Global urbanization presents numerous health challenges and necessitates a deeper comprehension of how diseases spread in urban settings. The chapter proposes a novel framework for epidemic risk analysis by incorporating human mobility. The proposed framework combines evidence-based risk analysis driven by facts with the advantages of flexible precautionary models taking into account causation-and-effect connections and spatial reference. The precautionary approach is implemented in the form of a set of interrelated models, which, as a result, give estimates of a potential risk, obtained in advance and distributed in space. To obtain these estimates, the following models are built: a spatial model, a model of human mobility, as well as a model of disease spread. The spatial model comprises a set of confined locations of people’s concentration. These locations are subdivided into several levels, such as residential buildings (base locations where people live), and workplace locations / locations of study (locations that people attend regularly). Over the spatial model, we build the model of human mobility represented as a network with the nodes being locations of different levels. Each node at every time moment is characterized by a certain number of people. The arcs of the network show human flows within the spatial model, which influence disease spread. The disease spreading model reflects disease movement through the nodes of the network. Each node of the network has its status regarding a certain disease, such as susceptible, infected, or recovered. A transition of the node from one status to another is represented as an event. A spread of the disease through the nodes of the network is represented by an event-tree network. We also consider external factors (meta-factors) that can influence the rate of spread of the disease such as weather conditions (temperature, humidity) and air quality. A distinctive feature of the proposed approach is a spatial reference of network nodes. This chapter addresses the framework for epidemic risk analysis. The proposed framework is based on two main principles such as an evidence-based approach and a precautionary principle. These principles are used in the following way. Using the precautionary principle, scenarios of disease spread and risk assessments are built in advance and can be used for disease prevention and mitigation. With the help of the evidence-based approach, the risk assessments obtained using the precautionary approach are adjusted. Justified risk assessments can be used for making decisions to counter the disease. The proposed framework makes it possible to diagnose the situation within the area of interest and sheds new light on disease-spreading analysis. The most dangerous areas can be identified, and measures can be taken to stop the disease from spreading. The work contributes to the creation and putting into practice the policies that slow down or prevent the spread of illnesses.
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