The evolution of virulence in a human infectious disease: the case study of HIV (Meeting)

We intend to combine large-scale data analysis and mathematical modeling to address the past and potential future trends of HIV virulence. Using a network of collaborations with HIV cohorts in North America, Europe and Africa, we will build a database of clinical data known to be relevant for studies of HIV virulence. We will define new standards for recording clinical data, and also for selecting, pooling and analyzing such data over time. By standardizing data collection and analysis across multiple cohorts, we will be able to recognize and control for potential discrepancies or local trends across cohorts, and to derive current best practices for the estimation of virulence trends in the HIV pandemic. NESCent Informatics support will be critical for issues concerning appropriate methods of data sharing across cohorts, the storage of such data in a public repository, and the development and public release of software for the analysis of virulence data across epidemiologically diverse cohorts. In addition to empirical analysis, we will use mathematical modeling to predict future trends of HIV virulence, taking into account the effect of potential interventions, e.g. “test and treat” approaches or disease-modifying vaccines. The two arms of the proposal will enjoy strong synergy: modeling will guide the collection and interpretation of data, and the large-scale data and knowledge base will provide a firm foundation for the design of the models. Synergy will be further strengthened by the cross-disciplinary collaboration of experts from clinical and theoretical epidemiology and mathematical modeling.

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