Development of an Individual-Based Model for Polioviruses: Implications of the Selection of Network Type and Outcome Metrics
by Hazhir R. Rahmandad, Kun Hu, Radboud J. Duintjer Tebbens, and Kimberly M. Thompson, Epidemiology and Infection 2011;139:836-848.

Abstract

We developed an individual-based (IB) model to explore the stochastic attributes of state transitions, the heterogeneity of the individual interactions, and the impact of different network structure choices on the poliovirus transmission process in the context of understanding the dynamics of outbreaks. We used a previously published differential equation-based model to develop the IB model and inputs. To explore the impact of different types of networks, we implemented a total of 26 variations of six different network structures in the IB model. We found that the choice of network structure plays a critical role in the model estimates of cases and the dynamics of outbreaks. This study provides insights about the potential use of an IB model to support policy analyses related to managing the risks of polioviruses and shows the importance of assumptions about network structure.

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Background on polio

What are the study’s main findings?

• This paper presents the first individual-based model for poliovirus outbreaks and confirms that the choice of network structure plays a critical role in the model estimates of cases and the dynamics of outbreaks, which is consistent with results from other individual-based models for other diseases.
• Controlling for all other factors in the simulation of an outbreak, the study finds that the choice of network structure alone leads to substantial variation of the probability that a virus introduction dies out without causing paralytic cases, with the highest probabilities of die-out for mixing site networks and all-in-range networks with low clustering.
• Considering only outbreaks that did not die out, the study suggest substantial variation in the speed of spread, duration of outbreaks, and moderate variation in the total number of paralytic cases and total number of infections as a result of the choice of network structure.
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• Although this work suggests that individual-based modeling offers an important opportunity to better characterize the actual dynamics of the spread of infection, using individual-based models appropriately for poliovirus outbreaks will depend on obtaining high-quality information about the nature of poliovirus transmission, immunity, and social interactions.
• The computational time to simulate poliovirus outbreaks in large populations represents an important consideration for the potential use of individual-based models to inform policies.
• The analysis considered a total of 26 variations of fully-connected, random, scale-free, small-world, all-in-range, and mixing site networks, and the study recommends that researchers should conduct additional studies to identify the most appropriate network structures for modeling polioviruses in different settings.
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