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Nine challenges for deterministic epidemic models
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Roberts, Mick G., Andreasen, Viggo, Lloyd, Alun and Pellis, Lorenzo (2015) Nine challenges for deterministic epidemic models. Epidemics, 10 . pp. 49-53. doi:10.1016/j.epidem.2014.09.006
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Official URL: http://dx.doi.org/10.1016/j.epidem.2014.09.006
Abstract
Deterministic models have a long history of being applied to the study of infectious disease epidemiology. We highlight and discuss nine challenges in this area. The first two concern the endemic equilibrium and its stability. We indicate the need for models that describe multi-strain infections, infections with time-varying infectivity, and those where superinfection is possible. We then consider the need for advances in spatial epidemic models, and draw attention to the lack of models that explore the relationship between communicable and non-communicable diseases. The final two challenges concern the uses and limitations of deterministic models as approximations to stochastic systems.
| Item Type: | Journal Article | ||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine | ||||||||||
| Divisions: | Faculty of Science > Mathematics | ||||||||||
| Library of Congress Subject Headings (LCSH): | Epidemics, Epidemiology | ||||||||||
| Journal or Publication Title: | Epidemics | ||||||||||
| Publisher: | Elsevier | ||||||||||
| ISSN: | 1755-4365 | ||||||||||
| Official Date: | March 2015 | ||||||||||
| Dates: |
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| Volume: | 10 | ||||||||||
| Number of Pages: | 5 | ||||||||||
| Page Range: | pp. 49-53 | ||||||||||
| DOI: | 10.1016/j.epidem.2014.09.006 | ||||||||||
| Status: | Peer Reviewed | ||||||||||
| Publication Status: | Published | ||||||||||
| Access rights to Published version: | Open Access | ||||||||||
| Funder: | Royal Society of New Zealand, United States. Department of Homeland Security. Science and Technology Directorate, Fogarty International Center, National Institutes of Health (U.S.) (NIH), National Science Foundation (U.S.) (NSF), Engineering and Physical Sciences Research Council (EPSRC) | ||||||||||
| Grant number: | MAU1106 (RSNZ), R01-AI091980 (NIH), RTG/DMS-1246991 (NSF) |
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