Sample Size Considerations for One-to-One Animal Transmission Studies of the Influenza A Viruses

Background: Animal transmission studies can provide important insights into host, viral and environmental factors affecting transmission of viruses including influenza A. The basic unit of analysis in typical animal transmission experiments is the presence or absence of transmission from an infectious animal to a susceptible animal. In studies comparing two groups (e.g. two host genetic variants, two virus strains, or two arrangements of animal cages), differences between groups are evaluated by comparing the proportion of pairs with successful transmission in each group. The present study aimed to discuss the significance and power to estimate transmissibility and identify differences in the transmissibility based on one-to- one trials. The analyses are illustrated on transmission studies of influenza A viruses in the ferret model. Methodology/Principal Findings: Employing the stochastic general epidemic model, the basic reproduction number, R-0, is derived from the final state of an epidemic and is related to the probability of successful transmission during each one-to-one trial. In studies to estimate transmissibility, we show that 3 pairs of infectious/susceptible animals cannot demonstrate a significantly higher transmissibility than R-0 = 1, even if infection occurs in all three pairs. In comparisons between two groups, at least 4 pairs of infectious/susceptible animals are required in each group to ensure high power to identify significant differences in transmissibility between the groups. Conclusions: These results inform the appropriate sample sizes for animal transmission experiments, while relating the observed proportion of infected pairs to R-0, an interpretable epidemiological measure of transmissibility. In addition to the hypothesis testing results, the wide confidence intervals of R-0 with small sample sizes also imply that the objective demonstration of difference or similarity should rest on firmly calculated sample size.