This study aimed to determine dose-response (DR) curve of avian influenza (AI) virus to predict the probability of illness or adverse health effects that may result from exposure to a pathogenic microorganism in a quantitative microbial risk assessment. To determine the parametric DR relationship of several strains of AI virus, 7 feeding trial data sets challenging humans (5 sets) and chickens (2 sets) for strains of H3N2 (4 sets), H5N1 (2 sets) and H1N1 (1 set) from the published literatures. Except for one data set (study with intra-tracheal inoculation for data set no. 6), all were obtained from the studies with intranasal inoculation. The data were analyzed using three types of DR model as the basis of heterogeneity in infectivity of AI strains in humans and chickens: exponential, beta-binomial and beta-Poisson. We fitted to the data using maximum likelihood estimation to get the parameter estimates of each model. The alpha and beta values of the beta-Poisson DR model ranged 0.06-0.19 and 1.7-48.8, respectively for H3N2 strain. Corresponding values for H5N1 ranged 0.464-0.563 and 97.3-99.4, respectively. For H1N1 the parameter values were 0.103 and 12.7, respectively. Using the exponential model, r (infectivity parameter) ranged from $1.6{ imes}10^{-8}$ to $1.2{ imes}10^{-5}$ for H3N2 and from $7.5{ imes}10^{-3}$ to $4.0{ imes}10^{-2}$ for H5N1, while the value was $1.6{ imes}10^{-8}$ for H1N1. The beta-Poisson DR model provided the best fit to five of 7 data sets tested, and the estimated parameter values in betabinomial model were very close to those of beta-Poisson. Our study indicated that beta-binomial or beta-Poisson model could be the choice for DR modeling of AI, even though DR relationship varied depending on the virus strains studied, as indicated in prior studies. Further DR modeling should be conducted to quantify the differences among AI virus strains.