Contagion & Networks

Progress and Issues with Models and Data
Satellite symposium, second edition @ NetSci2018
June 11 2018, Paris, France

Contagion & Networks

Satellite symposium, second edition @ NetSci2018
June 11 2018, Paris, France

Progress and issues with epidemiological models and data

The dynamics of contagion (e.g., the spread of ideas and diseases between individuals) are shaped by the networked structure of host populations. Whether the contagion travels quickly through an effectively static network or moves more slowly and thus encounters spatiotemporal variation in the networked structure itself, as a field, we still lack a definitive framework for translating data into predictions of contagion dynamics. The basic model for contagion spreading on a network is simple: An infectious agent, e.g., a pathogen or an idea, is transmitted from "infectious" individuals to "susceptible" individuals through nearest-neighbor interactions on a contact network. However, some of the most basic assumptions surrounding this simple model have been challenged in recent years. The focus of our satellite will be on these recent challenges and on persistent issues in modeling the dynamics of contagion on networks:

  1. 1. It is unclear whether macroscopic invasions emerge continuously or discontinuously as contagion transmissibility increases;
    • a) threshold levels of transmission or social reinforcement leads to discontinuous transitions [1];
    • b) interacting epidemics can emerge continuously or discontinuously [2,3];
    • c) adaptive social networks can also cause the discontinuous emergence of contagions [4].

  2. 2. Only recently did we start developing robust models for epidemics on temporal networks, and we have yet to reach a consensus on the correct mathematical approach [5].

  3. 3. Interventions and network properties designed to hinder contagions can actually hasten their spread:
    • a) network clustering slows down simple diseases in isolation but can accelerate synergistic epidemics [6];
    • b) replacing sick workers can also cause a disease spread to be super-exponential [4].

  4. 4. Zika virus highlights the importance of asymmetric transmission and of mixed routes of transmission (i.e., through a mosquito vector and through sex), and the consequences of which are not fully understood [7,8].

  5. 5. No model has yet to produce actionable predictions implementing the interaction of human behavior and contagions.
Additionally, the complex network methodology has been shown useful to shed new lights on long-standing healthrelated challenges, for example:

  1. 6. Ecology of poverty, explaining how network effects play an important role in shaping poverty and population health [9].

  2. 7. Network Medicine, which is the application of network theory to the diagnosis, prevention and treatment of diseases based on biological networks [10].
Combined, these recent advances and new applications illustrate how quickly the field is developing and how many challenging scientific questions still exist. Despite new models being continually published, there has been little consensus or synthesis about the correct tools and their practical role in supporting public health decision making. We invite the researchers of all backgrounds to contribute to this satellite and thus to engage in interdisciplinary discussions on the status and future of this rapidly diversifying and expanding field.

Related satellites

Three other epidemiology-related satellite symposia are held at NetSci2018. Their themes are complementary to the ones covered at Contagion & Networks and there is no schedule overlap.

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Important dates

March 15, 2018: Satellite abstract submission deadline
April 1, 2018: Acceptance notifications
April 10, 2018: NetSci early registration deadline
June 11, 2018: Satellite symposium

Invited speakers

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Lisa Sattenspiel

University of Missouri

What can we learn from history? Using network formulations to model the spread of historic infectious disease epidemics

The vast majority of network models in epidemiology focus on diseases and epidemics in the contemporary world. There is much we can learn from modeling epidemics of the past, however. In this talk, I use examples from research on the 1918 influenza pandemic to illustrate the insights we can gain from looking at the past. This pandemic occurred at a time when vaccines and antibiotics were not available and when the ultimate cause of the disease was not known. Examination of the consequences of this pandemic provides a window into what might happen in the near future if antibiotic resistance and other modern problems become much worse. Discussion centers on the nature of the models I have used, the ways that I have modeled social networks and past communities, the sources and types of data available to ground the models in the reality of the early 20th century, and the implications of model results for dealing with future pandemics.

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Joel C. Miller

Institute for Disease Modeling

Contagion spread in clustered and unclustered small world networks

Small-world networks have been widely used as a model for social networks. The typical definition of a small-world network is based on the observation that as long-range connections are added to a ring or a lattice, a regime occurs in which the typical (path) distance between two nodes is small while the typical clustering coefficient is still quite large. This has important implications for the behavior of dynamic processes occurring on the networks. In this talk, we discuss an alternative perspective on small-world networks, and explore a class of small-world networks that have negligible clustering (in the large network limit). We show that dynamic processes on these networks retain many of the features they have on small-world networks. In doing so we push the suggestion that the concept of "small-worlds" has less to do with local clustering than nearness of neighbor.

Call for abstracts


We invite abstracts of new and/or recently published work for contributed talks to take place at the satellite symposium. We hope for a broad range of topics to be covered, across theory, methodology, and application to empirical data. Topics of special interest, as they relate to contagion, include:

  • –Interacting contagions
  • –Temporal networks
  • –Novel physics of spreading
  • –Multiplex networks
  • –Memes
  • –Emerging infectious diseases
  • –Prediction
  • –Behavior
  • –Data collection
The deadline for abstract submission is March 15, 2018, and acceptance notifications will be sent April 1st, 2018.

All participants are required to be registred at the main conference. Abstract submission will be handled by EasyChair and is free of charge. There is no word limit on abstracts but please limit their length to one page, including title, authors, equations, figure(s), etc. All abstracts will be considered for contributed and lightning talks (please indicate if you have a preference); there will be no posters.

Registration Submit an abstract


Time Authors Title
08:45 Organizers Opening remarks
09:00 Michele Tizzoni, André Panisson, Daniela Paolotti and Ciro Cattuto Media coverage and public awareness in the United States during the 2016 Zika epidemic
09:20 Petter Holme Optimizing sentinel surveillance in static and temporal networks
09:40 Joana Gonçalves-Sá and Cláudio Vieira The contagiousness of non-infectious disease: using influenza to study anxiety
10:00 Lisa Sattenspiel What can we learn from history? Using network formulations to model the spread of historic infectious disease epidemics
— Coffee break (approx. 30 min.) —
11:15 Joel C. Miller Contagion spread in clustered and unclustered small world networks
12:00 Tiago Peixoto and Laetitia Gauvin Change points, memory and epidemic spreading in temporal networks
12:20 Sang-Hwan Gwak, Eun-Kyu Park and Kwang-Il Goh Hidden impact of quarantine under outbreak : No-exclaves percolation on networks
12:25 Rashad Eletreby, Yong Zhuang and Osman Yagan Evolution of Spreading Processes on Complex Networks
12:30 Laura Ozella, Francesco Gesualdo, Michele Tizzoni, Caterina Rizzo, Elisabetta Pandolfi, Ilaria Campagna, Alberto Eugenio Tozzi and Ciro Cattuto Close encounters between infants and household members measured through wearable proximity sensors
12:35 Ceyhun Eksin and Joshua S. Weitz Surveillance and control in networked SIS dynamics with individual response
12:40 Igor Kanovsky Diffusion in Social Networks: Between Contagion and Complex Contagion
12:45 David Haw, Rachael Pung and Steven Riley Topological drivers of sub-exponential growth in early disease dynamics
12:50 Samuel Rosenblatt Making the Most of the Network Data We Have: Effective Targeted Immunization Using Incomplete Network Data
12:55 Organizers Closing remarks


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Antoine Allard

Universitat de Barcelona

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Benjamin M. Althouse

Institute for Disease Modeling

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Laurent Hébert-Dufresne

University of Vermont

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Samuel V. Scarpino

Network Science Institute