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Journal articleNgwili N, Kachepa U, Korir M, et al., 2026,
Spatial and temporal risk mapping of human and porcine Taenia solium infections in Malawi: a systematic review and geostatistical approach
, One Health Outlook, Vol: 8, ISSN: 2524-4655Background Taenia solium, colloquially called the pork tapeworm, is a zoonotic parasite with a human definitive host and a porcine intermediate host. Humans can become an aberrant intermediate host due to accidental ingestion of parasite eggs from the environment or through autoinfection, resulting in human cysticercosis (HCC), neurocysticercosis (NCC) if the central nervous system is infected. Pigs become infected with the larval stage, porcine cysticercosis (PCC), through the ingestion of parasite eggs shed by humans through defecation. Malawi has been classified as endemic for T. solium by the WHO based on the presence of key risk factors; however, the subnational distribution is not known. To ensure the appropriate resources are mobilized to support targeted future T. solium control measures in Malawi, there is a need to understand the variation in T. solium endemicity status across the country.Methods The current study uses a systematic literature review (SLR) using a pre-registered protocol; (PROSPERO CRD42023411044) to collate all available evidence on T. solium in Malawi. A geospatial risk mapping approach was conducted based on data from Malawi demographic health surveys (MDHS), and pig density data from the Food and Agriculture Organization (FAO) database to create geospatial risk maps of endemic subnational areas for 2000, 2004, 2010, and 2016. To create a single composite risk factor map for the four years from the MDHS, each parameter was plotted as a binary variable with the high or low risk categories and overlaid into a single composite risk factor classification. Additional data from hospital records on NCC and meat inspection records across several Agricultural Development Divisions (ADDs) were also collected.
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Journal articleQuijada Rodriguez ML, Vicco A, Bajura F, et al., 2026,
Dengue epidemiology and transmission intensity across Panama during 2000-2024: a modelling study
, The Lancet Regional Health. Americas, Vol: 58, ISSN: 2667-193XBackgroundPanama is a dengue endemic country which experienced a large outbreak in 2024 with over 32,000 reported cases and an incidence rate exceeding 700 cases per 100,000 inhabitants. Despite decades of circulation, the epidemiology of dengue and its heterogeneity in transmission intensity across Panama have not yet been characterised.MethodsWe used 25 years of dengue case notification and population data from across Panama's 16 health regions and 82 districts to characterise dengue epidemiology and transmission intensity in the country. The analytic dataset comprised 128,890 dengue cases, of whom 52% were female and 48% were male; the mean age was 32.4 years (range 0–108 years). Ethnicity data are not collected in Panama's national dengue surveillance system and were therefore unavailable for this analysis. We characterised spatial heterogeneities in delay distributions by fitting parametric probability distributions to epidemiological delays, and demographic differences in the incidence risk ratio of dengue, and of dengue attributable hospitalisations and deaths. We also implemented catalytic models to infer the time-constant dengue force-of-infection (FOI) (i.e. the long-term average annual per capita risk of infection for a susceptible individual) from the age-stratified case notification data reported across Panama during 2000–2024 and explored age- and sex-related differences in dengue case reporting in sensitivity analyses.FindingsWe observed spatial variation in delay distributions across health regions. The mean of the regional average time from symptoms onset to (i) reporting was 4.78 days (95% CI: 4.72–4.84 days), (ii) hospitalisation was 4.49 days (95% CI: 4.22–4.76), and (iii) recovery was 7.82 days (95% CI: 6.47–8.85 days). The dengue transmission intensity also showed spatial heterogeneity, with a mean regional per-serotype FOI of 0.008 (95% CrI: 0.004–0.015). The mean regional probability of detecting a secondar
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Journal articleSaluzzo F, Lindahl O, Chindelevitch L, et al., 2026,
When the whole exceeds the sum of its parts: squeezing greater cumulative benefit from cross-technology partnerships in bacterial infection
, International Journal of Infectious Diseases, Vol: 167, ISSN: 1201-9712ObjectivesEffective care for bacterial infections requires both new antibiotics (ABx) to address antimicrobial resistance (AMR) and appropriate diagnostics (Dx) to guide their use. Diagnostics are essential to identify pathogens, determine susceptibility, and support targeted prescribing, including ruling out unnecessary antibiotic use. However, diagnostics are undervalued in the current market, limiting their availability and integration with antibiotic development. To examine the interplay between antibiotics and diagnostics and assess the potential value of coordinated development and partnerships.MethodsThis paper analyses the antibiotic and diagnostic development landscape, focusing on market dynamics, regulatory frameworks, and collaboration models involving ABx developers, Dx developers, clinicians, and public-sector stakeholders.ResultsAntibiotics and diagnostics are rarely developed or introduced in parallel, and available diagnostics often fail to deliver treatment-focused or point-of-care–relevant results. This misalignment hampers the effective deployment of new antibiotics and weakens stewardship. Cross-technology partnerships can improve trial efficiency, enhance market valuation, and support more targeted antibiotic use. Key barriers include fragmented incentives, regulatory misalignment, and financial constraints.ConclusionBetter alignment between antibiotic and diagnostic development is critical to maximise clinical impact and support resistance monitoring. Public-sector support could help enable effective partnerships and improve patient outcomes.
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Journal articleSilva L, Gogoi M, Lal Z, et al., 2026,
Antibiotic knowledge among ethnic minority groups in high-income countries: A mixed-methods systematic review.
, Public Health Pract (Oxf), Vol: 11OBJECTIVES: Antimicrobial resistance (AMR) is a major global public health concern. Although low-income countries are disproportionately affected by AMR, certain underserved groups in high-income countries (HICs), such as migrants and ethnic minorities, disproportionately bear the burden of AMR. This may be driven by socio-cultural factors including differences in health literacy. This review aimed to investigate the level of antibiotic knowledge amongst different ethnic minority groups in HICs. STUDY DESIGN: This was a mixed-methods systematic literature review. METHODS: We searched four databases (MEDLINE, EMBASE, the Cochrane library, CINAHL) to May 5, 2023, for primary studies on knowledge of antibiotics in different ethnic groups in HICs. We included studies in English using qualitative, quantitative and/or mixed-methods approaches and reporting on antibiotic knowledge by ethnicity. We used the convergent integrated approach for data synthesis and the Mixed-Methods Appraisal tool for quality assessment. RESULTS: 3935 articles were screened and 24 studies (17 quantitative, 5 qualitative, and 2 mixed-methods) were included, comprising 52778 participants from 8 countries (USA, UK, Australia, New Zealand, Netherlands, Greece, Sweden, Germany). Overall, participants from ethnic minority groups were able to identify common names of antibiotics and were aware of risks of antibiotics and side effects. However, participants thought antibiotics would treat viral-type illnesses. Ethnic minority groups generally had lower levels of knowledge compared to ethnic majority groups. CONCLUSIONS: Although ethnic minority communities possessed good levels of knowledge on certain aspects of antibiotics (e.g. being able to identify names of antibiotics), there were gaps in other areas (e.g. misperception that antibiotics are used for viral infections). The lower level of knowledge in ethnic minority groups compared to majority groups may be a contributing factor to health inequaliti
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Journal articleManley H, Leber W, Smith K, et al., 2026,
Application of machine-learning algorithms to identify the key determinants of risk for HIV, hepatitis C and hepatitis B in primary care settings.
, BMC Infect DisBACKGROUND: Testing for Blood-Borne-Viruses (BBVs) such as the human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV) is generally focused on specialist settings. However, people with undiagnosed infections are also present within the general population. We explore whether using machine-learning algorithms (MLAs) can identify people at heightened risk of HIV, HBV, HCV, or a composite 'any BBV' (defined as positivity for one or more of the three infections) in primary care settings. METHODS: From de-identified electronic health records data from 165 general practices in North East London we extracted risk factors for HIV, HCV and HBV and used them to train (75% data) and test (25% data) three MLAs: Logistic Regression (LR), AdaBoost with random under sampling (RUSBoost) and Balanced Random Forest classifier (BRFC). The ROC curves, ROC AUC, sensitivity and specificity values quantified the models' performance. Across the models the key features for each outcome were identified. RESULTS: A total of 1,987,954 patients were included in the study with no inclusion or exclusion criteria, from whom 75 predictive features were selected for HIV, 24 for HCV, 37 for HBV and 88 for any BBV outcome. Different models were optimal for individual BBVs positivity classification, depending on the accuracy metric. As a single infection, HCV was predicted most accurately across models and accuracy metrics. When targeting any BBV outcome, LR was the model with highest AUC value, BRFC was the most sensitive model and RUSBoost was the most specific model. The key identified features were similar across models with age the strongest predictor for both individual positivity and the composite outcome. A number of features were important for two of the BBV positive groups: Black African ethnicity (HIV and HBV), liver disease (HBV and HCV) and opiate and cocaine use (HBV and HCV). A number of individual features were important for individual BBVs positivity. CON
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Journal articleBlake I, Islam MO, Fuller B, et al., 2026,
Integration of poliovirus and enteropathogen sewage surveillance in Dhaka Bangladesh: a longitudinal surveillance study June 2019 – June 2020
, The Lancet Microbe, ISSN: 2666-5247Environmental surveillance (ES) for poliovirus is a surveillance method used by the Global Polio Eradication Initiative (GPEI). ES will continue following certification of poliovirus eradication, potentially through its integration into other infectious disease surveillance programs. We evaluated TaqMan array cards (TAC) to detect poliovirus in sewage, whilst simultaneously testing for 11 other enteric pathogens and 34 markers of antimicrobial resistance (AMR) across 12 sites in Dhaka, Bangladesh. Sites were selected following mapping of the informal sewage network and a demographic survey of the population. Samples were collected before and after a bivalent oral polio vaccine (bOPV) campaign. 372 samples were collected over 379 days. A water-quality probe measured physicochemical properties of the sewage. A Multivariable mixed-effects Gamma Hurdle regression model was used to measure the association between enterovirus detection and concentration with site properties. The highest concentration of Sabin-1 and -3 poliovirus was detected two weeks after the bOPV campaign (mean (SD) Sabin- 1 and -3 viral copies per L of sewage: 0·83 (2·13) and 0·84 (1·96)) , (vs baseline 0·05 (0·21) and 0·11 (0·50) respectively) [p=0·004: SL1, p=0·005: SL3] . Detection of enteroviruses was more likely with increasing levels of Total Dissolved Solids (mg/L) (aOR per absolute increase of 100 units 1·39 95%CI: 1·17 – 1·61). The median ES viral load of rotavirus was 0·567 (IQR 0·202-0·839), and this pathogen had the strongest correlation with respective concurrent clinical case incidence (cor = 0·828, p = 0·0017). Thirty-one AMR genes of clinical significance were detected.When GPEI dissolves, poliovirus surveillance needs to be integrated into other surveillance programs. TAC may provide a method to screen suitable pathogens to survey in sewage alongside p
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Journal articleTurner H, Ahmed S, Nguyen HA, et al., 2026,
Economic evaluation of alternative hepatitis C treatment options: a post hoc analysis of the VIETNARMS trial
, EClinicalMedicine, ISSN: 2589-5370BackgroundHepatitis C remains a leading cause of liver disease worldwide, and access to Direct-Acting Antiviral (DAA) treatment remains limited in many settings. Alternative treatment strategies that require fewer tablets and clinical visits could help improve equitable access, and new approaches have recently been found to be non-inferior in producing sustained viral suppression. MethodsWe did a cost-minimization analysis of alternative treatment options for non-cirrhotic patients evaluated in the VIETNARMS trial (ISRCTN61522291), conducted between 19/06/2020 and 10/05/2023 in Vietnam. These were: (i) ‘response guided’ (which adjusts treatment duration based on 1-week viral load); (ii) ‘induction maintenance’ (which reduces the dosing frequency in later weeks of treatment); and (iii) ‘Peg-IFN+DAA’ (4 weeks of DAAs combined with four weekly doses of PEGylated interferon (Peg-IFN). The primary outcome was the cost per cure. A disaggregated societal perspective was adopted, including stratification for the healthcare provider and patient costs. FindingsThe three alternative treatment strategies were projected to have lower costs per cure than standard 12-week DAA treatment in the base-case scenario: US$202 (15%) less for ‘response guided’, US$234 (18%) less for ‘induction maintenance’, and US$163 (12%) less for ‘Peg-IFN+DAA’. However, the potential for cost savings, and which strategy had the lowest cost per cure, depended on the assumed cost of DAA drugs: the strategy with the lowest cost per cure was generally ‘induction maintenance’ when DAA drug costs for a standard treatment course were under US$1,000, but Peg-IFN+DAA when DAA costs exceeded US$1,500. In some scenarios, lower costs per cure were achieved through reduced health system expenditures, despite increased costs to patients.InterpretationAlternative strategies for Hepatitis C treatment could reduce costs for providers an
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Journal articleMohan S, Chagoma N, Walker S, et al., 2026,
Estimating System-Wide Healthcare Costs Using a Health System Model: Application to the Thanzi La Onse Model of Malawi.
, Appl Health Econ Health PolicyOBJECTIVES: Modelling approaches that consider system-wide delivery platforms rather than single diseases can be instrumental in economic evaluation and forward-looking policy formulation. This study develops a costing approach tailored to the Thanzi La Onse (TLO) model of Malawi's healthcare system, with general applicability to other health system models. METHODS: We developed a mixed-method costing approach to estimate the total cost of healthcare delivery (excluding high-level administrative costs) in Malawi using the TLO model, from a healthcare provider perspective. Through iterative adjustments of key parameters, we aligned model-based estimates as closely as possible with real-world expenditure and budget data. Costs were projected for 2023-2030 under alternative scenarios of health system capacity. RESULTS: A comparison with expenditure and budget data suggests our costing method is broadly reliable for the conditions captured by the model, though some mismatches remain owing to data limitations and definitional inconsistencies. Under current system capacity, total healthcare delivery costs for 2023-2030 were estimated at 2.83 billion US dollars [95% uncertainty interval (UI), $2.80-$2.87 billion], excluding non-medical infrastructure and administrative costs, averaging $390.98 million [$385.92-$396.71 million] annually or $16.89 [$16.75-$17.08] per capita. Scenario analysis highlighted strong interdependencies within the health system. Improving consumable availability alone increased consumables costs by 4.63%, while expanding human resources for health (HRH) alone increased them by 1.43%. When both HRH and consumable availability were expanded together, consumable costs rose by 5.93%, a combined effect larger than either change alone, illustrating how bottlenecks in one component constrain the impact of improvements in another. CONCLUSIONS: Mixed-method costing using health system models is a feasible and robust method to estimate and forecast
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Journal articleNascimento FF, Franceschi VB, Volz EM, 2026,
treestructure: an R package to detect population structure in phylogenetic trees.
, Bioinformatics, Vol: 42MOTIVATION: How population structure can shape genetic diversity is a longstanding problem in population genetics. While the use of geographic locations, when available, can help answer some of these questions, it is still difficult to determine population structure when such metadata are not available or when the potential population structure is not easily observed. Here, we present an updated version of treestructure, an R package that implements a statistical test based on coalescent theory to detect unobserved population structure in a time-scaled phylogenetic tree. AVAILABILITY: treestructure is available at CRAN at https://cloud.r-project.org/web/packages/treestructure/ and at https://emvolz-phylodynamics.github.io/treestructure/.
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Journal articleNdiaye A, Motyl F, Drammeh S, et al., 2026,
Carbon emissions associated with antenatal testing for hepatitis B prophylaxis eligibility, the Gambia.
, Bull World Health Organ, Vol: 104, Pages: 301-314OBJECTIVE: To estimate the carbon footprint of three diagnostic strategies to identify pregnant women eligible for antiviral prophylaxis to prevent hepatitis B vertical transmission in the Gambia. METHODS: In 2024, we conducted a life cycle assessment of a point-of-care polymerase chain reaction (PCR) test using plasma, and a rapid diagnostic test for hepatitis B core-related antigen (HBcrAg) using plasma and capillary blood across three hospitals (rural, suburban and urban) and a suburban health centre. We included all products and processes in each diagnostic strategy. The functional unit was an antenatal testing episode assessing eligibility for antiviral prophylaxis, beginning after positive hepatitis B surface antigen screening. We estimated carbon emissions in grams of carbon dioxide equivalent (g CO2e) ± uncertainty. FINDINGS: Mean carbon emissions per strategy were significantly different between point-of-care PCR and the rapid diagnostic tests (P-value: 0.028): 1619.0 ± 200.6 g CO2e (PCR), 520.4 ± 59.1 g CO2e (plasma-based rapid diagnostic test) and 374.3 ± 50.4 g CO2e (capillary-based test). Higher emissions with the PCR test were mainly driven by its reliance on air conditioning (759.1 g CO2e compared with 125.2 g CO2e for plasma-based rapid diagnostic test and 24.3 g CO2e for capillary-based test); the test itself (290.0 g CO2e versus 129.0 g CO2e for rapid diagnostic tests); and PCR-specific requirements including diagnostic device (47.0 g CO2e) and additional patient travel to collect results (255.8 g CO2e). CONCLUSION: Our findings suggest that HBcrAg rapid diagnostic tests can reduce emissions substantially compared with point-of-care PCR. Our study demonstrates that life cycle assessments are feasible in resource-constrained settings and highlights the importance of integrating sustainability into
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