Theresa Stocks


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Works at Department of Mathematics (incl. Math. Statistics)
Visiting address Roslagsvägen 101, Kräftriket, hus 6
Room 319
Postal address Matematiska institutionen 106 91 Stockholm

About me

I am a PhD student in the division of Mathematical Statistics at Stockholm University and my supervisors are Tom Britton and Michael Höhle. I am interested in mathematical modeling of infectious diseases with a focus on applying inference methods for partially observed epidemic models.

since 2014: PhD sutdent at the Department of Mathematics
Topic: Simulation-based inference for stochastic epidemic models
Stockholm University, Sweden

2014: Master of Science in Mathematics
Thesis: Quality Measures for Radiation Therapy and their Optimization
University of Muenster, Germany

2012: Research Exchange
Research in optimization of cancer treatment
University of Alberta, Canada

2011: Bachelor of Science in Mathematics
Thesis: Modelling and Prediction of Tumor Control Probabilities
University of  Muenster, Germany


autumn 2017: Categorical Data Analysis


Mathematical Statistics

  • Simulation-based Inference Methods for Partially Observed Markov Processes in Epidemics
  • Mathematical Modelling with an Emphasis on Medical and Biological Processes
  • Applications of Stochastic Processes
  • Numerical Analysis


A selection from Stockholm University publication database
  • Theresa Stocks, Tom Britton, Michael Höhle.

    Infectious disease surveillance data often provides only partial information about the progression of the disease in the individual while disease transmission is often modelled using complex mathematical models for large scale data, where variability only enters through a stochastic observation process. In this work it is shown that a rather simplistic, but truly stochastic transmission model, is competitive with respect to model fit when compared with more detailed deterministic transmission models and even preferable because the role of each parameter and its identifiability is clearly understood in the simpler model. The inference framework for the stochastic model is provided by iterated filtering methods which are readily implemented in the R package pomp available from the comprehensive R archive network (CRAN). We illustrate our findings on German rotavirus surveillance data from 2001 to 2008 and calculate a model based estimate for the reproduction number R0 using these data.

  • 2017. Theresa Stocks (et al.).

    This thesis consists of two papers dealing with the stochastic dynamic modelling of one communicable and one non-communicable disease respectively. In the first paper we derive a patient- and organ-specific measure for the estimated negative side effects of radiotherapy using a stochastic logistic birth-death process. We find that the region of a maximum tolerable radiation dose can be approximated by an asymptotic simplification  and illustrate our findings on brachytherapy for prostate cancer. The second paper is concerned with the stochastic dynamic modelling of infectious disease spread in a large population to explain routine rotavirus surveillance data.  More specifically, we show that a partially observed dynamical system which includes structural variability in the transmission rates but which is simple with respect to disease progression is able to explain the available incidence data. A careful mathematical analysis addresses parameter identifiability and a model-based estimate for the basic reproduction number $R_0$ is given. As inference method we use iterated filtering which is implemented in the \texttt{R} package \texttt{pomp}, available from the comprehensive R archive network (CRAN).

  • 2016. Theresa Stocks (et al.). Mathematical Medicine and Biology

    The normal tissue complication probability (NTCP) is a measure for the estimated side effects of a given radiation treatment schedule. Here we use a stochastic logistic birth–death process to define an organ-specific and patient-specific NTCP. We emphasize an asymptotic simplification which relates the NTCP to the solution of a logistic differential equation. This framework is based on simple modelling assumptions and it prepares a framework for the use of the NTCP model in clinical practice. As example, we consider side effects of prostate cancer brachytherapy such as increase in urinal frequency, urinal retention and acute rectal dysfunction.

Show all publications by Theresa Stocks at Stockholm University

Last updated: September 21, 2018

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