What is it about?
Computational epidemiological models are widely used in public health planning, emergency preparedness and government decision-making. All such models are planning tools and best used judiciously by well-informed practitioners. This paper provides state-of-the-art assessment as to the potential for their optimal use, and also what is as yet unknown for such predictive models.
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Why is it important?
We endeavor to provide guidance as to the relevance of computational epidemiological models for public health practice. We examine disease-specific models of greatest concern for public health protection, including Ebola, influenza, smallpox, anthrax, cholera, and typhoid. From this assessment, we describe what has been learned and the benefits of modeling each disease, the known pitfalls, and what remains to be accomplished.
Perspectives
The intent is that this article stimulates and enables further discussion and examination of the applications of mathematical disease models. The eminent statistician George Box's observation that: "All models are wrong, but some are useful" should be foremost for anyone hoping to predict disease in human populations. While imperfect, the use of predictive disease models in planning for and during outbreaks has become a high-demand tool in public health. The more such practices are examined and improved, the greater the potential to attain Box's ideal that ".. cunningly chosen parsimonious models often do provide remarkably useful approximations."
Zygmunt Dembek
Battelle Memorial Institute
Read the Original
This page is a summary of: Best practice assessment of disease modelling for infectious disease outbreaks, Epidemiology and Infection, May 2018, Cambridge University Press,
DOI: 10.1017/s095026881800119x.
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