Modeling the spread of infectious disease using genetic information within a marked branching process.
Stat Med
; 28(29): 3626-42, 2009 Dec 20.
Article
em En
| MEDLINE
| ID: mdl-19739239
ABSTRACT
Accurate assessment of disease dynamics requires a quantification of many unknown parameters governing disease transmission processes. While infection control strategies within hospital settings are stringent, some disease will be propagated due to human interactions (patient-to-patient or patient-to-caregiver-to-patient). In order to understand infectious transmission rates within the hospital, it is necessary to isolate the amount of disease that is endemic to the outside environment. While discerning the origins of disease is difficult when using ordinary spatio-temporal data (locations and time of disease detection), genotypes that are common to pathogens, with common sources, aid in distinguishing nosocomial infections from independent arrivals of the disease. The purpose of this study was to demonstrate a Bayesian modeling procedure for identifying nosocomial infections, and quantify the rate of these transmissions. We will demonstrate our method using a 10-year history of Morexella catarhallis. Results will show the degree to which pathogen-specific, genotypic information impacts inferences about the nosocomial rate of infection.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
2_ODS3
Base de dados:
MEDLINE
Assunto principal:
Infecção Hospitalar
/
Doenças Transmissíveis
/
Modelos Estatísticos
/
Teorema de Bayes
/
Modelos Genéticos
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Stat Med
Ano de publicação:
2009
Tipo de documento:
Article