First, it is worth noting that age is a crucial covariate. The infection probability of all viruses increases with host' age [62] , thus age must strongly participate in the generation of false interactions. This age-dependence is due to both a biological effect (i.e., behaviors and immune defenses may evolve with age, [82, 83] ) and a mechanical effect (i.e., older individuals are more likely to be seropositive because of a longer exposure time). Disentangling both effects would require the use of Susceptible-Infected-Recovered (SIR) models, but was not necessary here. Indeed, to The type I error of the corrected chi-square tests represented here is based on P-value2 but similar results were observed with P-value1 (Fig. S3) . Note that for the logistic regression approach, points resulting from a given sample size were linked to see the effect of the N F /n ratio for different sample sizes (solid line: n = 100, dashed line: n = 200, dotted line: n = 300). The dashed horizontal line represents a type I error of 5%. doi:10.1371/journal.pone.0029618.g001 correct for age in the study of interactions, the important is to model the evolution of the probability of infection with age.