Development of an individual-based model for polioviruses: implications of the selection of network type and outcome metrics

Abstract

SUMMARYWe 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.

Characterizing Poliovirus Transmission and Evolution: Insights from Modeling Experiences with Wild and Vaccine‐Related Polioviruses

“…The DEB model does not track heterotypic immunity, which requires stratifying the population according to each possible combination of immunity states for the three serotypes (which would increase model complexity multiplicatively). The use of an individual‐based model might allow better characterization of the timing of immunity by serotype for each individual, but it would do so at the expense of significantly increased assumptions about population structure and individual contact and mixing patterns …”

Expert Review on Poliovirus Immunity and Transmission

“…As a result of the complexity of immunity, poliovirus infection transmission models must go beyond simple susceptible‐infected‐removed (SIR) models . While we recognize that the ability to participate in poliovirus transmission depends on many factors besides immunity, such as contact patterns and environmental conditions, we focus this review on the role of immunity and we assume that risk and policy models will capture the other factors in the basic reproductive number ( R 0 ) or more detailed characterizations of mixing . Thus, for this review determining the specific immunity states used to characterize population immunity represents the first task in model development …”

High-Resolution Epidemic Simulation Using Within-Host Infection and Contact Data

“…In addition, choices of theoretical network structure used for simulation can alter epidemic outcomes [28]. Thus, a network model at least obeying empirical data provides a more solid ground for epidemic simulations.…”

“…We propose that this limitation can be overcome by using explicitly within-host infection model. On the other, implementations of population level models were either a general representation using probabilistic assumption [28,29] or a demanding implementation of a particular population [27,30,15].…”