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The transmission dynamics of the coronavirus -COVID-19-have challenged humankind at almost every level. Currently, research groups around the globe are trying to figure out such transmission dynamics using different scientific and technological approaches. One of those is by using mathematical and computational models like the compartmental model or the agent-based models. In this paper, a general agent-based model, called INFEKTA, that combines the transmission dynamics of an infectious disease with agents (individuals) that can move on a complex network of accessible places defined over a Euclidean space representing a real town or city is proposed. The applicability of INFEKTA is shown by modeling the transmission dynamics of the COVID-19 in Bogotá city, the capital of Colombia. Introduction 1Infectious diseases have a substantial impact on public health, health care, 2 macroeconomics, and society. The availability of options to control and prevent the 3 emergence, expansion or resurgence of pathogens warrants continuous evaluation using 4 different methods. Mathematical models allow characterizing both the behavior and the 5 emergent properties of biological systems, such as the transmission of infectious 6 disease. [1-3]. Many biological systems have been modeled in terms of complexity since 7 their collective behavior cannot be simply inferred from the understanding of their 8 components [4, 5].9Complex systems are computational approaches that make use of computer-based 10 algorithms to model dynamic interactions between individuals agents (e.g. persons, 11 cells) or groups and their properties, within, and across levels of influence [6,7]. In 12 general, agent-based modeling (ABM) can be used for testing theories about underlying 13 interaction mechanics among the system's components and their resulting dynamics. It 14 can be done by relaxing assumptions and/or altering the interaction mechanisms at the 15 individual agent level. ABMs can increase our understanding of the mechanisms of 16 complex dynamic systems, and the results of the simulations may be used for predicting 17 future scenarios [8].In this paper, we introduce an ABM, called INFEKTA (Esperanto word for 19 infectious), for modeling the transmission of infectious disease, applied to the 20 coronavirus COVID-19. INFEKTA models the disease transition at the person level and 21 takes into consideration individual infection disease incubation periods and evolution, 22 medical preconditions, age, daily routines (movements from house to destination places 23 and back, including transportation medium if required), and enforced social separation 24 policies. 25Complex Systems Approaches for Epidemic Models 26 The complex system model approach considers a system as a large number of entities 27 (equally complex systems that have autonomous strategies and behaviors) that interact 28 with each other in local and non-trivial ways [9][10][11]. This approach provides a 29 conceptual structure (a multi-level complex network [12]) that allows characterizing ...
The transmission dynamics of the coronavirus -COVID-19-have challenged humankind at almost every level. Currently, research groups around the globe are trying to figure out such transmission dynamics using different scientific and technological approaches. One of those is by using mathematical and computational models like the compartmental model or the agent-based models. In this paper, a general agent-based model, called INFEKTA, that combines the transmission dynamics of an infectious disease with agents (individuals) that can move on a complex network of accessible places defined over a Euclidean space representing a real town or city is proposed. The applicability of INFEKTA is shown by modeling the transmission dynamics of the COVID-19 in Bogotá city, the capital of Colombia. Introduction 1Infectious diseases have a substantial impact on public health, health care, 2 macroeconomics, and society. The availability of options to control and prevent the 3 emergence, expansion or resurgence of pathogens warrants continuous evaluation using 4 different methods. Mathematical models allow characterizing both the behavior and the 5 emergent properties of biological systems, such as the transmission of infectious 6 disease. [1-3]. Many biological systems have been modeled in terms of complexity since 7 their collective behavior cannot be simply inferred from the understanding of their 8 components [4, 5].9Complex systems are computational approaches that make use of computer-based 10 algorithms to model dynamic interactions between individuals agents (e.g. persons, 11 cells) or groups and their properties, within, and across levels of influence [6,7]. In 12 general, agent-based modeling (ABM) can be used for testing theories about underlying 13 interaction mechanics among the system's components and their resulting dynamics. It 14 can be done by relaxing assumptions and/or altering the interaction mechanisms at the 15 individual agent level. ABMs can increase our understanding of the mechanisms of 16 complex dynamic systems, and the results of the simulations may be used for predicting 17 future scenarios [8].In this paper, we introduce an ABM, called INFEKTA (Esperanto word for 19 infectious), for modeling the transmission of infectious disease, applied to the 20 coronavirus COVID-19. INFEKTA models the disease transition at the person level and 21 takes into consideration individual infection disease incubation periods and evolution, 22 medical preconditions, age, daily routines (movements from house to destination places 23 and back, including transportation medium if required), and enforced social separation 24 policies. 25Complex Systems Approaches for Epidemic Models 26 The complex system model approach considers a system as a large number of entities 27 (equally complex systems that have autonomous strategies and behaviors) that interact 28 with each other in local and non-trivial ways [9][10][11]. This approach provides a 29 conceptual structure (a multi-level complex network [12]) that allows characterizing ...
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