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Dr Lorenzo Pellis Visiting Fellow (currently, Sir Henry Dale Fellow in Manchester) Office: 348b, Zeeman Institute, Senate House Phone: 糖心TV: +44 (0)24 765 73360 Manchester: +44 (0)161 275 5884 Email: 糖心TV: l.pellis@warwick.ac.uk Manchester: lorenzo.pellis@manchester.ac.uk

 

Research Interests:

I am a mathematical modeller in infectious disease epidemiology. I have recently moved to the University of Manchester, in the at the s. In 糖心TV I worked with and in the Zeeman Institute and the Mathematics Institute, where I still have a Visiting Fellowship position.

I am also an Honorary Research Associate in the Medical Research Council (MRC) , within the Department of , Imperial College London.

Research

My research focuses on the development of novel deterministic and stochastic techniques to follow, approximate and summarise the dynamics of infection spread. I mostly focus on directly transmissible human infections, and on the heterogeneity imposed on the spread by the complexity of the human social structure. I am currently a Sir Henry Dale Fellow, working on developing methods to understand the epidemiological and evolutionary consequences of co-infection (i.e. when two or more pathogens, or variants of the same pathogen, are present simultanously within the host) using multi-scale models that include both within-host dynamics and between-host transmission.

Methods

I am interested in any modelling approach that can lead to better insight and practically useful applications, including integral equations, branching processes, network models, moment-closure techniques, MCMC methods for parameter estimation and individual-based stochastic simulations. I am trying to bridge the gap between 鈥渦nrealistic but tractable鈥� and 鈥渃omplex and intractable鈥� approaches.

Applications

Current work on multi-scale models with both within-host and between-host dynamics has important applications for understanding the spread of antimicrobial resistance, the dynamics of multi-strain infections and systems of co-circulating pathogens (e.g. HIV and TB). Other work in progress focuses on human respiratory syncytial virus (RSV) transmission in Kenya, as part of a coordinated by , as well as on improving methods for approximating epidemic dynamics on networks. Previous research has focused on determining the importance of school closure in mitigating influenza pandemics and quantifying the relative contribution of household and age stratification on epidemic spread. I have a strong interest in the problem of models comparison, with the purpose of investigating when simple models, in addition to being key tools to gain understanding of the determinants of system dynamics, can inform health care decision-making processes, and when instead they are over-simplistic, fail to capture some essential system features and lead to inaccurate predictions.

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Selected publications:

(see for a full list)

Submitted:

Chapman, L. A. C., Jewell, C. P., Spencer, S. E. F., Pellis, L., Datta, S., Chowdhury, R., Bern, C., Medley, G. F. & Hollingsworth, T. D., 鈥淭he role of case proximity in transmission of visceral leishmaniasis in a highly endemic village in Bangladesh鈥�.

Pellis, L., Cauchemez, S., Ferguson, N.M., Fraser, C., 鈥淪ystematic model selection for emerging epidemic predictions: the relative importance of age and household structure鈥�.

2016:

Keeling, M. J., House, T. A., Cooper, A. J. & Pellis, L. (2017). . PLOS Computational Biology 12(12): e1005296

Lythgoe, K. A., Blanquart, F., Pellis, L., & Fraser, C. (2016). . PLOS Biology, 14(10), e1002567.

Kinyanjui, T. M., Pellis, L., & House, T. (2016). . Epidemics, 16, 17–26.

Ball, F., Pellis, L., & Trapman, P. (2016). . Mathematical Biosciences, 274, 108–139. ()

2015:

Pellis, L., House, T., & Keeling, M. J. (2015). . Journal of Theoretical Biology, 382, 160–177. ()

Pellis L, Spencer S, House T (2015). , Mathematical Biosciences 265: 65-81. ()

Ball FG, Britton T, House T, Isham V, Mollison D, Pellis L, Scalia-Tomba G (2015). , Epidemics 10: 63-67.

Pellis L, Ball FG, Bansal S, Eames K, House T, Isham V, Trapman P (2015). , Epidemics 10: 58-62.

Roberts M, Andreasen V, Lloyd A, Pellis L (2015). , Epidemics 10: 49-53.

Gog JR, Pellis L, Wood JLN, McLean AR, Arinaminpathy N, Lloyd-Smith JO (2015). , Epidemics 10: 45-48.

Heesterbeek H et al (2015). , Science.

2013:

Lythgoe K*, Pellis L*, Fraser C (2013). , Evolution 67(10): 2769–2782. *Equal contribution

2012:

Pautasso M, D枚ring TF, Garbelotto M, Pellis L, Jeger MJ (2012). , European Journal of Plant Pathology 133(1): 295-313.

Pellis L, Ball FG, Trapman P (2012). , Mathematical Biosciences 235: 85–97.

2011:

Shirreff G, Pellis L, Laeyendecker O, Fraser C (2011). , Plos Comput Biol 7(10): e1002185.

2010:

Pellis L, Ferguson NM and Fraser C (2010). , Journal of Mathematical Biology 63(4): 691-734.

Pautasso M, Xu XM, Jeger MJ, Harwood TD, Moslonka-Lefebvre M, Pellis L (2010). , Journal of Applied Ecology 47(6): 1300-1309.

2009:

Pellis L (2009). , Doctoral dissertation, Imperial College London.

Pellis L, Ferguson NM and Fraser C (2009). , Journal of the Royal Society Interface 6: 979-987.

2008:

Pellis L, Ferguson NM and Fraser C (2008). , Mathematical Biosciences 216(1): 63-70.