Modelling the COVID-19 pandemic in context : An international participatory approach

Funding RA is funded by the Bill and Melinda Gates Foundation (OPP1193472). LW is funded by the Li Ka Shing Foundation. CF is funded by grant #2017/26770-8, São Paulo Research Foundation (FAPESP). The CoMo Consortium has support from the Oxford University COVID-19 Research Response Fund (ref: 0009280). Scientific writing assistance and editorial support was provided by Adam Bodley, according to Good Publication Practice guidelines.Peer reviewedPublisher PD

Potential health and economic impacts of dexamethasone treatment for patients with COVID-19

Acknowledgements We thank all members of the COVID-19 International Modelling Consortium and their collaborative partners. This work was supported by the COVID-19 Research Response Fund, managed by the Medical Sciences Division, University of Oxford. L.J.W. is supported by the Li Ka Shing Foundation. R.A. acknowledges funding from the Bill and Melinda Gates Foundation (OPP1193472).Peer reviewedPublisher PD

Dissecting cause and effect in host-microbiome interactions using the combined worm-bug model system

High-throughput molecular studies are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome we need robust experimental models that allow the systematic manipulation of variables to test the multitude of hypotheses arisen from large-scale ‘meta-omic’ projects. The nematode C. elegans combined with bacterial models offers an avenue to dissect cause and effect in host-microbiome interactions. This combined model allows the genetic manipulation of both host and microbial genetics and the use of a variety of tools, to identify pathways affecting host health. A number of recent high impact studies have used C. elegans to identify microbial pathways affecting ageing and longevity, demonstrating the power of the combined C. elegans-bacterial model. Here I will review the current state of the field, what we have learned from using C. elegans to study gut microbiome and host interactions, and the potential of using this model system in the future

Algorithm in the diagnosis of febrile illness using pathogen-specific rapid diagnostic tests.

BACKGROUND: In the absence of proper guidelines and algorithms, available rapid diagnostic tests (RDTs) for common acute undifferentiated febrile illnesses (AUFI) are often used inappropriately. METHODS: Using prevalence data of five common febrile illnesses from India and Cambodia, and performance characteristics (sensitivity and specificity) of relevant pathogen-specific RDTs, we used a mathematical model to predict the probability of correct identification of each disease when diagnostic testing occurs either simultaneously or sequentially in various algorithms. We developed a web-based application of the model so as to visualise and compare output diagnostic algorithms when different disease prevalence and test performance characteristics are introduced. RESULTS: Diagnostic algorithms with appropriate sequential testing predicted correct identification of aetiology in 74% and 89% of patients in India and Cambodia respectively compared to 46% and 49% with simultaneous testing. The optimally performing sequential diagnostic algorithms differed in India and Cambodia due to varying disease prevalence. CONCLUSION: Simultaneous testing is not appropriate for the diagnosis of AUFIs with presently available tests, which should deter the unsupervised use of multiplex diagnostic tests. The implementation of adaptive algorithms can predict better diagnosis and add value to the available RDTs. The web application of the model can serve as a tool to identify the optimal diagnostic algorithm in different epidemiological settings, whilst taking into account the local epidemiological variables and accuracy of available tests.</p