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Prediction and Predictability of Resistance to Antibiotics: Studies Based on Coupled Map Lattices

Applicant Shiner John S.
Number 63267
Funding scheme NRP 49 Antibiotic resistance
Research institution Department for BioMedical Research Universität Bern
Institution of higher education University of Berne - BE
Main discipline Infectious Diseases
Start/End 01.07.2001 - 30.06.2004
Approved amount 61'307.00
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All Disciplines (2)

Infectious Diseases
Methods of Epidemiology and Preventive Medicine

Lay Summary (English)

Lay summary
Prediction and predictability of resistance to antibiotics: studies based on coupled map lattices

Population control and antibiotics usage strategies for reducing the appearance of antibiotic resistance to antibiotics or preventing its spread should have a rational basis if possible. Mathematical studies are designed to provide insights into and guidelines for these strategies.

Among the weapons available to fight bacteria resistant to antibiotics are those of population control. Quarantine and isolation come to mind. Isolation is often undesirable, however, and may be impossible under certain circumstances. Isolation may also lead to unexpected effects. In ecology it is known that many small isolated populations may be more effective in preserving species than a few large ones. Of course, in the case of drug resistant germs, one wants to eradicate the population. Ecology tells us that isolation may be the wrong strategy. Furthermore, the development of an epidemic of bacterial resistance may be only weakly predictable due to "chaos", or because of variability in the number of contacts an infected person has. Additionally one wants to use as little antibiotic as possible, since its use leads to resistance.

Our goals are twofold. (1) To understand when the time course of infections and resistance are predictable and to develop mathematical "tricks" to restore predictability when they are not. (2) To study the effects of the degree of contact between populations, the connections between the populations and their relative sizes on the spread of a resistant infection and the amount of antibiotic needed to have the most effect in combating the nonresistant germs and the smallest effect on inducing resistance.

Those responsible for making decisions about strategies for fighting antibiotic resistance need a rational basis for deciding which isolation policies to pursue to inhibit the spread of resistance and reduce the amount of antibiotic used, while at the same time still treatin nonresistant infections. Our studies are designed to give them insights into and guidelines for which policies are best when the spread of infection is predictable. When it is not, it is important that they know this too, since then the methods for restoring predictability may be useful, or if all else fails, any decisions will have to be based on other considerations.

Direct link to Lay Summary Last update: 21.02.2013

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