Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis

López-Lozano, J.M.; Monnet, Dominique; Yagüe, Alberto; Burgos, Amparo; Gonzalo, Nieves; Campillos, Pilar; Sáez, Marc

doi:10.1016/s0924-8579(99)00135-1

Cited by 178 publications

(145 citation statements)

References 17 publications

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“…26 The Box-Jenkins approach uses autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models for time-series analysis to make forecasts. Ló pezLozano et al 27 employed ARIMA (Box-Jenkins) and transfer function models to analyze antimicrobial use and resistance in ceftazidimeGram-negative bacilli and imipenem-Pseudomonas aeruginasa. Their results indicated a temporal relationship between antimicrobial use and bacterial resistance.…”

Section: Discussionmentioning

confidence: 99%

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

et al. 2012

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We analyzed the effect of antimicrobial use and implementation of a hand hygiene program on the incidence of healthcareassociated infections (HAIs) and healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) infections at the Chung Shan Medical University Hospital (Taichung, Taiwan). Monthly data were retrospectively reviewed from January 2004 to December 2010. Use of antimicrobials and alcohol-based hand cleaner were separately regressed against the incidences of HAIs and HA-MRSA infections. Infection incidence was expressed as persons per 1000 patient days (PDs), monthly use of i.v. antibiotics was expressed as defined daily doses per 1000 PDs and monthly alcohol-based hand cleaner use was expressed as bottle per 1000 PDs. Multivariate analysis indicated that use of hand cleaner was associated with reduced incidence of HAIs (P ¼ 0.0001) and HA-MRSA infections (Po0.0001). Time-series analysis indicated that increased use of hand cleaner was significantly associated with significant decreases in the incidences of HAIs and HA-MRSA infections. Total antibiotic use had no significant effect on HAIs, but was associated with more HA-MRSA infections. In addition, the use of J01CR01 antibiotics (combinations of penicillins, including b-lactamase inhibitors) in particular was correlated with significantly increased incidence of HA-MRSA infections. Our forecasting model demonstrates the efficacy of a hand hygiene program and the need to limit the use of certain restricted antimicrobials in order to reduce the incidence of HAIs and HA-MRSA infections.

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Section: Discussionmentioning

confidence: 99%

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

et al. 2012

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“…(v) The lack of coresistance to ␤-lactams may weaken the strength of macrolides in the spread of erythromycin resistance in S. pyogenes. The role of antibiotics in the selection of resistance has been studied mostly in the hospital context (17,19). However, in the larger, open, dynamic, and more complex community setting, we need larger and more geographically dispersed samples of clinical isolates to be representative of what is being measured, along with reliable and standardized data on antibiotic consumption.…”

Section: Discussionmentioning

confidence: 99%

Pharmacoepidemiological Analysis of Provincial Differences between Consumption of Macrolides and Rates of Erythromycin Resistance among Streptococcus pyogenes Isolates in Spain

et al. 2002

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The M phenotype is by far the most common mechanism of erythromycin resistance among Streptococcus pyogenes isolates in Spain. A geographic analysis of the relationship between within-country differences in the prevalence of M-type resistance to erythromycin in S. pyogenes and the level of consumption of 14-and 15-membered macrolides within different provinces was carried out. From 1998 to 1999, a nationwide multicenter surveillance study yielded 2,039 consecutive pharyngeal isolates of S. pyogenes. Data on antibiotic consumption for the same period were gathered from IMS Health, and the corresponding daily defined doses per 1,000 inhabitants per day were calculated according to the Anatomic Therapeutic Classification index. Macrolide use was subdivided into dosages given three times a day (TID), twice a day (BID), or once a day (OD). Spearman nonparametric correlation coefficients (R) were calculated, and variables proving to be significantly associated (P < 0.1) were introduced into a linear regression model. The total consumption of macrolides presented a significant correlation with the prevalence of resistance (R ‫؍‬ 0.527; P ‫؍‬ 0.032). Neither TID nor BID macrolide consumption showed significant correlations. Only OD consumption had a significance below 0.1. These data are consistent with the hypothesis that only the total consumption of macrolides influences the local rates of M-type erythromycin resistance in S. pyogenes, and subgroups of macrolides seem to have an additive rather than a selective effect by contributing to increasing the final amount of macrolides used. Local variations in total consumption were associated only with BID consumption (R ‫؍‬ 0.849; P ‫؍‬ 0.004). The simple linear regression with total macrolide consumption showed a considerable determination coefficient (R 2 ‫؍‬ 0.678; P ‫؍‬ 0.006). The model explains up to 68% of the measured variation and is clearly better as a predictor of the prevalence of resistance than the mere mean is. By solving the regression equation, the resultant value of 2.2 defined doses per 1,000 inhabitants per day fits with the existence of a critical threshold of selective pressure.

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“…However, it seems reasonable to speculate that a human-driven increase in antibiotic concentrations of a given ecosystems, such as a city, may influence both antibiotic resistance and the microbial population dynamics [21]. Based on this line of thinking and on empirical findings [8,9,[14][15][16][17][18][19], it is reasonably expected to observe a natural derivation of a bacterial population ontogeny under a certain level of exposure to external factors. This seems to be the case for the human commensal E. coli under ciprofloxacin/quinolone exposure, which would then derive to a resistant population and would occasionally be related to human infectious processes.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, it is still unknown how these different environmental and individual determinants are distributed over space and time and their possible influences on a resistance emergence or clonal spread. It has been shown by time-series analysis that antimicrobial usage in a restricted and contained environment, such as a hospital, is temporally linked to the emergence of bacterial resistance [14,15]. Different epidemiological determinants may favour the emergence or establishment of specific resistances in given environments.…”

Section: Reviewmentioning

confidence: 99%

A proposed model for understanding human-bacterial interactions: Space-time approach on community <i>Escherichia coli</i> occurrence and resistance phenomenon

Kiffer¹,

Monteiro²,

Camargo³

et al. 2013

ABB

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Due to ecological effect, it is expected that population exposures to antimicrobial drugs may lead to microorganisms' modifications, occasionally leading to resistance emergence. The present review was based on previous empirical data and on related literature search for quantitative empirical models exploring the human-bacterial interactions. Our previous studies have shown the emergence of ciprofloxacin resistant (CIP-R) Escherichia coli significantly related to previous specific levels of ciprofloxacin consumption and to urban clusters of CIP-R E. coli. The evidence of significant spatial clustering of antimicrobial resistance (ciprofloxacin resistance E. coli) reinforces the ecological effect hypothesis as a major drive in resistance emergence. In other words, human populations submitted to a certain ciprofloxacin or quinolone usage level may affect neighbours within certain geographical areas, not necessarily due to individual antimicrobial intake, but as a driving pressure over a modified circulating E. coli population. Apparently quantitative spatial-temporal analytical frameworks may be better for understanding human-bacterial interactions based on any of their epiphenomena (antimicrobial consumption, antimicrobial resistance, geno/phenotypic characteristics).

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Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis

Cited by 178 publications

References 17 publications

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

Pharmacoepidemiological Analysis of Provincial Differences between Consumption of Macrolides and Rates of Erythromycin Resistance among Streptococcus pyogenes Isolates in Spain

A proposed model for understanding human-bacterial interactions: Space-time approach on community <i>Escherichia coli</i> occurrence and resistance phenomenon

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Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis

Cited by 178 publications

References 17 publications

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

Time-series analysis of the relationship of antimicrobial use and hand hygiene promotion with the incidence of healthcare-associated infections

Pharmacoepidemiological Analysis of Provincial Differences between Consumption of Macrolides and Rates of Erythromycin Resistance among Streptococcus pyogenes Isolates in Spain

A proposed model for understanding human-bacterial interactions: Space-time approach on community &lt;i&gt;Escherichia coli&lt;/i&gt; occurrence and resistance phenomenon

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A proposed model for understanding human-bacterial interactions: Space-time approach on community <i>Escherichia coli</i> occurrence and resistance phenomenon