Uncovering the endemic circulation of rabies in Cambodia

Abstract

In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within‐Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.

How fast are viruses spreading in the wild?

“…spatial heterogeneity in the sampling effort) nor border effects, which can also affect the target statistics. For instance, Layan and colleagues have illustrated that the extent of the study area can impact the diffusion coefficient estimates [48]. As an interpretation, they put forward that “larger sampling areas are expected to be associated with higher probabilities to sample long-distance dispersal events that will, on average, more likely correspond to fast dispersal events than short-distance dispersal events” [48].…”

“…For instance, Layan and colleagues have illustrated that the extent of the study area can impact the diffusion coefficient estimates [48]. As an interpretation, they put forward that "larger sampling areas are expected to be associated with higher probabilities to sample long-distance dispersal events that will, on average, more likely correspond to fast dispersal events than short-distance dispersal events" [48]. As detailed in Table S1, we however see that the different datasets analysed here encompass a large range of study area sizes that are not necessarily following the trend of diffusion coefficient estimates.…”