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Modelling strategies for minimizing the impact of an imported exotic infection
1Institute of Information and Mathematical Sciences, Massey University, North Shore Mail Centre, Auckland, New Zealand. m.g.roberts@massey.ac.nz
Abstract:
The global epidemic of severe acute respiratory syndrome (SARS) in 2003 demonstrated the need to determine control strategies for exotic infections. The prior determination of such strategies, and the use of mathematical models to assist this, is hampered by the obvious lack of data. We propose an integral equation model of Kermack-McKendrick type that may be used to compare strategies based on the isolation of infectious individuals. The model structures the incidence of infection according to the location of an infected individual at exposure, and requires knowledge of the infectivity kernel and the initial rate of exponential increase of cases. The model's use in the design of strategies to minimize the risk of SARS in a previously unexposed community is demonstrated.
Insights
This study introduces a mathematical model to compare infectious disease control strategies, specifically isolation, for novel outbreaks like severe acute respiratory syndrome (SARS). The model aids in minimizing epidemic risk in unexposed populations.
Area of Science:
- Epidemiology
- Mathematical Biology
- Infectious Disease Modeling
Background:
- The 2003 SARS epidemic highlighted the need for effective control strategies for novel infectious diseases.
- Developing these strategies is challenging due to a lack of empirical data for new pathogens.
- Mathematical modeling is crucial for evaluating and designing disease control interventions.
Purpose of the Study:
- To propose an integral equation model of Kermack-McKendrick type for comparing isolation-based control strategies.
- To demonstrate the model's utility in designing strategies to minimize SARS risk in a new community.
Main Methods:
- Development of an integral equation model based on the Kermack-McKendrick framework.
- Structuring infection incidence by exposure location.
- Incorporating infectivity kernel and initial exponential growth rate of cases.
Main Results:
- The proposed model allows for the comparison of different isolation strategies.
- The model can predict the impact of isolation on disease spread based on location and infectivity.
- Demonstrated application in designing risk-minimization strategies for SARS.
Conclusions:
- The integral equation model provides a framework for evaluating infectious disease control strategies, particularly isolation.
- This modeling approach can inform public health decisions for emerging infectious diseases.
- The model is valuable for proactive risk management in previously unexposed populations.
