Abstract
To assess the impacts of various interventions on epidemic dynamics, the authors propose an integrated epidemiological simulation framework called Multilayer Epidemic Dynamics Simulator (MEDSim), which combines four contact structures: within age group, between age groups, daily commute, and nationwide interaction. We use the daily commuting network to simulate outbreak locations and intervention scenarios for the 2009 A/H1N1 influenza epidemic in Taiwan. Our three main findings are: (a) lower transmission rates and earlier intervention activation times did not reduce total numbers of infected cases, but did delay peak times; (b) when transmission rate was decreased by a minimum of 70%, significant slowing-down effects were observed when interventions were activated before the 50th new case (c) peaks times were achieved more quickly when initial outbreaks occurred in urban rather than rural areas. The innovative simulation framework reflects the dynamic processes of epidemics under different intervention scenarios, thus clarifying the effects of complex contact structures on disease transmission dynamics.
| Original language | English |
|---|---|
| Title of host publication | Selected Topics in System Science and Simulation in Engineering - 9th WSEAS International Conference on System Science and Simulation in Engineering, ICOSSSE'10 |
| Pages | 77-83 |
| Number of pages | 7 |
| State | Published - 2010 |
| Event | 9th WSEAS International Conference on System Science and Simulation in Engineering, ICOSSSE'10 - Iwate, Japan Duration: 04 10 2010 → 06 10 2010 |
Publication series
| Name | International conference on System Science and Simulation in Engineering - Proceedings |
|---|---|
| ISSN (Print) | 1792-507X |
Conference
| Conference | 9th WSEAS International Conference on System Science and Simulation in Engineering, ICOSSSE'10 |
|---|---|
| Country/Territory | Japan |
| City | Iwate |
| Period | 04/10/10 → 06/10/10 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Commuting network
- Computer simulation
- Epidemic dynamics
- Geographic information system
- Multilayer model
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