Boven, M., van

Buist, W.G.

Engel, B.

Goot, J.A., van der

Koch, G.

Stegeman, A.

Water, S.G.P., van de

English

Wageningen Yield 

  
ISVEE/153
 
Validation of diagnostic tests for detection of avian influenza in vaccinated chickens using 
Bayesian analysis 
 
Van der Goot JA (1), Engel B (2), Van de Water SGP (1), Buist W (2), De Jong MCM (3), 
Koch G (1), Van Boven M (4), Stegeman JA (5)  
  
(1) Central Veterinary Institute (CVI), Wageningen University & Research Center, 
Lelystad, The Netherlands, (2) Biometris, Wageningen University & Research Center, 
Wageningen, The Netherlands (3) Quantitative Veterinary Epidemiology (QVE), 
Wageningen University, The Netherlands (4) Centre for Infectious Disease Control, 
National Institute for Public Health and the Environment, Bilthoven, The Netherlands (5) 
Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands  
 
 
Vaccination is an attractive tool for the prevention of outbreaks of highly pathogenic avian 
influenza in domestic birds. It is known, however, that vaccination does not always 
provide perfect protection against infection, and that the detection of infection in 
vaccinated birds can be problematic. This implies that there is a risk of silent spread of 
virus in vaccinated populations (Savill et al., 2006). Therefore, it is increasingly believed 
that vaccination programs should always be accompanied by active surveillance.  
     Surveillance programs can be based on the use of serological DIVA (differentiating 
infected from vaccinated animals) tests. However, validation of serological DIVA tests is 
difficult to perform, because there is no gold standard test, and the true disease status of 
the animals is unknown. Here, we investigate the characteristics of three serological tests 
for avian influenza (immunofluorescent antibody test (iIFAT), neuraminidase inhibition 
(NI) assay, and NS1 ELISA) that are able to differentiate infected from vaccinated 
animals. To this end, data of H7N7 infection experiments are analyzed using Bayesian 
methods of inference (Enoe et al., 2000; Engel et al., 2008). These Bayesian methods 
enable validation of the tests in the absence of a gold standard, and allow one to take into 
account that infected birds do not always develop antibodies after infection. 
     The results show that the N7 iIFAT and the NI assay have sensitivities for detecting 
antibodies of 0.95 (95% CI: 0.89-0.98) and 0.93 (95% CI: 0.78-0.99), but substantially 
lower sensitivities for detecting infection: 0.64 (95% CI: 0.52-0.75) and 0.63 (95% CI: 
0.49-0.75). The NS1 ELISA has a low sensitivity for both detecting antibodies (0.55 (95% 
CI: 0.34-0.74)) and infection (0.42 (95% CI: 0.28-0.56)). The estimated specificities of 
the N7 iIFAT and the NI assay are 0.92 (95% CI: 0.87-0.95) and 0.91 (95% CI: 0.85-
0.95), and 0.82 (95% CI: 0.74-0.87) for the NS1 ELISA. Additionally, our analyses 
suggest a strong association between the duration of virus excretion of infected birds and 
the probability to develop antibodies. 
Engel, B., Buist, W., Orsel, K., Dekker, A. de Clerq, K., Grazioli, S., Van Roermund, H., 
2008. A Bayesian evaluation of six diagnostic tests for foot-and-mouth disease for 
vaccinated and non-vaccinated cattle. Preventive veterinary medicine 86, 124-138.  
Enoe, C., Georgiadis, M.P., Johnson, W.O., 2000. Estimation of sensitivity and specificity 
of diagnostic tests and disease prevalence when the true disease state is unknown. 
Preventive veterinary medicine 45, 61-81. 
Savill, N.J., St Rose, S.G., Keeling, M.J., Woolhouse, M.E.J., 2006. Silent spread of H5N1 
in vaccinated poultry. Nature 442, 757-757. 
  
  


Validation of diagnostic tests for detection of avian influenza in vaccinated chickens using Bayesian analysis

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Validation of diagnostic tests for detection of avian influenza in vaccinated chickens using Bayesian analysis

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