An empirical model for the infectious disease spread predictions
Disease-spreading simulation has received significant attention in research. In general, there are two approaches to simulating a pandemic. The first one assumes a homogeneous population and uses differential equations to model the number of people in each compartment: Susceptible, Exposed, Infectio...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175395 |
| _version_ | 1811685275467776000 |
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| author | Nguyen, Vinh Quang |
| author2 | Cai Wentong |
| author_facet | Cai Wentong Nguyen, Vinh Quang |
| author_sort | Nguyen, Vinh Quang |
| collection | NTU |
| description | Disease-spreading simulation has received significant attention in research. In general, there are two approaches to simulating a pandemic. The first one assumes a homogeneous population and uses differential equations to model the number of people in each compartment: Susceptible, Exposed, Infectious, and Recovered. The other approach reflects the population’s heterogeneity and utilizes face-to-face contact records for disease-spreading simulation. The objective of this study is to build an empirical model that follows the second approach, reflecting the dynamics of disease transmission, and then to compare it with other efficient approximating models such as network-based models. We will show that the presented empirical model only slightly enhances simulation accuracy despite its expensive time and space complexity. However, if the time step of the network-based model is inappropriately set, the disparity in simulation performance between the empirical and network-based models can be substantial. Therefore, the empirical model can serve as a benchmark to identify the optimal time step of the network-based model. |
| first_indexed | 2024-10-01T04:41:56Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/175395 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:41:56Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1753952024-04-26T15:45:04Z An empirical model for the infectious disease spread predictions Nguyen, Vinh Quang Cai Wentong School of Computer Science and Engineering ASWTCAI@ntu.edu.sg Computer and Information Science Algorithms Disease-spreading simulation has received significant attention in research. In general, there are two approaches to simulating a pandemic. The first one assumes a homogeneous population and uses differential equations to model the number of people in each compartment: Susceptible, Exposed, Infectious, and Recovered. The other approach reflects the population’s heterogeneity and utilizes face-to-face contact records for disease-spreading simulation. The objective of this study is to build an empirical model that follows the second approach, reflecting the dynamics of disease transmission, and then to compare it with other efficient approximating models such as network-based models. We will show that the presented empirical model only slightly enhances simulation accuracy despite its expensive time and space complexity. However, if the time step of the network-based model is inappropriately set, the disparity in simulation performance between the empirical and network-based models can be substantial. Therefore, the empirical model can serve as a benchmark to identify the optimal time step of the network-based model. Bachelor's degree 2024-04-24T01:41:34Z 2024-04-24T01:41:34Z 2024 Final Year Project (FYP) Nguyen, V. Q. (2024). An empirical model for the infectious disease spread predictions. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175395 https://hdl.handle.net/10356/175395 en application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Algorithms Nguyen, Vinh Quang An empirical model for the infectious disease spread predictions |
| title | An empirical model for the infectious disease spread predictions |
| title_full | An empirical model for the infectious disease spread predictions |
| title_fullStr | An empirical model for the infectious disease spread predictions |
| title_full_unstemmed | An empirical model for the infectious disease spread predictions |
| title_short | An empirical model for the infectious disease spread predictions |
| title_sort | empirical model for the infectious disease spread predictions |
| topic | Computer and Information Science Algorithms |
| url | https://hdl.handle.net/10356/175395 |
| work_keys_str_mv | AT nguyenvinhquang anempiricalmodelfortheinfectiousdiseasespreadpredictions AT nguyenvinhquang empiricalmodelfortheinfectiousdiseasespreadpredictions |