We evaluated two novel, portable microscopes and locally acquired, single-ply, paper towels as filter paper for the diagnosis of Schistosoma haematobium infection. The mobile phone-mounted Foldscope and reversed-lens CellScope had sensitivities of 55.9% and 67.6%, and specificities of 93.3% and 100.0%, respectively, compared with conventional light microscopy for diagnosing S. haematobium infection. With conventional light microscopy, urine filtration using single-ply paper towels as filter paper showed a sensitivity of 67.6% and specificity of 80.0% compared with centrifugation for the diagnosis of S. haematobium infection. With future improvements to diagnostic sensitivity, newer generation handheld and mobile phone microscopes may be valuable tools for global health applications.

Schistosomiasis affects over 170 million people in Africa. Here we compare a novel, low-cost mobile phone microscope to a conventional light microscope for the label-free diagnosis of Schistosoma haematobium infections in a rural Ghanaian school setting. We tested the performance of our handheld microscope using 60 slides that were randomly chosen from an ongoing epidemiologic study in school-aged children. The mobile phone microscope had a sensitivity of 72.1% (95% confidence interval [CI]: 56.1–84.2), specificity of 100% (95% CI: 75.9–100), positive predictive value of 100% (95% CI: 86.3–100), and a negative predictive value of 57.1% (95% CI: 37.4–75.0). With its modest sensitivity and high specificity, this handheld and cost-effective mobile phone–based microscope is a stepping-stone toward developing a powerful tool in clinical and public health settings where there is limited access to conventional laboratory diagnostic support.

Simple, efficient, and cost-effective strategies are needed for urine sample preparation in the field diagnosis of infection with Schistosoma haematobium. In this proof-of-concept study, we evaluated inexpensive and widely available paper products (paper towels, school workbook paper, and newspaper) to gravity-filter urine containing 60 eggs/mL of Schistosoma haematobium. Eggs were reliably visualized by light microscopy by using single-ply paper towels as urine filters. This filtration method has broad applicability in clinical and public health settings in resource-constrained environments.

Background and Aim: Mathematical modelling plays an important role in public health by enabling the prediction of disease outbreaks, assessment of transmission dynamics and evaluation of intervention strategies. Although widely applied in high‐resource settings, its use in underserved contexts remains underexplored. This review aimed to examine and synthesize current evidence on the application of mathematical modelling for predicting and controlling infectious diseases in underserved settings.Methods: A comprehensive and reproducible search was conducted using Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) and population, intervention, comparison and outcome (PICO) frameworks across databases, including PubMed, Scopus, Medline, ScienceDirect and EBSCOhost. Keywords and Medical Subject Headings (MeSH) terms related to mathematical modelling and infectious disease control were applied. Two reviewers independently screened titles, abstracts and full texts, with a third resolving discrepancies. Thematic analysis and meta‐analysis were used for synthesis.Results: Out of 838 studies screened, 27 (3.2%) met inclusion criteria. Deterministic models were most used, followed by stochastic and agent‐based models. Diseases modelled included COVID‐19, malaria, tuberculosis (TB), Ebola, Zika, chikungunya, dengue, diphtheria, respiratory infections, visceral leishmaniasis (VL) and Mpox. Modelling predicted the impact of interventions on transmission, with pooled effect size (Ro) of 1.32 (θ = 1.3, p < 0.0001). However, challenges, such as data underreporting, gaps and inconsistencies, were common, potentially affecting model accuracy and real‐world applicability.Conclusion: Mathematical modelling has demonstrated value in supporting infectious disease control in underserved settings. However, the predominance of deterministic models limits adaptability across diverse contexts. Poor data quality further constrains reliability. Future work should focus on expanding modelling approaches, strengthening data infrastructure and addressing a broader range of diseases. These findings can guide public health policy by supporting data‐driven decision‐making, improving resource allocation and integrating modelling into outbreak preparedness and response strategies in underserved settings.

Chronic Kidney Disease (CKD) remains a significant global non-communicable disease (NCD) that affects more than 10% of the world's population. Attention is gradually shifting to tertiary prevention of CKD to avoid End-Stage Renal Disease (ESRD) progression. This study reviewed evidence of the use of a Dietary Approach to Stop Hypertension (DASH) and its effect on disease progression among patients living with CKD. A comprehensive search was conducted using the Scopus, PubMed, Web of Science, ProQuest, and EBSCOHost databases for studies published from 1997 to 2025. The PICO framework guided the search, focusing on patients with CKD, DASH as the intervention, other dietary and non-dietary approaches as comparisons, and CKD progression measured by changes in estimated Glomerular Filtration Rate (eGFR) and/or Urine Albumin-to-Creatinine Ratio (UACR) as outcomes. Effect sizes with 95% confidence intervals and pooled effects were calculated using random effects REML models and Z-tests. Percentage changes in renal function post-intervention, based on eGFR, were also computed. Cochran's Q test and the I-squared (I²) statistic assessed study heterogeneity. This review protocol is registered with PROSPERO (CRD42024588682). Of the 174 studies screened, four met the eligibility criteria and were included in the review. All were prospective cohort studies with an average follow-up of 5.5 years and a combined patient sample size of 7033. Across studies, low DASH adherence was defined as scores in the lower half of the possible range used, and high adherence as scores in the upper half (e.g., 0-40 vs. 41-80; 0-4 vs. 5-9; 8-24 vs. 25-40). Low DASH adherence was associated with a mean eGFR improvement of 0.54 mL/min/1.73m² (1.2%) (Z=0.57, p=0.57), while high adherence showed a greater improvement of 3.34 mL/min/1.73m² (6.8%) (Z=1.77, p=0.08). Only one study assessed UACR, reporting a lower median UACR with high DASH adherence (33.6 mg/g) compared to low adherence (55.6 mg/g). The DASH diet has the potential to slow CKD progression; however, consistent adherence is crucial to maximize its clinical benefits and improve renal outcomes. Although improvements in eGFR with DASH diet adherence are clinically meaningful, they lack statistical significance. These findings support global efforts towards achieving Sustainable Development Goal 3 for NCDs.