Network Modelling of Infectious Diseases
Abstract/ Overview
Mathematical modelling of infectious diseases is an important tool for assessing disease
dynamics. This branch of mathematics has provided many significant insights concerning the
epidemiology of infectious diseases. Previous disease models studied normally took the
deterministic approach in modelling. This form of modelling, even thoti~h it has helped to
bring out some powerful epidemiological insights; has been criticized to be less realistic
because it oversimplifies the biology of real world disease dynamics. In recent years, where
machines with more computing power have been introduced; more complex modelling
scenarios have been developed. Much of this complexity can be incorporated within the
population level framework provided by compartmental models. This form modelling of
diseases has heavily borrowed techniques from network science to come up with complex
epidemiological scenarios that do not make the unrealistic assumptions of homogenous
populations. These complex modelling scenarios are believed to give a more realistic picture
of epidemiological dynamics thus providing important insights in disease control and
prevention. In this study we investigated how network modelling can be incorporated in
existing compartmental models. This was done with an aim of gaining a better understanding
of different disease properties and more importantly to predict how various disease mitigation
and prevention measures can work in different disease scenarios. A comparison of
compartmental modelling scenarios and network modelling scenarios is also done using an
interactive modelling software called NetLogo.
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