Collective Dynamics

Research Interests

Collective dynamics is an integrating component of natural systems, fundamental to all sciences, from physics to biology and sociology. We seek any unifying principles underlying the forms of self-organization in large populations of interacting elements. Our approach combines theoretical and experimental systems.

Group Members

Research Project

Exploring pathogen diversity in disease epidemiology and vaccine research

Viruses, bacteria and parasitic pathogens have evolved multiple strategies to evade innate and acquired immune responses, facilitating transmission, permitting the establishment of persistent and recurrent infections, and often hampering the development of effective vaccines. Antigenic variation of immune response targets is one such pathogen strategy that can only be confronted with the support of a highly specialised research programme combining basic and applied research. This is the theme of this project. The proposed team integrates basic research in infection, population genetics, and mathematical epidemiology, with a range of practical aspects of experimental design from the laboratory to the field.
The overall research strategy is to unravel the molecular bases and epidemiological significance of immunity in order to guide vaccine design and deployment. For this it is necessary to consider antigenic diversity at varying levels of resolution. In some pathogens, antigenic diversity follows a discrete multi-type structure (dengue viruses and pneumococcal bacteria), as compared to others where genetic diversity is so vast that any type of organization is very difficult do discern (malaria parasites). As causative agents of major human diseases for which antigenic variability is critical, we will study selected pathogens in depth, such as: dengue, pneumococcus and malaria parasites. From these case studies, we will develop comparisons and generalise trends and methodologies. Mathematical models will be developed to:
1. Formulate hypotheses on evolutionary processes of the pathogen in connection with disease epidemiology.
2. Explore the epidemiological and evolutionary consequences of existing and potential vaccines.
3. Determine the practical implications of this research for vaccine design.

Funding

Fundação para a Ciência e a Tecnologia, Portugal

Collaborators

IGC Disease Genetics, Carlos Penha-Gonçalves
IGC Population and Conservation Genetics, Lounes Chikhi
Instituto de Tecnologia Química e Biológica, UNL, Raquel Sá-Leão
Instituto Superior de Economia e Gestão, UTL, Diogo Pinheiro
Centro de Matemática e Aplicações Fundamentais, UL, Jaime Combadão
Fundação Oswaldo Cruz, Brazil, Cláudia Codeço

Research Project

Molecular epidemiology of Mycobacterium tuberculosis in Portugal

We propose to genotype all the strains from sputum of smear positive pulmonary tuberculosis cases with recent methods based on the variability of mycobacterial interspersed repetitive units (MIRU) and variable number tandem repeats (VNTR). A database that includes mycobaterial genotype and clinical and demographic information about patients will be implemented, constituting a valuable resource for molecular epidemiology studies, transmission models and applied research on mycobacterial evolution and pathogenesis.

Funding

Fundação para a Ciência e a Tecnologia, Portugal

Collaborators

IGC BioInformatics Unit, José Pereira-Leal
IGC Genomics Unit, Carlos Penha-Gonçalves
Direcção-Geral da Saúde, António Fonseca Antunes
Instituto Nacional de Saúde Dr Ricardo Jorge, Anabela Miranda

Research Project

Developing the framework for an epidemic forecast infrastructure (Epiwork)

In recent years a huge flow of quantitative social, demographic and behavioural data is becoming available, spurring the quest for innovative technologies that can improve the traditional disease-surveillance systems, providing faster and better localized detection capabilities and resulting in a broad practical impact. Improved ICT techniques and methodologies support the inter-linkage and integration of datasets causing a qualitative change in the ways we can model epidemic processes. The EPIWORK project proposes a multidisciplinary research effort aimed at developing the appropriate framework of tools and knowledge needed for the design of epidemic forecast infrastructures. The research considers most of the much needed development of modeling, computational and ICT tools such as i) the foundation and development of the mathematical and computational methods needed to achieve prediction and predictability of disease spreading; ii) the development of large scale, data driven computational models endowed with a high level of realism and aimed at epidemic scenario forecast; iii) the design and implementation of original data-collection schemes motivated by identified modeling needs; v) the set up of a computational platform for epidemic research and data sharing that will generate important synergies between research communities and countries.

Funding

European Commission Framework Programme 7, Large-scale Integrating Project

Collaborators

IGC Science Communication and Outreach, Ana Godinho
Institute for Scientific Interchange, Italy, Alessandro Vespignani
Tel Aviv University, Israel, Lewi Stone
Max Planck Institute Gottingen, Germany, Dirk Brockmann
Grote Griepmeting.nl, Netherlands, Ronald Smallenburg
London School of Hygiene and Tropical Medicine, UK, John Edmunds
Swedish Institute for Infectious Disease Control, Sweeden, Olof Nyrén
Katholieke Universiteit Leuven, Rega Instituut for Medical Research, Belgium, Marc Van Ranst
Bar Ilan University, Israel, Shlomo Havlin
Fondazione Bruno Kessler, Italy, Stefano Merler
Center for Research and Telecommunication Experimentation for NETworked communities, Italy, Daniele Miorandi
Faculdade de Ciências, University de Lisboa, Portugal, Mário Silva

Publications

(selected) Updated Outubro (2009).

Águas R, Lourenço JML, Gomes MGM, White LJ (2009). The impact of IPTi and IPTc interventions on malaria clinical burden – in silico perspectives PLoS ONE 4 :e6627

Coelho F, Codeço C (2009). Dynamic Modeling of Vaccinating Behavior as a Function of Individual Beliefs PLoS Comp Biol 5 :e1000425

Maude RJ, Pontavornpinyo W, Saralamba S, Aguas R, Yeung S, Dondorp AM, Day NP, White NJ, White LJ (2009). The last man standing is the most resistant: eliminating artemisinin-resistant malaria in Cambodia Malar J. 8 :31

Bacaër N, Gomes MGM (2009). On the final size of epidemics with seasonality Bull Math Biol In press

Gordo I, Gomes MGM, Reis DG, Campos PRA (2009). Genetic variation in the SIR model of pathogen evolution PLoS ONE 4 :e4876

Rodrigues P, Margheri A, Rebelo C, Gomes MGM (2009). Heterogeneity in susceptibility to infection induces unexpectedly high reinfection rates J Theor Biol 259 :280-290

Mantilla-Beniers NB, Gomes MGM (2009). Mycobacterial ecology as a modulator of tuberculosis vaccine success Theor Popul Biol 75 :142-52

Parker MJ, Gomes MGM, Stewart IN (2008). Examples of forced symmetry-breaking to homoclinic cycles in three-dimensional Euclidean-invariant systems International Journal of Bifurcation and Chaos 18 :83-107

Parker MJ, Stewart IN, Gomes MGM (2008). Partial classification of heteroclinic behaviour associated with the perturbation of hexagonal planforms Dynamical Systems – An International Journal 23 :137-162

Águas R., White LJ., Snow RW., Gomes MGM. (2008). Prospects for malaria eradication in sub-Saharan Africa PLoS ONE 3(3) :e1767 Link

Rodrigues P, Gomes MGM, Rebelo, C (2007). Drug resistance in tuberculosis: A reinfection model Theor Popul Biol 71 :196-212

White LJ, Mandl JN, Gomes MGM, Bodley-Tickell AT, Cane PA, Perez P, Siqueira MM, Portes SA, Straliotto SM, Waris M, Medley GF, Nokes DJ (2007). Understanding the transmission dynamics of RSV: Multiple time series and nested models. Math Biosci 209 :222-239

Gomes M.G.M., Rodrigues P, Hilker FM, Mantilla-Beniers NB, Muehlen M, Paulo AC, Medley GF (2007). Implications of partial immunity on the prospects for tuberculosis control by post-exposure interventions J. Theor. Biol. 248 :608-617

van Noort SP, Lourenço J, Rebelo de Andrade H, Muehlen M, Gomes M.G.M. (2007). Gripenet: an internet-based system to monitor influenza-like illness uniformly across Europe Eurosurveillance Monthly 12 :7-8

Gökaydin D, Oliveira-Martins JB, Gordo I, Gomes M.G.M. (2007). Reinfection thresholds regulate pathogen diversity: The case of influenza R. S. Soc. Interface 4 :137-42

Parker MJ, Gomes MGM, Stewart IN (2006). Forced symmetry-breaking of square lattice planforms. Journal of Dynamics and Differential Equations 18 :223-255

Nunes A, Telo da Gama MM, Gomes MGM (2006). Localised contacts between hosts reduce pathogen diversity Journal of Theoretical Biology 241 :477-487

Águas R, Gonçalves G, Gomes M.G.M. (2006). Pertussis: Increasing disease as a consequence of reducing transmission Lancet Infectious Diseases 6 :112-117

Gomes MGM, White LJ and Medley GF (2005). The Reinfection Threshold J. Theor. Biol 133 :561-569

Gomes M.G.M, Margheri A, Medley GF, Rebelo C. (2005). Dynamical behaviour of epidemiological models with suboptimal immunity and nonlinear incidence J. Math. Biol 51 :414-430

Gomes M.G.M., Franco A.O., Gomes M.C. & Medley G.F. (2004). The reinfection threshold promotes variability in tuberculosis epidemiology and vaccine efficacy. Proc. R. Soc. Lond. B 271 :617-623

Gomes M.G.M., White L.J., & Medley G.F. (2004). Infection, reinfection, and vaccination under suboptimal immune protection. J. Theor. Biol. 228 :539-549

Gomes M.G.M., Medley G.F. & Nokes D.J. (2002). On the Determinants of Population Structure in Antigenically Diverse Pathogens. Proc. R. Soc. Lond. B. 269 :227-233