Comparing the historical limits method with regression models for weekly monitoring of national notifiable diseases reports.
J Biomed Inform
; 76: 34-40, 2017 Dec.
Article
em En
| MEDLINE
| ID: mdl-29054709
ABSTRACT
To compare the performance of the standard Historical Limits Method (HLM), with a modified HLM (MHLM), the Farrington-like Method (FLM), and the Serfling-like Method (SLM) in detecting simulated outbreak signals. We used weekly time series data from 12 infectious diseases from the U.S. Centers for Disease Control and Prevention's National Notifiable Diseases Surveillance System (NNDSS). Data from 2006 to 2010 were used as baseline and from 2011 to 2014 were used to test the four detection methods. MHLM outperformed HLM in terms of background alert rate, sensitivity, and alerting delay. On average, SLM and FLM had higher sensitivity than MHLM. Among the four methods, the FLM had the highest sensitivity and lowest background alert rate and alerting delay. Revising or replacing the standard HLM may improve the performance of aberration detection for NNDSS standard weekly reports.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Vigilância da População
/
Doenças Transmissíveis
/
Surtos de Doenças
Tipo de estudo:
Prognostic_studies
/
Screening_studies
Limite:
Humans
País/Região como assunto:
America do norte
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article