Abstract:
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Infectious disease modeling plays an important role in understanding and preventing diseases from spreading, and different approaches can be taken to describe it. In this regard, the well-known SIR (Susceptible, Infected, and Recovered) compartment model is a common choice for modeling problems of this kind. In this work, we use an extended version of the SIR model with age classes. Also, aiming to model the locations of infectious individuals in space, we employ techniques from Point Process modeling to describe the epidemic intensity across the studied region. In this way, the SIR model machinery will describe the disease-spreading evolution in time, and a Cox process will be used to model the spatial correlation in each of the discretized time windows. In a nutshell, our work proposes a framework for infectious disease modeling by integrating a compartment model in time and a Cox process model in space in such a way that we can study the distribution of infectious individuals in space and time. Also, when making predictions, if the epidemic dynamic is correctly characterized in time, the results in space-time are better when compared to a standard Cox process modeling approach.
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