Specifically for the experiment, the models related RMR, MMR and the other output measures to the interaction of experimental group (‘experimental’ and ‘control’) and phases of the experiment (‘before’ experimental infection, during ‘acute’ or ‘chronic’ phase of infection), while controlling for repeated measurements. We applied Bayesian simulation techniques to compute posterior probabilities for differences between experimental groups. All analyses were run in R (v. 3.3.2) , using the R-packages ‘arm’ (v. 1.9–3)  and ‘lme4’ (v. 1.1-12) . As the lmer function does not provide p-values, we considered factors with absolute t-values greater than 2 significant at the p < 0.05 level following suggestions in .