2.6 Epidemiological relevance of the network
To analyse the causality of the direct pathway transmission, we used the
k-test, comparing the observed connectivity between cases with the
expected distribution of the k-statistic, which is the average number of
observed cases, occurring within one step of an infected case in the
network (k=1) (VanderWaal et al., 2016) . We assessed whether it was
possible that the pattern of observed disease outbreaks (cases) could be
the result of network transmission, thus evaluating itsepidemiological relevance . We used a network of premises
specifying the status of their nodes (not infected=0, infected=1) for
every year and the cumulative period. We then compared the observed
k-statistic with its permuted distribution, where case locations are
randomly reassigned within the network through 1,000 iterations.
Cleaning of the datasets was performed to homogenize premises
classification, and remove inconsistencies, also match outbreaks with
movements between databases. We computed all analyses using R V.3.6.3
(https://cran.r-project.org/)
and software gephi v0.9.2
(https://gephi.org/).