Forecasting ESKAPE infections through a time-varying auto-adaptive algorithm using laboratory-based surveillance data.
BMC Infect Dis
; 14: 634, 2014 Dec 06.
Article
in En
| MEDLINE
| ID: mdl-25480675
ABSTRACT
BACKGROUND:
Mathematical or statistical tools are capable to provide a valid help to improve surveillance systems for healthcare and non-healthcare-associated bacterial infections. The aim of this work is to evaluate the time-varying auto-adaptive (TVA) algorithm-based use of clinical microbiology laboratory database to forecast medically important drug-resistant bacterial infections.METHODS:
Using TVA algorithm, six distinct time series were modelled, each one representing the number of episodes per single 'ESKAPE' (E nterococcus faecium, S taphylococcus aureus, K lebsiella pneumoniae, A cinetobacter baumannii, P seudomonas aeruginosa and E nterobacter species) infecting pathogen, that had occurred monthly between 2002 and 2011 calendar years at the Università Cattolica del Sacro Cuore general hospital.RESULTS:
Monthly moving averaged numbers of observed and forecasted ESKAPE infectious episodes were found to show a complete overlapping of their respective smoothed time series curves. Overall good forecast accuracy was observed, with percentages ranging from 82.14% for E. faecium infections to 90.36% for S. aureus infections.CONCLUSIONS:
Our approach may regularly provide physicians with forecasted bacterial infection rates to alert them about the spread of antibiotic-resistant bacterial species, especially when clinical microbiological results of patients' specimens are delayed.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Bacterial Infections
/
Algorithms
/
Gram-Negative Bacteria
/
Gram-Positive Bacteria
Type of study:
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Limits:
Female
/
Humans
/
Male
/
Middle aged
Country/Region as subject:
Europa
Language:
En
Journal:
BMC Infect Dis
Journal subject:
DOENCAS TRANSMISSIVEIS
Year:
2014
Document type:
Article
Affiliation country:
Italy