SCIENTIFIC INITIATION - PIBIC/CNPq/UFOP
Under the guidance of Prof. (a) VANDER LUIS DE SOUZA FREITAS, from the DEPARTMENT OF COMPUTATION, from UFOP.
This project aims to simulate epidemiological models in temporal mobility networks. We seek to compare the results obtained from dynamic networks and static versions. A second strategy is commonly used, starting from the aggregation of the network states in several instants of time, within a temporal one - a simplification of the flows of people between locations. However, having the status of the network available at different times, reliable, with more partial results, numbers of confirmed cases, deaths, etc. accurate during a simulation. Some points that will be investigated in this project are: the quantification of the differences between a simulated dynamics in the temporal network and its static version; what is the difference in the distinction of the time scale of the network in relation to its more refined version, or to verify if it is possible to aggregate some states of the network and still obtain the same results and investigate the correspondences between the changes in the dynamics with the topological changes of the network, in time.
A complex network is a graph composed of vertices, representing entities that make up the complex system under study, and edges, which capture the interactions between them. Examples are mobility networks, the Internet and social networks (BOCCALETTI et al, 2006; BARABÁSI, 2016).
An important feature of real networks is their evolution over time (KIM and ANDERSON, 2012; MASUDA et al., 2021). There are several ways of representing temporal networks, such as aggregated networks and event graphs, transmission, reachability and the like (SANO, 2021). Common metrics, such as degree and betweenness, must be adapted depending on the type of representation, as the notions of connectivity and shortest path are, in these cases, tied to time.
Mobility networks are characterized by nodes that represent locations and links that denote the flow of people between one node and another, in a given time window (LAMOSA et al., 2021). In the specific case of these networks, some databases provide static data with one or more layers (CAVARARO, 2017; GOVERNO DO ESTADO DE SÃO PAULO, 2019) and others with layers and a temporal component (GALLOTTI and BARTHELEMY, 2015). Epidemiological processes, for example, can be simulated in greater detail the more complete the network representation.
This project seeks to investigate: the quantification of the differences between the simulated dynamics in the temporal network and its static version; what is the tolerance in changing the time scale of the network in relation to its more refined version, that is, to verify if it is possible to aggregate some states of the network and still obtain the same results and; the correspondences between changes in dynamics with topological changes in the network over time. Initially, the SIR compartment model will be used, with metapopulations (KERMACK and McKENDRICK, 1927; HARKO, 2014), to simulate epidemics.
The general objective is to investigate a dynamic of epidemiological processes in temporal mobility networks and compare with a dynamic in static mobility networks. The goals are specifications:
- (1) Conduct a literature review on the methods used to solve the usage problem.
- (2) Model epidemiological processes in mobility networks.
- (3) Simulate the processes in temporal networks at different time scales.
- (4) Simulating the processes in static networks and comparing with the temporal case.
- (5) Contribute to the dissemination of techniques applied to solving the problem.
- (6) Collaborate with the training of human resources specialized in this area of knowledge.
- (7) To favor the consolidation of the Intelligent Systems Computing Laboratory (CSILab) of the Federal University of Ouro Preto.
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