Dr Panayiota Touloupou BSc MSc PhD

Dr Panayiota Touloupou

School of Mathematics
Lecturer in Mathematics and Statistics

Contact details

Address
School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Panayiota Touloupou is a Lecturer in Mathematics and Statistics. Panayiota's research interests lie in statistical methodology and computational statistics. Her research mostly involves aspects of stochastic epidemic models, and applying and developing statistical methodology for the study of infectious diseases. Panayiota is a member of the Mathematical Biology and Healthcare Group, the Applied and Computational Statistics Group and the Institute of Interdisciplinary Data Science and AI. She is also a member of Equality, diversity and inclusion (EDI) committee of the School of Mathematics. Panayiota was a member of the Neglected Tropical Disease modelling consortium. Panayiota has received funding for her research from Bill and Melinda Gates Foundation and the Task Force for Global Health.

Qualifications

  • PhD in Statistics, University of Warwick, 2016
  • MSc in Statistics, University of Warwick, 2012
  • BSc in Mathematics and Statistics, University of Cyprus, 2011

Biography

Panayiota Touloupou graduated with a BSc in Mathematics and Statistics from the University of Cyprus in 2011. She then moved to the University of Warwick to study for the MSc degree in Statistics and she carried on her studies for a PhD in Statistics under the supervision of Dr Simon Spencer and Prof. Barbel Finkenstadt at the University of Warwick. The title of her PhD was 'Bayesian inference and model selection for partially observed stochastic epidemics' and she has continued to work in infectious disease modelling ever since. In July 2016 she became a Research Fellow of the Neglected Tropical Disease modelling consortium, a large-scale international multidisciplinary collaboration between research groups working on neglected tropical disease.

As of November 2020 she became a Lecturer in Mathematics and Statistics in the School of Mathematics at the University of Birmingham.

Teaching

Semester 2

LH Applied Statistics (Jinan)

Postgraduate supervision

Panayiota Touloupou is interested in supervising PhD students in Applied Statistics with particular focus on epidemiology. If you are interested, please email her.

Research

Panayiota’s research is concerned with mathematical modelling of infectious diseases and the development of novel statistical methods needed for model fitting and model selection.

Research Themes

  • Bayesian inference for infectious disease data 
  • Model comparison and model assesment
  • Stochastic epidemic models

Research Activity

Panayiota’s research spans from mathematical modelling of infectious diseases and the statistical methods needed for model fitting, to the epidemiology of pathogens she is modelling. Her PhD thesis explored Bayesian techniques for parameter estimation and model comparison in the context of partially observed epidemic data. More specifically, in her PhD she developed new inference methods to learn the epidemiology of Escherichia coli O157 in cattle. Her most recent work on the project 'Projections on eliminating neglected tropical diseases' has involved developing new methods of linking geospatial models of disease prevalence with transmission models of epidemic dynamics in order to make maps of future projections of disease. These predictions can be used to inform policy makers where elimination efforts should be focused and how long it will take until elimination is achieved.

Publications

Recent publications

Article

Prada, JM, Stolk, WA, Davis, EL, Touloupou, P, Sharma, S, Munoz, J, Rivera, RC, Reimer, LJ, Michael, E, de Vlas, SJ & Hollingsworth, TD 2021, 'Delays in lymphatic filariasis elimination programmes due to COVID-19, and possible mitigation strategies', Transactions of the Royal Society of Tropical Medicine and Hygiene, vol. 115, no. 3, pp. 261-268. https://doi.org/10.1093/trstmh/trab004

Touloupou, P, Finkenstadt, B, Besser, TE, French, NP & Spencer, SEF 2020, 'Bayesian inference for multi-strain epidemics with application to Escherichia coli O157: H7 in feedlot cattle', Annals of Applied Statistics, vol. 14, no. 4, pp. 1925-1944. https://doi.org/10.1214/20-AOAS1366

Retkute, R, Touloupou, P, Basanez, M-G, Hollingsworth, DT & Spencer, S 2020, 'Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling', Annals of Applied Statistics.

Toor, J, Adams, ER, Aliee, M, Amoah, B, Anderson, RM, Ayabina, D, Bailey, R, Basáñez, M-G, Blok, DJ, Blumberg, S, Borlase, A, Rivera, RC, Castaño, MS, Chitnis, N, Coffeng, LE, Crump, RE, Das, A, Davis, CN, Davis, EL, Deiner, MS, Diggle, PJ, Fronterre, C, Giardina, F, Giorgi, E, Graham, M, Hamley, JID, Huang, C-I, Kura, K, Lietman, TM, Lucas, TCD, Malizia, V, Medley, GF, Meeyai, A, Michael, E, Porco, TC, Prada, JM, Rock, KS, Le Rutte, EA, Smith, ME, Spencer, SEF, Stolk, WA, Touloupou, P, Vasconcelos, A, Vegvari, C, de Vlas, SJ, Walker, M & Hollingsworth, TD 2020, 'Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation', Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa933

Touloupou, P, Finkenstadt, B & Spencer, SEF 2020, 'Scalable Bayesian Inference for Coupled Hidden Markov and Semi-Markov Models', Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2019.1654880

Touloupou, P, Retkute, R, Hollingsworth, TD & Spencer, SEF 2020, 'Statistical methods for linking geostatistical maps and transmission models: application to lymphatic filariasis in East Africa', Spatial and Spatio-temporal Epidemiology, vol. 2020, no. 00, 100391. https://doi.org/10.1016/j.sste.2020.100391

Prada, JM, Davis, EL, Touloupou, P, Stolk, WA, Kontoroupis, P, Smith, ME, Sharma, S, Michael, E, de Vlas, SJ & Hollingsworth, TD 2019, 'Elimination or Resurgence: Modelling Lymphatic Filariasis After Reaching the 1% Microfilaremia Prevalence Threshold', The Journal of Infectious Diseases. https://doi.org/10.1093/infdis/jiz647

Stolk, WA, Prada, JM, Smith, ME, Kontoroupis, P, de Vos, AS, Touloupou, P, Irvine, MA, Brown, P, Subramanian, S, Kloek, M, Michael, E, Hollingsworth, TD & de Vlas, SJ 2018, 'Are Alternative Strategies Required to Accelerate the Global Elimination of Lymphatic Filariasis? Insights From Mathematical Models', Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciy003

Touloupou, P, Alzahrani, N, Neal, P, Spencer, SEF & McKinley, TJ 2018, 'Efficient Model Comparison Techniques for Models Requiring Large Scale Data Augmentation', Bayesian Analysis. https://doi.org/10.1214/17-ba1057

Alzahrani, N, Neal, P, Spencer, SEF, McKinley, TJ & Touloupou, P 2018, 'Model selection for time series of count data', Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2018.01.002

Michael, E, Sharma, S, Smith, ME, Touloupou, P, Giardina, F, Prada, JM, Stolk, WA, Hollingsworth, TD & de Vlas, SJ 2018, 'Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination', PLoS Neglected Tropical Diseases. https://doi.org/10.1371/journal.pntd.0006674

Prada, JM, Touloupou, P, Adriko, M, Tukahebwa, EM, Lamberton , PHL & Hollingsworth, TD 2018, 'Understanding the relationship between egg- and antigen-based diagnostics of Schistosoma mansoni infection pre- and post-treatment in Uganda', Parasites and Vectors. https://doi.org/10.1186/s13071-017-2580-z

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