The Influence of Global Environmental Change on Infectious Disease Dynamics: Workshop Summary by Eileen R. Choffnes

Author:Eileen R. Choffnes
Language: eng
Format: epub
Tags: ebook, book
Publisher: The National Academies Press
Published: 2014-09-10T00:00:00+00:00

A8

MISCONCEPTIONS AND EMERGING PATHOGENS: WHAT CAN MATHEMATICAL MODELS TELL US?

Andrew Dobson25

The last 25 years have seen a renaissance in the use of mathematical models in epidemiology; much of this is largely due to the influence of Anderson and May and their colleagues (Anderson and May, 1992; Grenfell and Dobson, 1994, 1995). The transformation came about as the models they developed were based upon empirical assumptions. This allowed the whole discipline to move from an overt fascination with mathematical elegance, to embrace data and become the pragmatic powerhouse that is at the center of quantitative insight to any modern epidemiological problem. At first glance, this creates problems for the use of these models in studies of emerging diseases, as almost by definition, there will be no data prior to emergence. Nonetheless, all of the recent major studies of disease emergence have quickly led to the almost obligatory use of mathematical models in infectious disease biology. A nice index of this was the chance remark by the editor of one major journal during a recent influenza outbreak, “Half the world is worried about this new pathogen—while we’re facing an epidemic of submitted papers, all claiming to have produced the definitive predictive model for it!”

In this short overview, I will take a brief personal and idiosyncratic review of the key ways in which mathematical models have been used, misused, or could potentially be used to provide insights into the dynamics of emerging pathogens. I will offer no specific recommendations or recipes for the “best way” to use models to understand pathogen emergence. This is partly because different model structures will provide different insights to different pathogens; moreover, each new emergence usually leads to the development of new mathematical tricks, techniques, and approaches that provide powerful new tools for the current crisis and often retrospective insights into older emergences.

Dynamics of Initial Cross-Over

A huge number of pathogens are circulating in all free-living species of animals and plants. One of the most profound testimonies to the shortsightedness of scientific exploration is that we know neither how many other species share the planet with us, nor how many are pathogens or parasites of the more apparent and better classified free-living species (Dobson et al., 2008). The most conservative estimate is that 50 percent of species are parasitic, but it could be significantly higher, potentially larger than 90 percent. Although a huge number of pathogens could potentially colonize humans (or domestic livestock and crops), only a relatively small proportion seem to have done so. Although searching for “the next pandemic virus” has achieved the momentum of a well-oiled government job-creation scheme (a curious European phenomenon that may be unfamiliar to USA readers!), I suspect that a large proportion of pathogens that might jump the species barrier to humans may already have attempted this leap and have failed the test. The simple logic here is humans have explored most of the terrestrial parts of the planet and exposed themselves to a multitude of insect bites, scratches by plants, and

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