Epidemic in small-world network

Koh, Sook Tean (2013) Epidemic in small-world network. [Final Year Project Report] (Unpublished)

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Abstract

The susceptible-infected-recovered type of epidemiological compartment models assumes the population is well-mixed, homogenous and each individual has the equal likelihood of getting the disease regardless their spatial location. Obviously, these oversimplifications of real-world epidemic outbreak have neglected the short-and long-range disease spreading process. the study of epidemic disease is always related with the social network when the interaction of individuals in a community or a region is concerned, especially in the context of contagious diseases such as influenza and measles, caused by biological pathogens. Thus, we model the spreading of infectious disease that takes place in a dynamic small-world network where individuals are connected through short-range and long-range linkage by two approaches. First we formulate the differential equations following the work of Saramaki(2004) where an aggregated model is derived. Then, the equations are solved and simulated with the help of System Dynamics Modeler in NetLogo. Next, we simulate an individual-based small-world network model by agent-based technique in NetLogo. also we examine the effect of long-rage connection in disease transmission and approximate the disease threshold in small-world network. The results from both the aggregate model and the individual-based model show a good agreement for small number of population.

Item Type: Final Year Project Report
Additional Information: Project Report (B.Sc.) -- Universiti Malaysia Sarawak, 2013
Uncontrolled Keywords: compartment models, System Dynamics Modeler, short-and long-range disease spreading process,
Subjects: K Law > K Law (General)
Q Science > QA Mathematics
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Dan
Date Deposited: 02 Aug 2022 06:25
Last Modified: 11 Aug 2023 03:11
URI: http://ir.unimas.my/id/eprint/39028

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