🔴 To the best of authors’ knowledge, this is the first
time that an econometric time series model (obtained through a methodology
inspired by the well-known Box–Jenkins technique) is used for characterising EU
prevalence of antimicrobial resistance by means of EARS-Net EU nosocomial
resistance data. Hereby, it has been possible to statistically test if there is
any change in the global behaviour of this data.
🔴 The statistically proven brakes and reversions
observed in the EU antimicrobial resistance prevalence constitute noteworthy
milestones in the tackling of antimicrobial resistance in Europe.
🔴 It has been proven through an AR model
with interventions a growth deceleration in the global increasing tendency of Escherichia coli resistance to
third-generation cephalosporins, resulting in a much softer slope. Concerning Klebsiella pneumoniaeand Escherichia coli resistanceto
fluoroquinolones in the EU, a slowdown in their increasing tendency has also
been proven but, in these cases, towards a stabilization into a constant value.
🔴 It has been proven via an AR econometric
model with interventions a modification in the growing trend of K. pneumoniae and P. aeruginosa resistance to
third-generation cephalosporins that consists in an inversion into a very
slightly descending slope.
🔴 For all these data series, there is a temporal
association between the statistically proven deceleration in their global
tendency and the enforcement of EU referral procedures that optimize and
restrict the use of different antibiotics in the treatment of diseases in human
with bacteria harbouring resistance to cephalosporins or fluoroquinolones (FQ)
constitute a serious hazard to human health.
a methodology based on econometric analysis and the largest European Union (EU)
resistance database (EARS-Net), to model nosocomial antimicrobial resistance
(AMR) in the EU and to detect tendency changes, steps or peaks. The
contribution of legislation based on third-generation cephalosporin (3GC) and
FQ class referrals to resistance rate patterns is evaluated.
Resistance to 3GC and FQ was examined in nosocomial Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa in at least 25
out of 30 EU countries (> 94% population coverage), weighted by their mean
annual population, between 2006 and 2016. Autoregressive integrated moving
average (ARIMA) model analysis, inspired by Box–Jenkins methodology, was
prepared to adjust series to a mathematical model to detect hypothetical
changes in the general behaviour. To the best of the authors’ knowledge, this
is the first study to use ARIMA with interventions to model overall nosocomial
AMR data compiled in EARS-Net.
Econometric ARIMA models statistically prove the
occurence of slowdowns and reversions in the increasing trend of AMR prevalence
in nosocomial E. coli and K. pneumoniae to
3GC and FQ, as well as resistance of P.
aeruginosa to 3GC. The resistance of P.
aeruginosa to FQ exhibited a descending slope. The presented
decreasing trends constitute noteworthy milestones in tackling AMR in Europe.