Non-Markovian epidemic processes in complex networks

• Grant number: 21/12566-5
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2022
• End date: July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Francisco Aparecido Rodrigues
• Grantee: José Andrés Guzmán Morán
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The use of Markovian processes to describe epidemic phenomena in complex networks has been a dominant approach in the last few years. Markovian models do not consider the effect of memory, in other words, past events do not affect future ones. This is not what actually happens in the majority of real world processes. Non-Markovian epidemic processes, which are characterized by events that cannot be described by Poisson random processes, are a way to consider memory. In this Project, we intend to explore how network properties and characteristics affect propagation dynamics modeled by non-Markovian processes. These results will be compared with simulation characterized by Markovian processes, and the differences between these two approaches will be highlighted. Also, the Mai-Thompson roumer model will be studied considering the effect of memory. Again, how network properties, characteristics and topology affect propagation dynamics will be studied. (AU)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

MORÁN, José Andrés Guzmán. Non-Markovian epidemic processes in complex networks. 2023. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.