Disease elimination and re-emergence in differential-equation models
Scott Greenhalgh1, Alison P Galvani1, Jan Medlock2
1Center for Infectious Disease Modeling and Analysis, School of Public Health, Yale University, 135 College Street, New Haven, CT 06510, USA.
Journal of Theoretical Biology
|October 17, 2015
Summary
This study introduces a novel control theory approach to model disease dynamics at low prevalence, accurately predicting measles re-emergence in Iceland by accounting for migration events.
Area of Science:
- Epidemiology
- Mathematical Biology
- Control Theory
Background:
- Traditional differential equation models struggle with probabilistic events during disease elimination and re-emergence.
- Low disease prevalence phases require models that capture stochastic dynamics.
Purpose of the Study:
- To develop a novel control theory application for modeling disease dynamics at low prevalence.
- To analyze measles elimination and re-emergence in Iceland (1923-1938).
- To predict disease trajectories influenced by external migration.
Main Methods:
- Application of control theory to epidemiological modeling.
- Analysis of historical measles data from Iceland.
- Modeling disease migration from Copenhagen, Denmark.
Main Results:
- The novel approach successfully modeled measles elimination and re-emergence.
- Disease migration from Copenhagen was identified as a key factor in re-emergence.
- Predicted temporal trajectories of measles dynamics.
Conclusions:
- Control theory offers a viable alternative to stochastic models for low-prevalence disease dynamics.
- Understanding migration's role is crucial for predicting disease re-emergence.
- The model provides insights into managing infectious disease elimination.
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