Kurs: Stochastic epidemic models with inference

Stochastic epidemic models with inference (June 24-26)

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This course page is not finalized: more information will appear later

Course Instructors

Tom Britton, Stockholm University

Lorenzo Pellis, University of Manchester

Course contents:

Basic stochastic epidemic models and their properties

Extensions (SEIR, multitype, …)

Household epidemic models (overview)

Network epidemic models (overview)

Endemic models

Interventions & Vaccination

Applications

Inference (based on final size or during epidemic), R_0, R_t, household models

Time and Place

All lectures take place at Stockholm University in Campus Albano, house 1, level 2, room 4. See Registration and Venue for further details.

Lecture times (includes also problem solving, tutorials, computer sessions, ...):

Monday June 24: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

Tuesday June 25: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

Wednesday June 26: 9.00-10.30, 11.00-12.30

General prerequisites

It is expected that course participants have basic knowledge of statistics and mathematics and rudimentary knowledge of infectious disease epidemiology. It is also expected that participants have basic computer software knowledge and preferably are familiar with the software R.

IMPORTANT: All participants are expected to bring a laptop with R installed on it.

Additional prerequisites for this course

Nothing additional beside general prerequisites, but good to know basic probability and statistics

Relevant literature

There are several monographs in the area, for example Diekmann, et al (2013): Mathematical tools for understanding infectious disease dynamics. Princeton UP.

There are also some overview papers, some egocentric examples are:

Britton, T. Epidemic models on social networks - with inference. (2020). Statistica Neerlandica (Special issue on Network modelling and analysis), 74:3, 222-241, https://doi.org/10.1111/stan.12203

Britton, T.: Stochastic epidemic models: a survey. (2010) Math. Biosci, 225, 24-35. (available below)

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