The development of drug-resistant strains of bacteria is an increasing threat to society, especially in hospital settings. Many antibiotics that were formerly effective in combating bacterial infections are no longer effective due to the evolution of resistant strains. The evolution of these strains compromises medical care worldwide. The goal of this project is to understand how to improve the situation in various kind of hospitals. Recently we focus on the effect of the antibiotic treatments. We have shown that the treatment period may influence the spread of resistant strain in Hospitals. The figures below are obtained from the IBM (Individual Based Model) that we have constructed. The same result is obtained for a corresponding PDE (Partial Derivative Equation). In the above figures below the green curve corresponds to the percentage of patients infected by non-resistant (to antibiotic) strain, and the red curve corresponds to the percentage infected by resistant (to antibiotic) strain. The only different between Figure 1 and Figure 2 is the period of treatment. In figure 1 the treatment starts on day 3 and stops on day 21 after infection. In figure 2 the treatment starts on day 1 and stops on day 8.
Figure 1: Antibiotic treatment starts on day 3 and stops on day 21
Figure 2: Antibiotic treatment starts on day 1 and stops on day 8
The point is that in Figure 1 the infection persists (i.e. there are still some infected patients) after 400 days, while in Figure 2 after the days 300 there are no more infected. This study allow us to conclude that the antibiotic treatment may strongly influence the persistence of Nosocomial infection.
The above figures are done by using an Individual Based Model (IBM) and a Differential Equation Model (DEM) (see D’Agata, P. Magal, D. Olivier, S. Ruan, G.F. Webb, Journal of Theoretical Biology 249 (2007) for detailled description). You may download the MATLAB codes below
Another aspect in our study concerns the visualization of data for infected patients in hospitals. Our goal is to provide a tool for medical doctors to use the available data in hospitals. We hope that such a tool will eventually medical doctors to solve such a problems. We already started to construct such a tool and the movie below corresponds to an infection of Pseudomonas aeruginosa in one of the Hospitals in Le Havre.
In this movie the hospital in represented by a graph, and the sensitive patients (respectively infected patients) are represented by green points (by red point). In this visualization we only represent the patients which will become eventually infected.
Click Here to download the movie for the data of the Hospital of Le Havre
We can also simulate the healthcare workers displacements into a department in the Hospital, with the contamination process. The following movie shows an example of such visualization. There is 1 healthcare worker moving from patient to patient. The patients in green are not infected by resistant strain, and the red patients are infected. We can visualize the transmission from patient to patient using such a program.
Click right to download the movie of 1 department
If you have any problems in visualizing the movie, please go to the following web page, and download the program VLC depending on the fact that you are using Windows, Mac, Linux, etc... . Please use VCL to visualize the movies. It should work hopefully!
REFERENCES
E. M.C. D'Agata, M. Dupont-Rouzeyrol, P. Magal, D. Olivier, S. Ruan (2008), The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria. PLoS ONE 3(12), 1-9.
E.M.C. D’Agata, P. Magal, D. Olivier, S. Ruan, G.F. Webb (2007), Modeling Antibiotic Resistance in Hospitals: The Impact of Minimizing Treatment Duration, Journal of Theoretical Biology 249, 487–499.
E. D'Agata, P. Magal, S. Ruan and G. F. Webb (2006), Asymptotic behavior in nosocomial epidemic models with antibiotic resistance, Differential and Integral Equations 19, 573-600.
A. Dutot, P. Magal, D. Olivier, and G. Savin (2006). Pyocyanic bacillus propagation simulation. In Eurosis, editor, European Simulation and Modelling Conference 440-449.
G.F. Webb, E. D'Agata, P. Magal, S. Ruan, (2005), A model of antibiotic resistant bacterial epidemics in hospitals. Proceedings of the National Academics of Sciences of the USA, 102, 13343-13348.