2671 research outputs found
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Codelists for "Performance of the Self-controlled case series with active comparators for drug safety signal detection using the Clinical Practice Research Datalink (CPRD)."
No full textCodelists for "Performance of the Self-controlled case series with active comparators for drug safety signal detection using the French administrative healthcare database (SNDS)."
No full textCode and data for: The case for composable probabilistic infectious disease models
No full textRecent outbreaks of Ebola, COVID-19 and mpox have demonstrated the value of modelling for synthesising data for rapid evidence to inform decision making. Effective models require integration of expert domain knowledge from multiple domains such as clinical medicine, environmental science, behavioural research, and public health, yet current modelling approaches create barriers to this integration. Methods used to synthesise available data broadly fall into pipeline approaches that chain separate models together, losing information and potentially introducing bias, or joint models that are often monolithic and difficult to adapt. These barriers have prevented advances across multiple settings where models could have provided actionable insights. Composable models where components can be reused across different contexts and combined in various configurations whilst maintaining statistical rigour could address these limitations. In this work, we start by outlining proposed requirements for a composable infectious disease modelling framework and then present a proof of concept that addresses these requirements through composable epidemiological components built on Julia's type system and Turing.jl. We demonstrate a prototype R interface showing how such frameworks can bridge software ecosystems. Through three case studies, we show how components can be reused across different models whilst maintaining statistical rigour. The first replicates a COVID-19 analysis for South Korea using a renewal process with time-varying reproduction numbers. The second extends these components with reporting delays and day-of-week effects to replicate EpiNow2, a real-time nowcasting tool. The third replicates an SIR model analysis of influenza outbreak data, integrating ODE solvers. We then discuss strengths, limitations, and alternative approaches. Our approach demonstrates promise for enabling interdisciplinary collaboration by lowering technical barriers for domain experts to contribute directly to model development. Future work is needed to solve remaining composability challenges, explore other options, expand the component library, and explore opportunities for large language model assisted model construction
Rapid Assessment of Avoidable Blindness Report: Mali, Koulikoro (2024)
No full textA report including output of standardised analysis of vision and eye health survey data including tables of vision impairment prevalence and service coverage estimates
tomsumner/Timing_of_vaccination
No full textCode written as part of a project to mathematically model the health impact of novel tuberculosis vaccines on TB burden in people living with HIV (PLHIV). The work explores the effects of different vaccine characteristics and delivery strategies (vaccinating PLHIV, HIV uninfected, or both) on the predicted health impact. The code supports the publication, "The delivery of new tuberculosis vaccines to people living with HIV – when to vaccinate?"
Transcripts of the COVID-19-related material from the focus group discussions and in-depth interviews
No full textSupporting files for the PLOS publication, "Food insecurity in South Indian households with TB during COVID-19 lockdowns and the impact of nutritional interventions: A qualitative study". These include transcripts of COVID-19-related material from the focus group discussions and in-depth interviews, In-depth interview questions for household contacts, and Focus group discussion guide
S1 Data for: "Do community-level factors play a role in HIV self-testing uptake, linkage to services and HIV-related outcomes? A mixed methods study of community-led HIV self-testing in rural Zimbabwe"
No full textStata dataset and documentation made available to support the publication, "Do community-level factors play a role in HIV self-testing uptake, linkage to services and HIV-related outcomes? A mixed methods study of community-led HIV self-testing in rural Zimbabwe". All files are hosted on Figshare
jodyphelan/NTM-Profiler
No full textCode for NTM-Profiler, a tool to predict species and drug resistance from NTM WGS data
Dataset for the "Evaluation of the diagnostic accuracy of the ReLASV Pan-Lassa Antigen Rapid Test for Lassa Fever in Nigeria"
No full textLassa fever is a zoonotic disease found in several countries across West Africa, with estimates of up to 300,000 infections and 10,000 deaths yearly. The highest incidence is in Nigeria. Suspected cases are often seen in areas with limited infrastructure and diagnostics capacity, hence the availability of an accurate rapid diagnostic test (RDT) that could be used in the community would be an important public health tool. Unfortunately, few RDTs for Lassa fever exist and have not been thoroughly validated. Toward that end, we conducted a Phase 2 performance evaluation to assess the diagnostic accuracy of the ReLASV Pan-Lassa Antigen Rapid Test (Zalgen Labs, Frederick, MD, USA) using archived, frozen whole blood, plasma, and serum samples collected from individuals in Nigeria to determine its suitability for widespread use as a screening tool for Lassa fever. The overall performance of this RDT was measured against the reference test, the Altona RealStar LASV real-time reverse transcription polymerase chain reaction 2.0 (Altona Diagnostics, Hamburg, Germany). The sensitivity and specificity of the ReLASV Pan-Lassa Antigen Test were 65% and 50.7%, respectively. The low diagnostic accuracy indicated in our and other independent evaluations of the ReLASV Pan-Lassa Antigen Rapid Test suggests that this test, at least until further developed, refined, and validated, is not suitable for making critical diagnostic or treatment decisions for Lassa fever, at least for lineages that commonly circulate in Nigeria. These findings underscore the importance of thoroughly assessing the performance characteristics of tests to ensure their reliability and accuracy
Prediction models for Mtb infection among adolescent and adult household contacts in high tuberculosis incidence settings
No full textTuberculosis household contacts are at high risk of developing tuberculosis. Tuberculosis preventive therapy (TPT) is highly effective, but implementation is hindered by limited accessibility of diagnostic tests aimed at detecting Mycobacterium tuberculosis ( Mtb) infection. Development of Mtb infection prediction models to guide clinical decision-making aims to overcome these challenges. We used data from 1905 tuberculosis household contacts (age ≥10 years) from Zimbabwe, Mozambique and Tanzania to develop two prediction models for Mtb infection determined by interferon-gamma release assay (IGRA) using logistic regression with backward elimination and cross-validation and converted these into a risk score. Model performance was assessed using area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. We developed a basic model with six predictors (age, caregiver role, index case symptom duration, index HIV status, household crowding, and index GeneXpert MTB/Rif results) and a comprehensive model with eleven predictors. The basic and comprehensive risk scores showed limited predictive capability (AUROC 0.592, sensitivity 76%, specificity 35% and AUROC 0.586, sensitivity 76%, specificity 36% respectively), with considerable overlap across IGRA-positive and -negative individuals. Neither model conferred net benefit over a treat-all strategy. Overall, our results suggest that the prediction models developed in this study do not add value for guiding TPT use in high-tuberculosis burden settings. This likely reflects complex Mtb transmission dynamics at the household- and community-level, variation in individual-level susceptibility and immune response, as well as limited accuracy of IGRA testing. Improved diagnostics to determine Mtb infection status in terms of ease-of-use, accuracy, and costs are needed