Preliminary evaluation of diagnostic tests for avian influenza using the Markov Chain Monte Carlo (MCMC) Method in an emergency surveillance.
In June 2005, an outbreak of avian influenza (AI) caused by a low pathogenic H5N2 virus was identified in Japan. A serological surveillance was conducted because the infected chickens did not show any clinical signs. The Markov Chain Monte Carlo Method was used to evaluate the performances of serological HI and AGP tests because there was not enough time when the surveillance was initiated to conduct a test evaluation. The sensitivity of the AGP test (0.67) was lower than that of the HI test (0.99), while the specificities were high for both tests (0.96 for AGP and 0.90 for HI). Based on the low sensitivity of the AGP test, the HI test was used for primary screening in later stages of the epidemic.
Yamamoto
Takehisa
T
Epidemiological Research Team, National Institute of Animal Health, Kannondai, Ibaraki-ken, Japan.
Tsutsui
Toshiyuki
T
Nishiguchi
Akiko
A
Kobayashi
Sota
S
Tsukamoto
Kenji
K
Saito
Takehiko
T
Mase
Masaji
M
Okamatsu
Masatoshi
M
D000818:Animals; D001717:Birds / Q000821:virology*; D004196:Disease Outbreaks / Q000662:veterinary*; D053125:Influenza A Virus, H5N2 Subtype / Q000276:immunology / Q000302:isolation & purification; D005585:Influenza in Birds / Q000175:diagnosis* / Q000453:epidemiology / Q000821:virology*; D007564:Japan / Q000453:epidemiology; D008390:Markov Chains; D009010:Monte Carlo Method; D011159:Population Surveillance; D012680:Sensitivity and Specificity