Design and analysis of small-scale transmission experiments with animals

Abstract

Interactions between pathogens and hosts at the population level should be considered when studying the effectiveness of control measures for infectious diseases. The advantage of doing transmission experiments compared to field studies is that they offer a controlled environment in which the effect of a single factor can be investigated, while variation due to other factors is minimized. This paper gives an overview of the biological and mathematical aspects, bottlenecks and solutions of developing and executing transmission experiments with animals. Different methods of analysis and different experimental designs are discussed. Final size methods are often used for analysing transmission data, but have never been published in a refereed journal; therefore, they will be described in detail in this paper. We hope that this information is helpful for scientists who are considering performing transmission experiments.

Fig. 1

Evaluation of a transmission experiment with a treatment and control group. If the experiment only consists of a control group (i.e. to estimate transmission parameters) the tree will not include the subtree about the treatment group.

Fig. 2

Theoretical results of a transmission experiment that is stopped (dashed vertical line) before a final size situation has been reached in all trials (left panel) and two possible end situations that could have been observed when the final-size situations have been reached (right panels).

Fig. 3

The final-size distributions of the stochastic SIR model for R=5 for the experimental designs I₀=1, S₀=9 and I₀=5, S₀=5.

Fig. 4

The 95% confidence interval of the estimated R value of 1000 simulated experiments of different sizes, given S₀ (total)=36; I₀ (total)=36; N₀ (total)=72; S₀≈I₀, in which R=0·5, 1·0 or 1·5, respectively.

Fig. 5

Decision tree illustrating which method analysis to use.