). This means that the effect of age on FIV prevalence observed here is not due to the accumulation of FIV cases with age. The p values are rather large (p = 0.02 and p = 0.043), especially considering the large number of tests performed. Unfortunately, we cannot apply a simple Bonferroni correction for multiple tests because of dependence among the different tests performed. Due to the strong correlation between the mean age of males and females, it is not surprising that both variables have the same significant effect on the male-to-female transmission rate. It seems more likely that only one of the two variables has a real biological effect, the effect of the other one being due to correlation. Due to the strong correlation between the two variables, we cannot rule out a role for mean age of males on the male-to-female transmission rate. H neigh e neigh F , respectively). Under these circumstances, we find no significant improvement in the models compared to H 0 (see Table 2 ). In summary, we found two potential risk factors for FIV: the mean ages of males and females that influence the FIV prevalence in females. These two factors are certainly linked because a large correlation exists between the two variables. Yet, considering the number of tests we performed and the relatively high p values we obtained, we cannot exclude the possibility that the simplest model We remove female prevalence data from the analysis because there is no female to male transmission of the virus. We determine the confidence region of the transmission rates b M and e M, of the ''male transmission model'' parameter space for three different values of the proportion of non-captured cats: p NC = 0.30 (Fig. 4a,  b) , p NC = 0.15 and p NC = 0.45 (Fig. 4b) . In Fig. 4b we superimpose these three confidence regions; only showing their boundaries. We conclude that p NC has a slight impact on the edge of the confidence region. If we project the region onto the b M 0 axis we obtain a 95% confidence interval for the male-to-male transmission rate b M ([1. Finally we look at the impact of the external transmission rate e M on FIV spread in already infected populations. We estimate the average size of a population as the mean number of observed males per population multiplied by 1+p NC , which is equal to 21 for p NC = 0.30. We divide the mean number of infected hosts calculated with the model for a population of average size conditioned to FIV non-extinction by the value obtained with the same parameters, but with an external transmission rate a hundred times lower. We denote R as this value minus one