TY - JOUR
T1 - Forecasting ESKAPE infections through a time-varying auto-adaptive algorithm using laboratory-based surveillance data
AU - Ballarin, Antonio
AU - Posteraro, Brunella
AU - Demartis, Giuseppe
AU - Gervasi, Simona
AU - Panzarella, Fabrizio
AU - Torelli, Riccardo
AU - Paroni Sterbini, Francesco
AU - Morandotti, Grazia Angela
AU - Posteraro, Patrizia
AU - Ricciardi, Walter
AU - Gervasi Vidal, Kristian A.
AU - Sanguinetti, Maurizio
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Forecasting
KW - Forecasting
UR - http://hdl.handle.net/10807/65997
U2 - 10.1186/s12879-014-0634-9
DO - 10.1186/s12879-014-0634-9
M3 - Article
SN - 1471-2334
VL - 14
SP - 634
EP - 634
JO - BMC Infectious Diseases
JF - BMC Infectious Diseases
ER -