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Jaswant et al. One Health Implement Res 2024;4:15-37 https://dx.doi.org/10.20517/ohir.2023.61 Page 29

phylogeographic analyses. Most used genetic relatedness of viruses from different locations, based on
interpreting phylogenies, without quantitative inference. When carried out, phylogeographic analyses
illuminated environmental features as both natural barriers and drivers of spread, with human-related
factors driving dispersal towards more populated and accessible areas. These analyses have potential to
guide spatial targeting of vaccination, and enhancement of surveillance in at-risk areas [18,89,170] . Frequent
reintroductions highlighted epidemiological connectivity of landscapes over which vaccination needs
scaling and coordination across political/administrative boundaries , with more recent studies showing
[13]
how sequencing can be used to monitor the impacts of and threats to dog vaccination programmes [13,98,149] .

Broader context
Our review has relevance to the broader application of genetic surveillance to pathogens. The recent
increase in third-generation sequencing of RABV has potential to further expand given the focus on
sequencing capacity for pandemic response. Deployable sequencing has become a key component of
outbreak response, with portable lab equipment and sequencing platforms facilitating on-site, real-time,
genomic surveillance [33,40,43] . Feasibility and utility of deployable sequencing for rabies surveillance has been
demonstrated [46,98,149] , with use of Nanopore’s MinIon reducing costs and turnaround times [34,46] , and
comprehensive protocols, bioinformatic pipelines and open-source user-friendly software and classification
tools becoming more available [171-175] . Sequencing for routine surveillance of endemic zoonoses could build
and sustain pandemic preparedness at the human-animal-environment interface. While COVID-19
accelerated application of genomic surveillance, it also highlighted stark global disparities in access to
sequencing, and bioinformatic expertise remains a bottleneck [176,177] . Since the pandemic investment in
[178]
LMICs has begun but much more is required .

RABV also serves as a model system to understand and manage cross-species transmission and spillover.
Instances highlighted in this review, reflect a broader ecological pattern with significant public health and
ecological implications. Spillovers can be precursors to larger outbreaks, as evidenced by recent epidemics
of Influenza, Ebola, Zika, and COVID-19, while swift sequencing and analysis can inform public health
responses and containment [33-35,40,43] .

Limitations of the study
While we endeavoured to comprehensively review global regions with endemic canine rabies, it is
important to acknowledge the limitations inherent in our study. Genetic studies on rabies demonstrating
progress in its elimination, conducted in countries or regions such as Canada, the USA, and Eastern Europe,
where dog rabies has been eliminated for some time, were not included. This approach may have limited
our ability to discover additional interventions and significant insights from the perspective of these
countries. Our review, while focusing on publications from endemic regions may have failed to identify
publications documenting importations in rabies-free countries. We supplemented our searches by
manually adding relevant instances (~10% of papers), but some studies, particularly those published in non-
English journals, may have been overlooked. Despite substantial manual curation efforts in RABV-GLUE to
[179]
enhance GenBank metadata , inconsistencies and gaps persist, potentially hindering data mining
efficiency for sequences not associated with a publication. We also only retrospectively and manually
identified some studies that did not report the use of sequencing in their abstract. Not all papers
transparently report methods, in particular many did not report locations where sequencing was
undertaken which we assumed was done in-country. We therefore likely overestimated sequencing capacity
for some countries, though we expect our conclusions are robust. We included only studies published after
the year 2000, which limited the scope of the study, as it did not capture some of the earliest genomic
studies conducted on RABV. However, this also meant most of the methods reported were more
comparable and aligned with the 1st, 2nd and 3rd generation sequencing platforms defined in Table 1.