Disease spread modeling using contact network

In recent years, due to emergent concerns from the COVID-19 pandemic, there has been an upsurge in interest surrounding the modeling of infectious disease transmission. One widely used approach relies on compartment models, which make assumptions of uniformly mixed populations. While these mod...

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Main Author: Wu, JunYan
Other Authors: Cai Wentong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/171773
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1717732023-12-15T15:38:06Z Disease spread modeling using contact network Wu, JunYan Cai Wentong School of Computer Science and Engineering ASWTCAI@ntu.edu.sg Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity In recent years, due to emergent concerns from the COVID-19 pandemic, there has been an upsurge in interest surrounding the modeling of infectious disease transmission. One widely used approach relies on compartment models, which make assumptions of uniformly mixed populations. While these models offer insights on a macro level, making them suitable for broad analyses, they can fall short in capturing the intricate processes of individual-to-individual contacts that drive disease propagation. To address this gap, our final year project delves into predicting disease transmission using contact networks, employing the dataset titled “Contact Patterns in a High School: A comparison between Data Collected Using Wearable Sensors, Contact Diaries, and Friendship Surveys”. Initially, the project entails an exploratory data analysis to decipher the publicly available data and to visualize space-time activity patterns. Subsequent steps involve extracting a contact network from the dataset to depict disease transmission pathways through vertices and edges. The research then shifts to an in-depth exploration of the contact network's attributes, it was discerned that certain nodes, potentially 'super-spreaders', played a disproportionate role in potential transmission pathways. Our findings underscore the importance of micro-level analyses for informed intervention strategies. Recognizing high-risk individuals and understanding their interaction patterns can equip health authorities with a more granular toolkit, ultimately enabling more targeted and effective containment measures in outbreak scenarios. Bachelor of Engineering (Computer Science) 2023-11-08T00:38:10Z 2023-11-08T00:38:10Z 2023 Final Year Project (FYP) Wu, J. (2023). Disease spread modeling using contact network. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/171773 https://hdl.handle.net/10356/171773 en application/pdf application/vnd.ms-powerpoint Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
spellingShingle Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
Wu, JunYan
Disease spread modeling using contact network
description In recent years, due to emergent concerns from the COVID-19 pandemic, there has been an upsurge in interest surrounding the modeling of infectious disease transmission. One widely used approach relies on compartment models, which make assumptions of uniformly mixed populations. While these models offer insights on a macro level, making them suitable for broad analyses, they can fall short in capturing the intricate processes of individual-to-individual contacts that drive disease propagation. To address this gap, our final year project delves into predicting disease transmission using contact networks, employing the dataset titled “Contact Patterns in a High School: A comparison between Data Collected Using Wearable Sensors, Contact Diaries, and Friendship Surveys”. Initially, the project entails an exploratory data analysis to decipher the publicly available data and to visualize space-time activity patterns. Subsequent steps involve extracting a contact network from the dataset to depict disease transmission pathways through vertices and edges. The research then shifts to an in-depth exploration of the contact network's attributes, it was discerned that certain nodes, potentially 'super-spreaders', played a disproportionate role in potential transmission pathways. Our findings underscore the importance of micro-level analyses for informed intervention strategies. Recognizing high-risk individuals and understanding their interaction patterns can equip health authorities with a more granular toolkit, ultimately enabling more targeted and effective containment measures in outbreak scenarios.
author2 Cai Wentong
author_facet Cai Wentong
Wu, JunYan
format Final Year Project
author Wu, JunYan
author_sort Wu, JunYan
title Disease spread modeling using contact network
title_short Disease spread modeling using contact network
title_full Disease spread modeling using contact network
title_fullStr Disease spread modeling using contact network
title_full_unstemmed Disease spread modeling using contact network
title_sort disease spread modeling using contact network
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/171773
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