Objective: There is insufficient evidence on the role of self‐financing patient support groups in the control of blood pressure (BP) and/or diabetes in low‐ and middle‐income countries (LMICs). We conducted a systematic review to investigate the effectiveness of these groups in BP and glycaemic control.Methods: We searched PubMed, Embase, SCOPUS, Web of Science, Global Health, African Journals Online, CINAHL and African Index Medicus for published peer‐reviewed articles from inception up to November 2021. Grey literature was obtained from OpenGrey. Studies on patient support groups for hypertension and/or diabetes with a component of pooling financial resources, conducted in LMICs, were included. Narrative reviews, commentaries, editorials and articles published in languages other than English and French were excluded. Study quality and risk of bias were assessed using the National Institutes of Health Quality assessment tool and the revised Cochrane risk‐of‐bias tool. Results are reported according to PRISMA guidelines.Results: Of 724 records screened, three studies met the criteria: two trials conducted in Kenya and a retrospective cohort study conducted in Cambodia. All studies reported improvement in BP control after 12 months follow‐up with reductions in systolic BP of 23, 14.8, and 16.9 mmHg, respectively. Two studies reported diabetes parameters. The first reported improvement in HbA1c (reduction from baseline 10.8%, to 10.6% at 6 months) and random blood sugar (baseline 8.9 mmol/L, to 8.5 mmol/L at 6 months) but these changes did not achieve statistical significance. The second reported a reduction in fasting blood glucose (baseline—216 mg/dl, 12 months—159 mg/dl) in diabetic patients on medication.Conclusion: Self‐financing patient support groups for diabetes and hypertension are potentially effective in the control of BP and diabetes in LMICs. More studies are needed to add to the scarce evidence base on the role of self‐financing patient support groups.

Japanese encephalitis virus (JEV) causes ~100,000 clinical cases and 25,000 deaths annually worldwide, mainly in Southeast Asia and the Western Pacific and mostly in children. JEV is transmitted to humans through the bite of mosquitoes that have fed on competent hosts. Abiotic factors, such as seasonal rainfall, influence transmission. Transmission models have an important role in understanding disease dynamics and developing prevention and control strategies to limit the impact of infectious diseases. Our goal was to investigate how transmission models capture JEV infection dynamics and their role in predicting and controlling infection. This was achieved by identifying published JEV transmission models, describing their features and identifying their limitations, to guide future modelling. A Preferred Reporting Items for Systematic Reviews and Meta‐Analyses Extension for Scoping Reviews (PRISMA‐ScR)‐guided scoping review of peer‐reviewed JEV transmission models was conducted. Databases searched included PubMed, ProQuest, Scopus, Web of Science and Google Scholar. Of the 881 full‐text papers available in English, 29 were eligible for data extraction. Publication year ranged from 1975 to 2023. The median number of host populations represented in each model was 3 (range: 1–8; usually humans, mosquitoes and pigs). Most (72% [ n = 21]) models were deterministic, using ordinary differential equations to describe transmission. Ten models were applied (representing a real JEV transmission setting) and validated with field data, while the remaining 19 models were theoretical. In the applied models, data from only a small proportion of countries in Southeast Asia and the Western Pacific were used. Limitations included gaps in knowledge of local JEV epidemiology, vector attributes and the impact of prevention and control strategies, along with a lack of model validation with field data. The lack and limitations of models highlight that further research to understand JEV epidemiology is needed and that there is opportunity to develop and implement applied models to improve control strategies for at‐risk populations of animals and humans.

Japanese encephalitis virus (JEV) is the leading cause of viral encephalitis in Southeast Asia and is thought to circulate between Culex mosquitoes, amplifying pig hosts, and ardeid birds, with humans acting as incidental dead-end hosts. However, multiple mosquito species may contribute to transmission, making community composition, abundance, and feeding behaviour important for understanding human exposure risk. This study investigated mosquito diversity, abundance, and blood feeding patterns across 24 sites in three Philippine provinces with a history of JEV cases. Mosquitoes were collected using CO₂-baited BG-Pro traps during five surveys between August 2024 and February 2026, and associations with environmental and host-density variables were assessed using generalised linear mixed-effects models. A total of 8,595 mosquitoes were collected, including 5,378 females representing eight genera and 13 species. Culex dominated collections (86.5%), with Culex quinquefasciatus the most abundant species. Mosquito abundance, diversity, and blood feeding activity were higher during the rainy season, while abundance increased with temperature and chicken density and diversity was greatest in high NDVI and low human dense environments. Genus-specific analyses showed overall abundance patterns were largely driven by Culex, whereas Aedes and Armigeres exhibited distinct environmental responses. Of 274 blood meals, 88.3% originated from chickens, primarily from Cx quinquefasciatus, highlighting the critical need to study the potential role of chickens in JEV ecology.

Background: Understanding mosquito blood-feeding preferences can help infer vector-borne pathogen transmission dynamics and improve intervention strategies for important human and animal pathogens. The gold-standard tests for identifying mosquito blood meals are expensive, time-consuming methods and decrease in accuracy as blood meals are digested. Mid-infrared spectroscopy with machine-learning (MIRS-ML) can offer a rapid, cost-effective alternative approach to identifying host blood meals but has never been used to analyse blood meals from Culex spp., an increasingly important genus of vectors of several high-priority multi-host pathogens such as orthoflaviviruses and filariasis. Methods: In this study, laboratory-reared Culex quinquefasciatus were fed blood from six hosts (human, pig, chicken, cattle, dog and horse). Dried bloodspots were created 6, 12, 24 and 30 h after digestion in the mosquito by rolling abdominal contents onto filter paper and then scanned using a Bruker ALPHA Fourier-transform infrared spectrometer. The spectra generated were used to train a multilayer perceptron algorithm to predict blood meals from these six host species and then tested on field-collected mosquito blood meals. Results: For laboratory-reared mosquitoes, the model was 93.6% accurate in predicting host species in comparison to 16.7% random classification, with a small decline in accuracy after 30 h of digestion (6%). While the accuracy for field-collected bloodspots was lower (67.9%), this likely reflects differences in blood source from wild mosquitoes, such as no anticoagulants and direct feeding from hosts rather than artificial feeders. Model performance was further enhanced by applying a probability threshold, which increased accuracy to 78% in field samples while removing 21% samples. Conclusions: This study demonstrates the potential application of MIRS-ML with dried bloodspots as a practical, scalable tool for blood meal analysis with scope for improving accuracy through further model development. This method may be of particular use for large-scale surveillance programmes in low-resource settings due to low running and labour costs. Further development of this method using samples from field-collected mosquitoes could enhance classification accuracy and expand the range of identifiable host species.