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Page 30 Jaswant et al. One Health Implement Res 2024;4:15-37 https://dx.doi.org/10.20517/ohir.2023.61

Conclusions and future recommendations
The promise of genetic data for informing rabies control is evident, but its full potential remains untapped
as most publications advocate generic measures that lack specificity derived from sequencing. More
demanding phylodynamic analysis, integrating geographical, epidemiological, and genetic data to yield
more detailed and quantitative understanding, requires greater expertise and computational resources that
have not been accessible in LMICs. Future research would benefit from more WGS as well as leveraging the
power of existing data through analyses that integrate partial and WGS . Applied insights to be gained by
[148]
enhancing rabies surveillance with sequencing, lie in the knowledge of what is circulating and how it is
spreading while we gear towards elimination. A standardised nomenclature system for categorising RABV
diversity, would facilitate clear communication and collaboration among researchers, healthcare
professionals and policymakers . We recommend efforts to develop a robust taxonomic classification
[175]
system under the International Committee on Taxonomy of Viruses (ICTV) that is capable of integrating all
existing and newly identified RABV sequences. Scaling up sequencing in endemic countries, with laboratory
networking and a more unified terminology for exchange of information and updates on new variants and
lineages could enhance risk assessment and control strategies. Genetic results underscore the need for
international and regional coordination in controlling transboundary spread, to accelerate progress and
maintain gains. Expanding sequencing initiatives and fostering collaborative efforts will support the “Zero
by 30” goal, and serve as a prime example of a genomics-informed One Health approach, building capacity
[180]
for the future .

DECLARATIONS
Authors’ contributions
Design: Brunker K, Thumbi SM, Hampson K, Oyugi JO
Literature search: Jaswant G, Bautista CT
Data analysis: Jaswant G, Bautista CT, Hampson K, Brunker K, Ogoti B, Changalucha J, Campbell K,
Mutunga M
Manuscript writing: Jaswant G, Bautista CT
Manuscript editing: Hampson K, Brunker K

Availability of data and materials
Data and code to reproduce the analyses and figures are available from our public repository https://github.
com/RAGE-toolkit/RABV_geneticSurv_review.

Financial support and sponsorship
This work was supported by Wellcome [207569/Z/17/Z, 224520/Z/21/Z to KH], the UK Medical Research
Council [MR/X002047/1 to KB], a Genomics and Modelling for the Control of Viral Pathogens (GeMVi)
fellowship to GJ funded by the National Institute for Health Research (NIHR) [176382], a Philippines
Department of Science and Technology (DOST) and British Council studentship to CB, a training
fellowship in Public Health and Tropical Medicine [110330 to SMT] and Institutional Strategic Support
Fund grants at the University of Glasgow [204820 to KB].

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.