Lorenzo Pellis

Lorenzo Pellis


Personal profile

Research interests

I use mathematical models to describe how infectious diseases spread in (typically human) populations and how pathogens evolve, for example in the case of emerging of resistance to drugs. Although I have worked also on spread of infection on networks, the areas of main interest to me at present involve infections in the context of:

  • Populations with a social structure (e.g. age classes, households, schools, etc.)
  • Multiscale models (i.e. within-host dynamics and between-host transmission)
  • Statistical methods for parameter estimation

The model construction process per se is already a third of the journey. The second third is the analysis of the model, and I try to work at the boundary between models that are analytically tractable and models that need to be studied via large stochastic simulations. Because my work is driven by a biologically relevant question, I typically use any mathematical tool that turns out to be useful for the problem, but most commonly:

  • Ordinary differential equations (ODEs)
  • Integral equations
  • Stochastic processes
  • Individual-based stochastic simulations

The third part of the journey is to estimate model parameters, so more recently I am developing a growing interest in Bayesian statistics, and more general in data science.

In such an interdisciplinary field, a surprising amount of time is spent clarifying poorly defined concepts. I am particularly interested in comparing the behaviour of a range of different models and the assumptions on which they rely, in order to ensure as much as possible that the model predictions do actually reflect the system at hand, rather than being an artefact of the particular mathematical representation used. 


I work in the Applied Mathematics group of the School of Mathematics. My research interests are in the area of mathematical models for infectious disease dynamics, which include both mathematics and statistics. My current fellowship focuses on developing multi-scale methods to study the epidemiological and evolutionary consequences of co-infection (e.g. when two different pathogens, or variants of the same pathogen, interact within the host).


After a 4-year degree in Mathematics from the Università di Trieste (Italy), I moved to London, for a PhD and postdoc at Imperial College (2005-2012). After another postdoc at the University of Warwick (2012-2017), I was awarded a Sir Henry Dale Fellowship, which I’m now continuing at the University of Manchester.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 4 - Quality Education
  • SDG 13 - Climate Action
  • SDG 15 - Life on Land

Education/Academic qualification

Doctor of Philosophy, Epidemic models in socially structure populations, Department of Infectious Disease Epidemiology, Imperial College London

External positions

Joint Chief Data Science Advisor, Uk Health Security Agency

8 Nov 2021 → …

Visiting Fellow, The University of Warwick

Aug 2017 → …

Visiting Fellow, The University of Warwick

Aug 2017 → …

Honorary Research Associate, Department of Infectious Disease Epidemiology, Imperial College London

Mar 2012 → …

Research Beacons, Institutes and Platforms

  • Digital Futures
  • Healthier Futures


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