Interacting Dynamics on Networks, Applications to Epidemiology (idonate)

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Syndemic diseases are not new phenomena, for example the influenza pandemic of 1918 (Spanish flu) killed 20-40 million people mostly by bacterial co-infections. Generally pathogens that spread and proliferate on networks (e.g. contact networks between individuals in single populations or networks of populations that are coupled by means of transportation) interact, coexist and coevolve. These interactions are either cooperative or competitive and can effectively change the way syndemic diseases spread and proliferate in populations. Different pathogens may either facilitate the dynamics of other pathogens or inhibit them with different magnitudes. Thalassemia, a form of inherited autosomal recessive blood disorders, is an example of the latter case, inducing a degree of protection against malaria. Despite this, emergent infectious diseases are typically analyzed as single, autonomous agents. Interacting contagion processes, their dynamical features, characteristics and consequences are still poorly understood. Fundamental questions are still open. For instance: How does cooperation/competition change fundamental dynamic properties, threshold dynamics, phase transitions and other properties that characterize global contagion dynamics? What are potential evolutionary processes that select pathogens when they are under competitive stress or benefit from cooperative mechanisms? How does the combination of different rate parameters, cooperative or competitive mechanism change the behavior of the system? In summary, we lack an understanding of coinfection dynamics and syndemic diseases at a fundamental level. The goal of the project is to develop co-epidemic concepts that yield a comprehensive understanding of the evolution of interacting contagion processes on complex networks. Our preliminary works suggests the existence of unexpected outbreaks when cooperation between two diseases plays a role. In this project we will develop a theoretical framework and a computational infrastructure in order to address four essential aspects of syndemics: 1) competition 2) cooperation 3) ecology 4) evolution processes of interacting pathogens on complex networks.