Infectious Disease Dynamics

A podcast by Cambridge University

53 Episodes

  1. HIV and the AIDS epidemic - past, present and future

    Published: 5/30/2014

  2. Temporal epidemic dynamics in the presence of contact network structure

    Published: 9/18/2013

  3. Is HIV short-sighted? Insights from a multistrain nested model

    Published: 9/16/2013

  4. Integrating viral epidemiology and evolution

    Published: 9/10/2013

  5. Constrained interventions in outbreak models - balancing conflicting policy objectives

    Published: 9/9/2013

  6. The process of re-exposure to an infectious agent

    Published: 9/9/2013

  7. Mathematical models of the evolution and epidemiology of drifting influenza

    Published: 9/6/2013

  8. Bovine TB and Badgers - the science behind the controversy

    Published: 9/5/2013

  9. Untangling human and animal transmission cycles of sleeping sickness

    Published: 9/3/2013

  10. Fluscape

    Published: 9/2/2013

  11. Recent progress in mathematical epidemiology and some future needs

    Published: 8/27/2013

  12. Decision Making for Prevention/Control Under Economic Constraints

    Published: 8/27/2013

  13. Models for Malaria Control and Elimination

    Published: 8/27/2013

  14. Ending AIDS: Past, Present and Yet to Come

    Published: 8/27/2013

  15. The role of multi-locus models in understanding within-host population dynamics

    Published: 8/23/2013

  16. Recovering transmission structure and dynamics from viral sequence data

    Published: 8/23/2013

  17. Whither disease ecology? Old problems and new solutions

    Published: 8/23/2013

  18. Network structure consequences and control: past and future

    Published: 8/23/2013

  19. Whither disease ecology? Old problems and new solutions in a complex world

    Published: 8/23/2013

  20. The Evolution & Adaptation of Influenza A Viruses in Swine

    Published: 8/23/2013

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On 1 January 2013, it will be twenty years since Epidemic Models started as a 6-month programme in the first year of the Isaac Newton Institute for Mathematical Sciences. Since then, the field has grown enormously, in topics addressed, methods and data available (e.g. genetics/genomics, immunological data, social, contact, spatial, and movement data were hardly available at the time). Apart from these advances, there has also been an increase in the need for these approaches because we have seen the emergence and re-emergence of infectious agents worldwide, and the complexity and non-linearity of infection dynamics, as well as effects of prevention and control, are such that mathematical and statistical analysis is essential for insight and prediction, now more than ever before. Read more at http://www.newton.ac.uk/programmes/IDD/. Image from The New England Journal of Medicine, Gardy, 'Whole-Genome Sequencing and Social-Network Analysis of a Tuberculosis Outbreak', Volume 364, pp 730-9. Copyright ©2011 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.