Simulating the Spread of Infectious Diseases in Heterogeneous Populations with Diverse Interactions Characteristics

• Main Author: Gomez-Lopez, Iris Nelly
• Other Authors: Mikler, Armin R.
• Format: Others
• Language: English
• Published: University of North Texas 2013
• Subjects: Simulation; epidemiology; population
• Online Access: https://digital.library.unt.edu/ark:/67531/metadc407831/

The spread of infectious diseases has been a public concern throughout human history. Historic recorded data has reported the severity of infectious disease epidemics in different ages. Ancient Greek physician Hippocrates was the first to analyze the correlation between diseases and their environment. Nowadays, health authorities are in charge of planning strategies that guarantee the welfare of citizens. The simulation of contagion scenarios contributes to the understanding of the epidemic behavior of diseases. Computational models facilitate the study of epidemics by integrating disease and population data to the simulation. The use of detailed demographic and geographic characteristics allows researchers to construct complex models that better resemble reality and the integration of these attributes permits us to understand the rules of interaction. The interaction of individuals with similar characteristics forms synthetic structures that depict clusters of interaction. The synthetic environments facilitate the study of the spread of infectious diseases in diverse scenarios. The characteristics of the population and the disease concurrently affect the local and global epidemic progression. Every cluster’ epidemic behavior constitutes the global epidemic for a clustered population. By understanding the correlation between structured populations and the spread of a disease, current dissertation research makes possible to identify risk groups of specific characteristics and devise containment strategies that facilitate health authorities to improve mitigation strategies.