Dynamic generalized linear models for monitoring endemic diseases: moving beyond univariate process monitoring control algorithms
Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt
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.
|Status||Udgivet - mar. 2016|
|Begivenhed||Annual Meeting of the Society for Veterinary Epidemiology and Preventive Medicine - 2016 - |
Varighed: 16 mar. 2016 → 18 mar. 2017
|Konference||Annual Meeting of the Society for Veterinary Epidemiology and Preventive Medicine - 2016|
|Periode||16/03/2016 → 18/03/2017|