiology has emerged as a powerful complement to clinical surveillance for monitoring infectious disease dynamics. However, most existing approaches either treat wastewater sites in isolation, overlooking spatial dependencies, and often fail to account for variability in data quality, limiting their ability to generate reliable predictions of healthcare demand. Here we present a spatial Bayesian renewal framework that integrates wastewater surveillance with mobility-informed spatial interactions while incorporating reliability-weighted wastewater signals. We apply the framework to three major respiratory pathogens, i.e., SARS-CoV-2, influenza, and respiratory syncytial virus (RSV), using wastewater and hospital data from counties in South Carolina. Across rolling four-week forecasts, the spatial framework consistently outperforms non-spatial approaches and remains robust even in counties lacking direct wastewater or hospitalization observations. Importantly, we show that county-level forecasts can be translated into facility-level predictions, enabling localized assessment of healthcare demand. These forecasts provide actionable early-warning signals to support hospital capacity planning, staffing decisions, and resource allocation. Together, this work establishes a scalable digital surveillance framework that integrates heterogeneous data sources for enabling more reliable infectious disease forecasting and supporting public health decision-making in underserved and data-limited settings.

Background Human challenge trials provide a unique opportunity to quantify pathogen infectivity in terms of the probability of infection given an inoculated dose. However, between-pathogen comparisons are often distorted by individual heterogeneity in host susceptibility and by differences in background immunity across trial populations. We examined how dose-dependent infection risks differ across common respiratory viruses when such heterogeneity is explicitly incorporated. Methods We conducted a systematic review of human challenge trials for four respiratory viruses: respiratory syncytial virus (RSV), influenza virus, rhinovirus, and adenovirus. Using the extracted data, we fitted dose-response models under different distributional assumptions, allowing both continuous susceptibility variation and discrete immune fractions. We compared alternative heterogeneity models and evaluated pathogen-specific dose-response patterns using original and scaled dose metrics. Results All four viruses showed substantial heterogeneity in host susceptibility, and models assuming homogeneous susceptibility were unsupported. RSV and influenza were best described by models with a distinct immune or effectively non-susceptible subgroup, and the estimated immune proportions were approximately 40% and 25%, respectively. In contrast, rhinovirus and adenovirus were better explained by continuously distributed susceptibility, with little evidence of a fully immune subgroup. On a scaled dose axis, rhinovirus and adenovirus showed steeper increases in infection risk with dose than RSV and influenza. Conclusions The structure of susceptibility heterogeneity differs across common respiratory viruses, which in turn shapes dose-dependent infection risks. Incorporating this heterogeneity is essential for valid cross-pathogen comparison and for interpreting human challenge data in epidemiologic and public health contexts.