Imperial College London

DrLorenzoPellis

Faculty of MedicineSchool of Public Health

Honorary Research Associate
 
 
 
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Contact

 

+44 (0)20 7594 3631l.pellis05

 
 
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Location

 

LG37Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

16 results found

Pellis L, House T, Keeling MJ, 2015, Exact and approximate moment closures for non-Markovian network epidemics, Journal of Theoretical Biology, Vol: 382, Pages: 160-177, ISSN: 0022-5193

Journal article

Pellis L, Spencer SEF, House T, 2015, Real-time growth rate for general stochastic SIR epidemics on unclustered networks, Mathematical Biosciences, Vol: 265, Pages: 65-81, ISSN: 0025-5564

Networks have become an important tool for infectious disease epidemiology. Most previous theoretical studies of transmission network models have either considered simple Markovian dynamics at the individual level, or have focused on the invasion threshold and final outcome of the epidemic. Here, we provide a general theory for early real-time behaviour of epidemics on large configuration model networks (i.e. static and locally unclustered), in particular focusing on the computation of the Malthusian parameter that describes the early exponential epidemic growth. Analytical, numerical and Monte-Carlo methods under a wide variety of Markovian and non-Markovian assumptions about the infectivity profile are presented. Numerous examples provide explicit quantification of the impact of the network structure on the temporal dynamics of the spread of infection and provide a benchmark for validating results of large scale simulations.

Journal article

Heesterbeek H, Anderson RM, Andreasen V, Bansal S, De Angelis D, Dye C, Eames KTD, Edmunds WJ, Frost SDW, Funk S, Hollingsworth TD, House T, Isham V, Klepac P, Lessler J, Lloyd-Smith JO, Metcalf CJE, Mollison D, Pellis L, Pulliam JRC, Roberts MG, Viboud Cet al., 2015, Modeling infectious disease dynamics in the complex landscape of global health, SCIENCE, Vol: 347, Pages: 1216-U29, ISSN: 0036-8075

Journal article

Ball F, Britton T, House T, Isham V, Mollison D, Pellis L, Scalia Tomba Get al., 2015, Seven challenges for metapopulation models of epidemics, including households models, Epidemics, Vol: 10, Pages: 63-67, ISSN: 1755-4365

Journal article

Pellis L, Ball F, Bansal S, Eames K, House T, Isham V, Trapman Pet al., 2015, Eight challenges for network epidemic models, Epidemics, Vol: 10, Pages: 58-62, ISSN: 1755-4365

Journal article

Roberts M, Andreasen V, Lloyd A, Pellis Let al., 2015, Nine challenges for deterministic epidemic models, Epidemics, Vol: 10, Pages: 49-53, ISSN: 1755-4365

Journal article

Gog JR, Pellis L, Wood JLN, McLean AR, Arinaminpathy N, Lloyd-Smith JOet al., 2014, Seven challenges in modeling pathogen dynamics within-host and across scales, Epidemics, Vol: 10, Pages: 45-48, ISSN: 1878-0067

The population dynamics of infectious disease is a mature field in terms of theory and to some extent, application. However for microparasites, the theory and application of models of the dynamics within a single infected host is still an open field. Further, connecting across the scales – from cellular to host level, to population level – has potential to vastly improve our understanding of pathogen dynamics and evolution. Here, we highlight seven challenges in the following areas: transmission bottlenecks, heterogeneity within host, dynamic fitness landscapes within hosts, making use of next-generation sequencing data, capturing superinfection and when and how to model more than two scales.

Journal article

Lythgoe KA, Pellis L, Fraser C, 2013, IS HIV SHORT-SIGHTED? INSIGHTS FROM A MULTISTRAIN NESTED MODEL, EVOLUTION, Vol: 67, Pages: 2769-2782, ISSN: 0014-3820

Journal article

Pautasso M, Doering TF, Garbelotto M, Pellis L, Jeger MJet al., 2012, Impacts of climate change on plant diseases-opinions and trends, EUROPEAN JOURNAL OF PLANT PATHOLOGY, Vol: 133, Pages: 295-313, ISSN: 0929-1873

Journal article

Pellis L, Ball F, Trapman P, 2012, Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R-0, MATHEMATICAL BIOSCIENCES, Vol: 235, Pages: 85-97, ISSN: 0025-5564

Journal article

Shirreff G, Pellis L, Laeyendecker O, Fraser Cet al., 2011, Transmission Selects for HIV-1 Strains of Intermediate Virulence: A Modelling Approach, PLOS COMPUTATIONAL BIOLOGY, Vol: 7, ISSN: 1553-734X

Journal article

Pellis L, Ferguson NM, Fraser C, 2011, Epidemic growth rate and household reproduction number in communities of households, schools and workplaces, JOURNAL OF MATHEMATICAL BIOLOGY, Vol: 63, Pages: 691-734, ISSN: 0303-6812

Journal article

Pautasso M, Xu X, Jeger MJ, Harwood TD, Moslonka-Lefebvre M, Pellis Let al., 2010, Disease spread in small-size directed trade networks: the role of hierarchical categories, Journal of Applied Ecology, Vol: 47, Pages: 1300-1309, ISSN: 1365-2664

Summary 1. Small-size, directed networks are relevant for many biological applications, from meta-populations to food webs, from transport flows to evolutionary trees, from epidemics within households to outbreaks of emerging plant pathogens (e.g. Phytophthora ramorum). However, little attention has been paid to dynamic processes in these networks.2. In the horticultural trade, structural change in hierarchical categories, i.e. the proportion of producers, wholesalers and retailers, can influence the likelihood that plant epidemics will take place in such systems, but it is unclear how.3. We model disease spread and establishment in directed networks of 100 nodes at four connectance levels in six network structures [local, small-world, random, and scale-free (SF) networks with positive, no, and negative correlation between in- and out-degree (number of incoming and outgoing links)], and study the role of hierarchical categories.4. For non-SF networks, the correlation coefficient between number of incoming and outgoing links is negatively correlated with the proportion of producers and retailers, and positively correlated with the proportion of wholesalers. Given the previously reported negative correlation between the in–out degree correlation coefficient and the epidemic threshold, adding producers/retailers and removing wholesalers can contribute to making epidemics more difficult in non-SF networks. For SF networks these associations are not generally present, as in these structures epidemic development is driven by the presence of hubs, rather than the features of the majority of the nodes.5. Synthesis and applications. despite the importance of trade movements of plants for plant epidemics and the emergence of new plant pathogens, little is known about the current contact structure of horticultural networks within and among nations, and about how this is changing. Such information is important for risk assessment and management in plant health regulation.

Journal article

Pellis L, Ferguson NM, Fraser C, 2009, Threshold parameters for a model of epidemic spread among households and workplaces, Journal of The Royal Society Interface, Vol: 6, Pages: 979-987

The basic reproduction number is one of the most important concepts in modern infectious disease epidemiology. However, for more realistic and more complex models than those assuming homogeneous mixing in the population, other threshold quantities can be defined that are sometimes more useful and easily derived in terms of model parameters. In this paper, we present a model for the spread of a permanently immunizing infection in a population socially structured into households and workplaces/schools, and we propose and discuss a new household-to-household reproduction number for it. We show how overcomes some of the limitations of a previously proposed threshold parameter, and we highlight its relationship with the effort required to control an epidemic when interventions are targeted at randomly selected households.

Journal article

Pellis L, 2009, Mathematical Models for Emerging Infections in Socially Structured Populations: The Presence of Households and Workplaces

This thesis is concerned with the description and analysis of a stochastic model for the spread of a directly transmissible infection, leading to permanent immunity af- ter recovery, in a fully susceptible population with a social structure characterised by the presence of households and workplaces. The model considered is highly ide- alised, but contains the key factors affecting the spread of a directly transmissible infection, namely those environments where frequent and intense contacts are most likely. Important analytical insights include the definition of a novel household re- production number RH, representing the average number of households infected by a single household, which is shown to overcome some of the limitations of a previously defined reproduction number and the development of a methodology for the approximate computation of the real-time growth rate, which is then used for the estimation of RH from the real-time growth rate. An efficient stochastic simulator is described and is used to gain understand- ing of the role that local saturation effects within workplaces play in shaping the epidemic spread and to investigate the reliability of estimates of R0 and the average epidemic final size from the real-time growth rate when the presence of the social structure is neglected. The methodologies are applied to the case of pandemic influenza: its rela- tively low infectiousness suggests that estimation of these key epidemiological quan- tities is surprisingly accurate when the social structure is neglected and that the additional presence of spatial constraints implying geographically localised trans- mission has negligible effect on the overall epidemic dynamics. Despite the lack of reliable data concerning workplaces, a realistic range of possible values for RH is identified, but the efficacy of school closure in reducing transmission appears to be difficult to quantify because of the unknown impact it has on transmission in other workplace enviro

Thesis dissertation

Pellis L, Ferguson NM, Fraser C, 2008, The relationship between real-time and discrete-generation models of epidemic spread, Mathematical Biosciences, Vol: 216, Pages: 63-70, ISSN: 0025-5564

Journal article

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