title: A network model for Ebola spreading.
abstract: The availability of accurate models for the spreading of infectious diseases has opened a new era in management and containment of epidemics. Models are extensively used to plan for and execute vaccination campaigns, to evaluate the risk of international spreadings and the feasibility of travel bans, and to inform prophylaxis campaigns. Even when no specific therapeutical protocol is available, as for the Ebola Virus Disease (EVD), models of epidemic spreading can provide useful insight to steer interventions in the field and to forecast the trend of the epidemic. Here, we propose a novel mathematical model to describe EVD spreading based on activity driven networks (ADNs). Our approach overcomes the simplifying assumption of homogeneous mixing, which is central to most of the mathematically tractable models of EVD spreading. In our ADN-based model, each individual is not bound to contact every other, and its network of contacts varies in time as a function of an activity potential. Our model contemplates the possibility of non-ideal and time-varying intervention policies, which are critical to accurately describe EVD spreading in afflicted countries. The model is calibrated from field data of the 2014 April-to-December spreading in Liberia. We use the model as a predictive tool, to emulate the dynamics of EVD in Liberia and offer a one-year projection, until December 2015. Our predictions agree with the current vision expressed by professionals in the field, who consider EVD in Liberia at its final stage. The model is also used to perform a what-if analysis to assess the efficacy of timely intervention policies. In particular, we show that an earlier application of the same intervention policy would have greatly reduced the number of EVD cases, the duration of the outbreak, and the infrastructures needed for the implementation of the intervention.
authors.affiliation: New York University, Tandon School of Engineering, Department of Mechanical and Aerospace Engineering, Six MetroTech Center, Brooklyn, NY 11201, USA; Politecnico di Torino, Dipartimento di Automatica e Informatica, Corso Duca degli Abruzzi 24, 10129 Torino, Italy. Electronic address: alessandro.rizzo@nyu.edu.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Rizzo
authors.affiliation: TEPHINET (Training Programs in Epidemiology and Public Health Interventions Network) in Cooperative Agreement with the Workforce and Institutions Development Branch at the Center for Global Health of the Centers for Disease Control and Prevention, Atlanta, GA30329, USA. Electronic address: pedalinobiagio@gmail.com.
authors.forename: Biagio
authors.initials: B
authors.lastname: Pedalino
authors.affiliation: New York University, Tandon School of Engineering, Department of Mechanical and Aerospace Engineering, Six MetroTech Center, Brooklyn, NY 11201, USA. Electronic address: mporfiri@nyu.edu.
authors.forename: Maurizio
authors.initials: M
authors.lastname: Porfiri
mesh_terms: D002138:Calibration; D003198:Computer Simulation; D029043:Ebolavirus / Q000502:physiology*; D019142:Hemorrhagic Fever, Ebola / Q000453:epidemiology / Q000635:transmission* / Q000821:virology*; D006760:Hospitalization; D006801:Humans; D007988:Liberia / Q000453:epidemiology; D008954:Models, Biological; D013997:Time Factors
keywords: Activity driven networks; Ebola virus disease; Epidemic model; Interventions; Liberia