title: Systems Medicine and Infection.
abstract: By using a systems-based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model and ultimately increase the accuracy of predictions.SIR models are used to describe epidemics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed.HIV is a complex disease where much is still to be learned about the virus and the best effective treatment. With basic mathematical modeling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computational resources now available, and interdisciplinary cooperation, further breakthroughs are inevitable.In TB, modeling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease.A systems medicine approach to infection modeling helps identify important biological questions that then direct future experiments, the results of which improve the model in an iterative cycle. This means that data from several model systems can be integrated and synthesized to explore complex biological systems.
authors.affiliation: School of Medicine, University of St Andrews, Medical and Biological Sciences Building, North Haugh, Fife, St Andrews, KY16 9TF, UK. rec9@st-andrews.ac.uk.
authors.forename: Ruth
authors.initials: R
authors.lastname: Bowness
mesh_terms: D060085:Coinfection; D003141:Communicable Diseases / Q000453:epidemiology / Q000209:etiology; D015658:HIV Infections / Q000453:epidemiology / Q000209:etiology; D006801:Humans; D008962:Models, Theoretical; D049490:Systems Biology / Q000379:methods; D014376:Tuberculosis / Q000453:epidemiology / Q000209:etiology
keywords: Epidemic; HIV; Infection; Mathematical; Modeling; Tuberculosis