Introduction to epidemiological modelling using R. We'll be following a number of papers and blogs in order to introduce a variety of mathematical epidemiology methods.
- Noncollapsibility, confounding, and sparse data bias
- June 2018 An introduction to data imputation
- Feb 2018. An introduction to infectious disease modelling
- Jan 2018. A clarification of transmission terms in host-microparasite models: numbers, densities and areas.
- Nov 2017. Perturbations in Epidemiological Models: When zombies attack, we can survive!
- Oct 2017. Modelling and calibration of the hepatitis C epidemic in Australia.
- Sep 2017. Vicious and virtuous circles in the dynamics of infectious disease and the provision of health care: gonorrhea in Britain as an example.
- July 2017. Estimating the future burden of multidrug-resistant and extensively drug-resistant tuberculosis in India, the Philippines, Russia, and South Africa: a mathematical modelling study.
- June 2017. Optimizing an HIV testing program using a system dynamics model of the continuum of care
- May 2017. Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)
- Estimating the fitness cost and benefit of cefixime resistance in Neisseria gonorrhoeae to inform prescription policy: A modelling study
- Introduction to POMP for partially observed data
- Epimodel R package
- Principled Bayesian workflow
- Reflection on modern methods: a common error in the segmented regression parameterization of interrupted time-series analyses
- Philosophy and the practice of Bayesian statistics