Mathematical and statistical modelling of infectious diseases and their prevention

Project leader

Funding source

Swedish Research Council - Vetenskapsrådet (VR)

Project Details

Start date: 01/01/2016
End date: 31/12/2019
Funding: 3200000 SEK


The current project involves stochastic modelling and analysis of epidemic outbreaks, as well as development of statistical methodology for these situations. More specifically, the first sub-project aims at improving current state of the art statistical methods for analysing new emerging outbreaks. We will study statistical studies from the two most recent emerging outbreaks (the H1N1 influenza pandemic and the recent Ebola outbreak in West-africa). There are several biases caused by different reasons: observing a growing epidemic, observing proxies rather than true infection times, and censoring from the epidemic not being observed until the end. The aim with this first sub-project is to define new improved yet simple estimation methods. The second sub-project is more theoretical/mathematical and consists of stochastic modelling for epidemics taking place on dynamic networks. Epidemics taking place on static networks are by now quite well understood. However, in reality, individuals change acquaintances over time, and this will have an effect on outbreak characteristics, at least if considering longer time spans. The aim with the project is to increase understanding of how different model parameters affect the outbreak dynamics, in particular whether the epidemic is super-critical or not, and in the latter case how big an outbreak might become before dying out or reaching endemicity. The conclusions may also have spin-off results of interest to public health authorities. For example the distinction between concurrent and non-overlapping sexual partnerships, and how this affects the potential for sexually transmitted infections to become endemic might be better understood.

Last updated on 2017-28-07 at 10:35