Dynamic generalized linear models for monitoring endemic diseases: moving beyond univariate process monitoring control algorithms

Publikation: KonferencebidragPaperForskningfagfællebedømt

The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control and eradication programmes based on changes in PRRS sero-prevalence was explored. Results showed a declining trend in PRRS sero-prevalence between 2007 and 2014 suggesting that Danish herds are slowly eradicating PRRS. The simulation study demonstrated the flexibility of DGLMs in adapting to changes intrends in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance of endemic and (re-)emerging diseases.
OriginalsprogEngelsk
Publikationsdatomar. 2016
Antal sider11
StatusUdgivet - mar. 2016
BegivenhedAnnual Meeting of the Society for Veterinary Epidemiology and Preventive Medicine - 2016 -
Varighed: 16 mar. 201618 mar. 2017

Konference

KonferenceAnnual Meeting of the Society for Veterinary Epidemiology and Preventive Medicine - 2016
Periode16/03/201618/03/2017

ID: 174127170