Cessation of hunting shifts transmission networks and increases
R0
We found that reducing hunting mortality had profound effects on
FIVpco transmission dynamics. Even though the
populations in the treatment and stable region were of comparable size
(Table S1), our estimates of R0 for the same virus were
two-fold higher in the treatment region compared to the stable region
(with non-overlapping 95% high probability density intervals indicating
that the difference is significant, Fig. 1). Other model parameters,
such as generation time (time between initial FIVpcoinfection and onward transmission, Fig. S2) and the proportion of
missing cases (Fig. S3) yielded similar estimates in both regions. This
burst of transmission in the treatment population was likely a product
of transmission between males as they were dominant in the network (Fig.
1a). In the treatment population, males had an overall mean weighted
degree (i.e., the number of likely transmission events per individual,
weighted by probability of transmission occurring) double that of
females (0.14 compared to 0.37), only one putative transmission event
occurring between sexes, and no detected female-female transmission
events. When we assessed weighted degree homophily of male-male
transmission events (i.e., the number of edges only between males), and
simulations revealed that the dominance of male-male transmission events
in the network was not random (1000 simulated annealing network
iterations, p < 0.001, Fig. S4a). Putative transmission
events largely occurred when hunting mortality was eliminated (Fig. 1a),
during which time the survival of adults and subadult males was high,
age structure increased, and the abundance of independent pumas
increased (Logan & Runge 2020b). Male survival rates in the hunting
period were also lower than for either sex in the treatment region
(Logan & Runge 2020a). Females were, however, much less connected in
the transmission network in the treatment region compared to the stable
region, where they were more central (Fig. 1b). In contrast to the
treatment region, the stable region showed evidence of transmission from
females to both females and males. Average weighted degree was higher
overall for males than females in the stable region (0.46 vs 0.29). Even
though weighted female-female degree homophily was higher between
regions (0 vs 0.05), our simulations show that we could not reject the
null hypothesis that this difference was by chance (p = 0.692,
Fig. S4b). Female-to-female transmission events occurred between highly
related females supporting our previous findings of a significant role
of host relatedness in FIV spread for puma living in this region
(Fountain-Jones et al. 2019). Taken together, our results
indicate that lower hunting mortality was associated with an increase in
the number of transmission events and a transmission shift towards
males.
After hunting was prohibited, the greater survival and increasing
abundance of males probably resulted in greater competition between
males for mates. As the dominant transmission mode for
FIVpco is considered to be via aggressive contacts
(VandeWoude & Apetrei 2006), increased male competition for mates
appears a probable explanation for the change in transmission dynamics.
Further interrogation of our transmission network supports this theory,
as in all but two instances, male-to-male transmission occurred between
individuals with overlapping territories in the treatment region (Fig.
2/S5/S6). One transmission pair was unusual in having less spatial
proximity, yet one puma of this pair was a likely immigrant to the
region (M133) and could have passed through M73’s territory at some
point (Fig. 2). With the exception of M73 (~6 y.o. at
time of infection), all individuals involved in these transmission
events were between 1-3 y.o., which is a period when males are
establishing new territories and are starting to compete for access to
females (Logan & Sweanor 2001; Hornocker & Negri 2010). Our results
suggest it is unlikely that these males transmitted to each other prior
to dispersal or via maternal or paternal contacts—since these
individuals were not related based on genomic data (Trumbo et al.2019). While our estimates suggest that we were able to sample
approximately 40% of the FIVpco infections in both
regions (Fig. S3)—arguably good coverage for secretive, free-ranging
wildlife—our models account for this type of missing data (Didelotet al. 2017). For example, nearly all putative transmission
events we identified from our transmission networks were between
individuals on the landscape at the same time and in most cases were
captured in close spatial proximity to each other. The biological
plausibility of these transmission events demonstrates the power of
adapting transmission network models to trace transmission and gain
epidemiological insights in systems that are difficult to observe.