Journal
JOURNAL OF THE ROYAL SOCIETY INTERFACE
Volume 7, Issue 43, Pages 271-283Publisher
ROYAL SOC
DOI: 10.1098/rsif.2009.0151
Keywords
mechanistic model; iterated filtering; sequential Monte Carlo; measles; state-space model
Categories
Funding
- National Science Foundation [0430120, 0545276, 0805533, DEB-0553768]
- Science & Technology Directorate, Department of Homeland Security
- Fogarty International Center, National Institutes of Health
- National Center for Ecological Analysis and Synthesis
- University of California, Santa Barbara
- State of California
- Direct For Biological Sciences [0545276, 0430120] Funding Source: National Science Foundation
- Direct For Mathematical & Physical Scien [0805533] Funding Source: National Science Foundation
- Division Of Mathematical Sciences [0805533] Funding Source: National Science Foundation
- Emerging Frontiers [0430120, 0545276] Funding Source: National Science Foundation
Ask authors/readers for more resources
Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions. We show the utility of the plug-and-play approach in the context of an investigation of measles transmission dynamics. Our novel methodology enables us to ask and answer questions that previous analyses have been unable to address. Specifically, we demonstrate that plug-and-play methods permit the development of a modelling and inference framework applicable to data from both large and small populations. We thereby obtain novel insights into the nature of heterogeneity in mixing and comment on the importance of including extra-demographic stochasticity as a means of dealing with environmental stochasticity and model misspecification. Our approach is readily applicable to many other epidemiological and ecological systems.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available