Appropriate models for the management of infectious diseases
Wearing, Helen J., Rohani, Pejman and Keeling, Matthew James. (2005) Appropriate models for the management of infectious diseases. PLOS Medicine, Vol.2 (No.7). pp. 621-627. ISSN 1549-1277
WRAP_Keeling_Appropriate_Models.pdf - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Official URL: http://dx.doi.org/10.1371/journal.pmed.0020174
Background Mathematical models have become invaluable management tools for epidemiologists, both shedding light on the mechanisms underlying observed dynamics as well as making quantitative predictions on the effectiveness of different control measures. Here, we explain how substantial biases are introduced by two important, yet largely ignored, assumptions at the core of the vast majority of such models.
Methods and Findings First, we use analytical methods to show that (i) ignoring the latent period or (ii) making the common assumption of exponentially distributed latent and infectious periods (when including the latent period) always results in underestimating the basic reproductive ratio of an infection from outbreak data. We then proceed to illustrate these points by fitting epidemic models to data from an influenza outbreak. Finally, we document how such unrealistic a priori assumptions concerning model structure give rise to systematically overoptimistic predictions on the outcome of potential management options.
Conclusion This work aims to highlight that, when developing models for public health use, we need to pay careful attention to the intrinsic assumptions embedded within classical frameworks.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics
|Divisions:||Faculty of Science > Life Sciences (2010- ) > Biological Sciences ( -2010)|
|Library of Congress Subject Headings (LCSH):||Epidemiology -- Mathematical models|
|Journal or Publication Title:||PLOS Medicine|
|Publisher:||Public Library of Science|
|Official Date:||July 2005|
|Number of Pages:||7|
|Page Range:||pp. 621-627|
|Access rights to Published version:||Open Access|
|Funder:||Royal Society (Great Britain), National Institutes of Health (U.S.) (NIH), Ellison Medical Foundation|
1. Frankish H (2003) Death toll continues to climb in Congo Ebola outbreak.
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