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United States Department of Agriculture

Agricultural Research Service

Research Project: IMMUNOLOGICAL APPROACHES TO CONTROLLING SWINE INTESTINAL PARASITES AND MUCOSAL PATHOGENS

Location: Animal Parasitic Diseases

Title: Use of the D-R model to define trends in the emergence of Ceftazidime-resistant Escherichia coli in China

Authors
item Ding, Fan -
item Zarlenga, Dante
item Ren, Yudong -
item Li, Guangxing -
item Luan, Jin -
item Ren, Xiaofeng -

Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 13, 2011
Publication Date: December 6, 2011
Citation: Ding, F., Zarlenga, D.S., Ren, Y., Li, G., Luan, J., Ren, X. 2011. Use of the D-R model to define trends in the emergence of Ceftazidime-resistant Escherichia coli in China. PLoS One. 6(12):e27295.

Interpretive Summary: Escherichia coli is a Gram negative rod-shaped bacterium that is commonly found in the lower intestine of warm-blooded organisms. Although most E. coli strains are harmless, some serotypes such as O157:H7, can cause serious food poisoning and even death in humans. Harmful bacterial infections are usually treated with antibiotics. In China and around the world, drug resistance is on the rise due to overuse in humans and overuse in the feed given to animals for promoting growth and weight gain. Ceftazidime is a common, third-generation cephalosporin antibiotic which has broad spectrum activity against Gram-negative bacteria; however, resistance is rapidly spreading. Being able to forecast future trends in drug resistance may provide valuable guidance on the appropriate clinical use of this and other antibiotics. Herein, we developed and used a novel algorithm, the D-R model, to simulate and predict future trends in bacterial resistance to Ceftazidime and compared these projections to those from other commonly used models. In our studies, the D-R model showed forecasting characteristics that equaled or bettered those generated by other commonly used models and projected that if left unchecked, resistance to Ceftazidime will exceed 75% within the next few years. These data and the D-R model will provide useful information to scientists, clinicians and veterinarians to help control the use of antibiotics, and assist in designing effective surveillance strategies for this and other transmissible diseases. With these projections clinicians and law makers can determine when and to what extent the infection rate has deviated from the norm, and provide guidance on how to best mitigate transmission.

Technical Abstract: Objective: To assess the efficacy of the D-R model for defining trends in the appearance of Ceftazidime-resistant Escherichia coli. Methods: Actual data related to the manifestation of Ceftazidime-resistant E.coli spanning years 1996-2009 were collected from the China National Knowledge Internet (CNKI). These data originated from 430 publications encompassing 1004 citations of resistance. The GM(1,1) and the novel D-R models were used to fit current data and from this, predict trends in the appearance of the drug-resistant phenotype. The calculated results were evaluated by Relative Standard Error (RSE), Mean Absolute Deviation (MAD) and Mean Absolute Error (MAE). Results: Results from the D-R model showed a quickly increasing appearance of Ceftazidime-resistant E. coli in this region of the world. These results were considered accurate based upon the minor values calculated for RSE, MAD and MAE, and were equivalent to or better than those generated by the GM(1,1) model. Conclusion: The D-R model which was originally created to define trends in the transmission of swine viral diseases can be adapted to evaluating trends in the appearance of Ceftazidime-resistant E. coli. Using only a limited amount of data to initiate the study, our predictions closely mirrored the changes in drug resistance rates which showed a steady increase through 2005, a decrease between 2005 and 2008, and a dramatic inflection point and abrupt increase beginning in 2008. This is consistent with a resistance profile where changes in drug intervention temporarily delayed the upward trend in the appearance of the resistant phenotype; however, resistance quickly resumed its upward momentum in 2008 and this change was better predicted using the D-R model. Additional work is needed to determine if this pattern of “increase-control-increase” is indicative of Ceftazidime-resistant E. coli or can be generally ascribed to bacteria acquiring resistance to drugs in the absence of alternative intervention.

Last Modified: 7/30/2014