Modelling to contain pandemics

Center on Social and Economic Dynamics at the Brookings Institution, 1775 Massachusetts Avenue, Washington DC 20036, USA.
Nature (Impact Factor: 41.46). 09/2009; 460(7256):687. DOI: 10.1038/460687a
Source: PubMed


Agent-based computational models can capture irrational behaviour, complex social networks and global scale--all essential in confronting H1N1, says Joshua M. Epstein.

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    • "Many of the worlds current problems can be described as complex [1] [2]. Complexity science and complex systems provide new ways to study many natural phenomena, from protein–protein interactions [3] [4] and the spreading of infectious diseases [5] [6], to social interactions and socio-economics of modern megacities [7] [8], all the way to the human brain itself [9] [10]. A complex behavior can occur in any system that consists of large numbers of components, which interact in a non-linear way [11], such as molecular and cellular systems, organisms, ecosystems and human societies. "
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    ABSTRACT: tComplexity and complex systems are all around us: from molecular and cellular systems in biology upto economics and human societies. There is an urgent need for methods that can capture the multi-scalespatio-temporal characteristics of complex systems. Recent emphasis has centered on two methods inparticular, those being complex networks and agent-based models. In this paper we look at the combi-nation of these two methods and identify “Complex Agent Networks”, as a new emerging computationalparadigm for complex system modeling. We argue that complex agent networks are able to capture bothindividual-level dynamics as well as global-level properties of a complex system, and as such may helpto obtain a better understanding of the fundamentals of such systems.
    Applied Soft Computing 08/2015; 37:311-321. DOI:10.1016/j.asoc.2015.08.010 · 2.81 Impact Factor
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    • "Urban processes have been the subject of many simulation studies in the past. This includes topics that cover diverse aspects of urban life, such as climate science (e.g., urban heat island effect [1]), energy studies (e.g., smart grids [2] or vehicle-to-grid [3]), health (e.g., pandemics [4]), social science (e.g., crowd evacuation [5]), and transportation (e.g., public transport [6] and traffic management [7]) to name only a few. Agent-based models are commonly used for simulating urban processes, such as transportation for example, and are often the only feasible way to study the urban systems of interest. "
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    ABSTRACT: Large-scale urban systems simulations are complex and with a large number of active simulation entities the computational workload is extensive. Workstation computers have only limited capabilities of delivering results for large-scale simulations. This leads to the problem that many researchers and engineers have to either reduce the scope of their experiments or fail to execute as many experiments as they would like in a given time frame. The use of high-performance computing (HPC) infrastructure offers a solution to the problem. Users of such simulations are often domain experts with no or little experience with HPC environments. In addition users do not necessarily have access to an HPC. In this paper we propose an architecture for a cloud-based urban systems simulation platform which specifically aims at making large-scale simulations available to typical users. The proposed architecture also addresses the issue of data confidentiality. In addition we describe the Scalable Electro-Mobility Simulation (SEMSim) Cloud Service that implements the proposed architecture.
    Simulation Modelling Practice and Theory 06/2015; 30. DOI:10.1016/j.simpat.2015.05.005 · 1.38 Impact Factor
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    • "Nunn et al., 2014). For these reasons, ABM within epidemiology has been growing, and applications range from studying dengue fever (Lourenço and Recker, 2013), foot-andmouth (Dion et al., 2011), hepatitis (Ajelli and Merler, 2009), influenza (Rao et al., 2009), malaria (Linard et al., 2008), measles (Perez and Dragicevic, 2009), mumps (Simoes, 2012), smallpox (Epstein et al., 2002), swine flu (H1N1, Epstein, 2009), tuberculoses (Patlolla et al., 2006) etc. Little attention however, has been focused Fig. 1. "
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    ABSTRACT: Cholera is an intestinal disease and is characterized by diarrhea and severe dehydration. While cholera has mainly been eliminated in regions that can provide clean water, adequate hygiene and proper sanitation; it remains a constant threat in many parts of Africa and Asia. Within this paper, we develop an agent-based model that explores the spread of cholera in the Dadaab refugee camp in Kenya. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks within this camp. We model the spread of cholera by explicitly representing the interaction between humans and their environment, and the spread of the epidemic using a Susceptible-Exposed-Infected-Recovered model. Results from the model show that the spread of cholera grows radially from contaminated water sources and seasonal rains can cause the emergence of cholera outbreaks. This modeling effort highlights the potential of agent-based modeling to explore the spread of cholera in a humanitarian context.
    Environmental Modelling and Software 12/2014; 62:164–177. DOI:10.1016/j.envsoft.2014.08.027 · 4.42 Impact Factor
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