Vittoria Colizza and Alain Barrat are the General co-Chairs, helped by a great team of collaborators. The webpage is up, have a look:
We are so proud to announce that Paris will host NetSci2018, the annual School and Conference in Network Science, next year in June!
Vittoria Colizza and Alain Barrat are the General co-Chairs, helped by a great team of collaborators. The webpage is up, have a look:
We just posted on the arxiv our new paper on the computation of the epidemic threshold for continuously time-evolving networks.
Epidemic threshold on continuous vs. discrete time evolving networks
E Valdano, M Re Fiorentin, C Poletto, V Colizza
The complex interplay between spreading dynamics on a network and underlying time-evolving topologies challenges our understanding of these phenomena. Specifically, contacts’ evolution impacts the conditions leading to the wide-spreading regime. In this work we introduce a novel theoretical framework for analytically predicting the epidemic threshold for any temporal network, extending the infection propagator approach (Valdano et al. Phys Rev X 2015) to continuous time evolving patterns. This allows us to go beyond previously used approximations, such as discretization, known to possibly bias results. We also provide an explicit solution applicable to contexts of interest and provide a mathematical formulation to reinterpret the widely used concept of annealing. Our findings offer the first systematic connection between the discrete and continuous formulations of spreading phenomena on arbitrary evolving networks.
Busy two days of presentations, interactions and discussions in Nantes at the international meeting on Modeling of Animal Health. Bryan Iotti (University of Torino, Italy) presented the work on BVD (bovine viral diarrhea) spread in the cattle trade market of Italy that we are doing in collaboration with Mario Giacobini at the Dept. of Veterinary Sciences of the University of Torino and with the Italian Agency of Animal Health.
Eugenio Valdano (Universitat Rovira i Virgili, Spain) gave a talk on cattle trade networks in Europe, our comparative study now involving 12 countries! [Do you want to include your cattle trade network? please contact us!
Vittoria Colizza discussed how the infection propagator approach can be used to assess the endemic risk of Brucellosis in Italy.
This is an Orange-sponsored PhD position on the modeling of the social dimension of disease dynamics based on cell phone data
About the science
The PhD thesis will focus on the identification and study of the social dimension embedded in the dynamics of infectious disease spread through complex dynamical networks generated by high-resolution cell phone data.
Controlling and containing epidemics is an important healthcare priority worldwide, as highlighted by the recent outbreaks of Ebola virus, Zika virus, MERS Coronavirus, and others. Modeling the inherent complexity of disease-spreading processes represents an important field of research aimed at assessing and anticipating the possible implications of an outbreak, and identifying prompt and effective prevention/control strategies. Pathogens spread represents an ever-evolving challenge, requiring continuing efforts at several levels and across a broad range of disciplines. Modern epidemic models recognize the increasing importance of population structure, patterns of interactions and mobility networks, as these can substantially alter the probability of encounters, patterns of exposure, and the likelihood of disease propagation [1-4]. Most importantly, all these factors are often inter-related, with social networks being heavily influenced by geography . While the role of human mobility patterns and contacts in closed settings has been widely addressed in infections transmission [2-4,6-10], also with the use of mobile phone data [11-13], little research has explicitly considered the spatial social dimension of epidemic dynamics [14,15].
Relying on complex networks research, Big Data analytics, and mathematical and computational modeling, the aim of the thesis will be to provide a quantitative description of the aspects of social interactions in space and time that are most relevant to disease transmission, based on the use of high resolution cell phone data. The setting of study will be a region in Africa.
You are a student with a MSc degree (Bac +5 level) in the field of applied mathematics, physics, computational biology, or similar.
You have a background in the following areas of expertise: Big data analysis / mathematical and computational modeling / machine-learning / statistics / complex systems / large-scale networks. You show a strong interest in interdisciplinary research and adaptation to blend into a multidisciplinary team composed by data scientists, infectious disease epidemiologists, modellers, sociologists. You have a demonstrated track record of: (1) manipulating large datasets with advanced machine learning, data mining or big data and complex-network analytics techniques; or (2) developing large-scale mathematical and computational diffusion/contagion processes. Experience in both aspects is highly encouraged.
About the position
You will enter the PhD program of the ED393 Pierre Louis PhD School of Public Health at the Universite Pierre et Marie Curie in Paris, starting the 2017/2018 Academic Year on October 1, 2017. You will be employed by Orange to perform the thesis work in the Orange premises (40-48, avenue de la République 92320 CHATILLON) with a 3-y term contract (30,000 € yearly gross salary).
The subject of the thesis is part of a research program within Orange called 'Digital Society' which seeks to investigate the impact of digital technologies on society as well as to design innovative digital services that meet social expectations through the technologies of the tomorrow’s society. Within this program, a project in particular, ‘Mining social reality with telco data’, aims at extracting from mobile phone data, information useful for individuals’ behavioral analysis and linking it to social phenomena driven by. Based on these data, we infer, for example, clues about social interactions, human mobility and analyse their impact in several research fields such as urban planning (Smart Cities, transport, etc) epidemiology of infectious diseases, education.
You will be supervised by: Dr. Vittoria Colizza, EPIcx lab (Epidemics in complex environments) at Inserm (French National Institute of Health and Medical Research) and Universite Pierre et Marie Curie; Dr. Stefania Rubrichi, SENSE (Sociology and Economics of Networks and Services) lab at Orange XDLab.
You will be able to evolve into an R&D department of a telecommunications operator that will give you access to the original data on high-performance infrastructures, ensuring you a unique data processing experience on this scale. The subject of the thesis, at the crossroads of social sciences and the epidemiology of infectious diseases, also offers a rare opportunity for the development of knowledge as well as associated application in the context of an innovative company.
More information on the position on the Orange website:
How to apply
Please submit your application dossier by email to Dr. Vittoria Colizza (email@example.com) and Dr. Stefania Rubrichi (firstname.lastname@example.org), including:
 Koopman JS and Lynch JW (1996) Emerging Objectives and Methods in Epidemiology. Am J Public Health 86(5)
 Keeling MJ, Rohani P. Modeling Infectious Diseases in Humans and Animals. Princeton: Princeton University Press; 2008.
 Dorjee S, Poljak Z, Revie CW, Bridgland J, McNab B, Leger E, Sanchez J. A review of simulation modelling approaches used for the spread of zoonotic influenza viruses in animal and human populations. Zoonoses Public Health. 2013; 60(6):383–411.
 Wu JT, Cowling BJ. The use of mathematical models to inform influenza pandemic preparedness and response. Exp Biol Med (Maywood). 2011; 236(8):955–61.
 Phithakkitnukoon S, Smoreda Z, Olivier P (2012) Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data. PLoS ONE 7(6): e39253.
 Halloran ME, Ferguson NM, Eubank S, Longini IM, Cummings DAT, Lewis B, Xu S, Fraser C, Vullikanti A, Germann TC, Wagener D, Beckman R, Kadau K, Barrett C, Macken CA, Burke DS, Cooley P. Modeling targeted layered containment of an influenza pandemic in the United States. Proc Natl Acad Sci USA. 2008; 105(12):4639–644.
 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, Furlanello C, Scalia Tomba G, Iannelli M. Mitigation measures for pandemic influenza in italy: An individual based model considering different scenarios. PLoS ONE. 2008; 3(3):e1790.
 Colizza V, Barrat A, Barthélemy M, Vespignani A (2006) The role of the airline transportation network in the prediction and predictability of global epidemics. Proceedings of the National Academy of Sciences of the United States of America, 103(7): 2015-2020
 Bansal S, Grenfell BT, Meyers LA. When individual behaviour matters: homogeneous and network models in epidemiology. J R Soc Interface. 2007; 4(16):879–91.
 Stehlé J, Voirin N, Barrat A, Cattuto C, Colizza V, Isella L, Régis C, Pinton JF, Khanafer N, Van den Broeck W, Vanhems P. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees. BMC Med. 2011; 9:87.
 Wesolowski A, Eagle N, Tatem AJ, Smith DL, Noor AM, et al. (2012) Quantifying the impact of human mobility on malaria. Science 338: 267–270.
 Le Menach A, Tatem AJ, Cohen JM, Hay SI, Randell H, et al. (2011) Travel risk, malaria importation and malaria transmission in Zanzibar. Sci Rep 1: 93
 Tizzoni M, Bajardi P, Decuyper A, Kon Kam King G, Schneider CM, Blondel V, Smoreda Z, Gonzàlez MC, Colizza V. On the Use of Human Mobility Proxies for Modeling Epidemics. PLoS Comput Biol 10(7): e1003716. doi:10.1371/journal.pcbi.1003716
 Toole et al. Coupling human mobility and social ties. J R Soc Interface 12, 20141128 (2015).
 Lima et al. Disease Containment Strategies based on Mobility and Information Dissemination. Sci Rep 5, 10650 (2015).
Accuracy and reliability of mobile phone data to describe people movements for infectious disease spread: new paper
Mobile phone data have recently offered new avenues to quantify human travel patterns with broad applications to epidemiology. But do they provide accurate and reliable descriptions of human movements for epidemic purposes? Through more than 650K simulations applied to France, we showed in a new paper that the adequacy of mobile phone data for infectious disease models becomes higher when epidemics spread between highly connected and heavily populated locations, such as large urban areas: mobile phones are more reliable in central regions than peripheral ones.
Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models
C Panigutti, M Tizzoni, P Bajardi, Z Smoreda, V Colizza
Royal Society Open Science 4, 160950 (2017).
Contagion '17: the call for abstract is open for the CCS2017 satellite on epidemic-related challenges
We co-organize Contagion, a satellite meeting of the Conference on Complex Systems, the major annual international event gathering scientific communities engaged in Complex Systems research. Since 2012, the satellite brings together researchers from a broad range of disciplines (physics, mathematics, biology, epidemiology, human and veterinary medicine, computer science, information technologies, social sciences), focusing on the many challenges that the battle against infectious diseases is still facing in the XXI century.
The sixth edition of Contagion will be held within CCS2017 (Cancun, Mexico, September 17-22, 2017), with a particular attention to topics like vaccination strategies/immunization on networks, interacting strain dynamics, long-lived and persistent diseases, complex contagion, zoonotic spread, temporal transmission networks, human adaptation and multiple transmission routes/multiplex networks.
The workshop will be one day long and will host two invited talks (invited speakers are Marco Ajelli, Northeastern University, USA & Bruno Kessler Foundation, Italy, and Samuel Scarpino, University of Vermont, USA) and 12-15 contributed talks, selected by an international program committee. The call for abstracts is now open: abstracts need to be submitted via EasyChair. The deadline is May 20, 2017.
Contagion '17 – CCS'17 Satellite Meeting. Cancun, Mexico, September 2017.
OK, it's been quite some time we haven't been updating our webpage (>1 year?) - except for the papers. So, here's what happened in the last few months (in random order):
In occasion of the 10th anniversary of the ERC (European research Council), Telethon Farmindustria awards a Research Prize to Vittoria Colizza as the youngest female researcher recipient of an ERC in Italy in the field of Life Sciences. The prize was presented by Dr. Francesca Pasinelli, General Director of Telethon, and by the Italian Ministry of Health, Mrs. Beatrice Lorenzin, in the awesome framework of the Camera di Commercio in Rome. The event was an occasion to promote initiatives to better understand the relation between gender and health.
A postdoctoral position is available at the EPIcx lab within the UMR S 1136 ‘Surveillance and modeling of infectious diseases’ of the INSERM. The candidate is expected to work within the framework of the project FluDE funded by Émergence @ Sorbonne Universités with the aim of jointly analyzing spread and evolution of seasonal influenza with data driven approaches.
We are looking for a strongly motivated person with excellent skills in computational modeling, data collection and analysis, and a keen interest in multidisciplinary research. The candidate should have a PhD (or expect to have one for the starting date) in quantitative science, such as physics, applied mathematics, computer science, epidemiology or any close related discipline. Proven ability to work independently and to quickly adapt to new scientific environments are essential for this position. Good communicative skills to successfully collaborate with the other members of the group, and a good knowledge of both oral and written English are required.
The selected candidate will join the EPIcx lab at INSERM UMR S 1136 in Paris, France and will work in collaboration with Dr. Chiara Poletto. The topics of the work will be marked by the objectives of FluDE, which include the mechanistic modeling of influenza spatial spread and evolution in the French territory through a computational approach. The work will be conducted in collaboration with the Team 1 of UMR S 1136, including the Surveillance Network group within the Team (responsible for GP influenza surveillance in France), and the other partners of the project, including the Team 2 at INSERM 1136 (‘Epidemiology of Influenza and viral hepatitis: risk, prognosis and therapeutic options’), the Institute Pasteur in Paris and the Rega Institute in Leuven. Research tasks will be computational programming (development of data-driven models, agent-based approaches), the analysis and characterization of simulation output and their comparison with empirical data (including incidence and genetic data). Experience with data-intensive computational modeling, agent-based approaches and data analysis is highly desirable.
The position is full-time and fixed-term available for one year in the first instance. Applications will be continuously received and evaluated until the position is filled.
Applications should be submitted to Dr. Chiara Poletto via email (email@example.com) and must include:
• letter of motivation;
• CV including the list of publications;
• up to 3 selected preprints/publications most relevant for this position;
• 2 letters of reference.
We published a new paper on the commonalities and differences in the Chikungunya and Zika transmission. We analysed 18 epidemics caused by the two viruses occurring in 9 distinct island territories. Through a hierarchical TSIR model we showed that population and territory, more than virus, determine variation in the epidemic transmission potential. At the same time, however, the two viruses cause very different level of case detectability, with Zika associated to higher under reporting of cases.
We analysed also the role of weather in transmission, identifying an effect of precipitation. Increased precipitation showed a dual effect, first reducing transmission after a two-week delay, then increasing it around five weeks later.
A comparative analysis of Chikungunya and Zika transmission,
J. Riou, C. Poletto, P.Y. Boëlle
Epidemics in press http://dx.doi.org/10.1016/j.epidem.2017.01.001 (2017)