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Estimating epidemic coupling between populations from the time to invasion
Karsten Hempel1, David J D Earn1
1Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4K1.
Journal of the Royal Society, Interface
|November 25, 2020
Summary
We developed a method to estimate disease transmission coupling between populations using susceptible-infected-removed (SIR) models. The time for a disease to invade a new population helps quantify this coupling, improving with more observed invasion events.
Area of Science:
- Epidemiology
- Mathematical Biology
- Network Science
Background:
- Understanding disease spread is crucial for epidemic and pandemic forecasting.
- Estimating transmission coupling between populations is challenging due to unobserved events and complex local dynamics.
Purpose of the Study:
- To present a method for estimating transmission coupling between two populations using susceptible-infected-removed (SIR) models.
- To demonstrate that invasion time into a second population can quantify coupling strength.
Main Methods:
- Modeling disease spread between two populations as coupled SIR systems.
- Analyzing the relationship between invasion time and transmission coupling strength.
- Investigating the impact of multiple invasion events on estimate confidence.
Main Results:
- Transmission coupling strength can be estimated from the time it takes for a disease to invade a second population.
- Single invasion events provide low confidence estimates.
- Multiple independent invasion events significantly improve the confidence of coupling estimates.
Conclusions:
- The proposed method offers a way to quantify epidemic coupling in idealized two-population scenarios.
- This work is a foundational step towards estimating epidemic connectivity in complex, interconnected global populations.
- Further research can extend these methods to more realistic and complex population structures.
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