Abstract
Reported data sets on infection of volunteers challenged with wild-type influenza A virus at graded doses are few. Alternatively, we aimed at developing a dose-response assessment for this virus based on the data sets for its live attenuated reassortants. Eleven data sets for live attenuated reassortants that were fit to beta-Poisson and exponential dose-response models. Dose-response relationships for those reassortants were characterized by pooling analysis of the data sets with respect to virus subtype (H1N1 or H3N2), attenuation method (cold-adapted or avian-human gene reassortment), and human age (adults or children). Furthermore, by comparing the above data sets to a limited number of reported data sets for wild-type virus, we quantified the degree of attenuation of wild-type virus with gene reassortment and estimated its infectivity. As a result, dose-response relationships of all reassortants were best described by a beta-Poisson model. Virus subtype and human age were significant factors determining the dose-response relationship, whereas attenuation method affected only the relationship of H1N1 virus infection to adults. The data sets for H3N2 wild-type virus could be pooled with those for its reassortants on the assumption that the gene reassortment attenuates wild-type virus by at least 63 times and most likely 1,070 times. Considering this most likely degree of attenuation, 10% infectious dose of H3N2 wild-type virus for adults was estimated at 18 TCID 50 (95% CI = 8.8-35 TCID 50). The infectivity of wild-type H1N1 virus remains unknown as the data set pooling was unsuccessful. © 2011 Society for Risk Analysis.
Author supplied keywords
Cite
CITATION STYLE
Watanabe, T., Bartrand, T. A., Omura, T., & Haas, C. N. (2012). Dose-Response Assessment for Influenza A Virus Based on Data Sets of Infection with its Live Attenuated Reassortants. Risk Analysis, 32(3), 555–565. https://doi.org/10.1111/j.1539-6924.2011.01680.x
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.