Session 3 ePoster: Using Nextstrain to Visualize Genomic Data from the 2022 Sudan Ebolavirus Outbreak in Uganda

On September 20th, 2022, the 5th Sudan ebolavirus (SUDV) outbreak since 2000 was declared in Uganda. Sudan ebolavirus is a single-stranded negative-sense RNA (ssRNA) virus in the Filovirus family that encodes seven viral proteins and has a case fatality rate of approximately 50%. Filoviruses are endemic to Africa and are hypothesized to circulate in Pteropodid bats as their natural reservoirs and can infect humans and nonhuman primates.

The SUDV outbreak originated in the Mubende district of Central Uganda – no data currently exists as to how the outbreak started but zoonotic spread from a reservoir animal is one possible hypothesis. After a duration 113 days, the Uganda Ministry of Health announced the end of the outbreak on January 11th, 2023. During the outbreak, 142 confirmed and 22 probable cases were officially identified. Next-generation sequencing (NGS) was performed at the Uganda Virus Research Institute (UVRI) Viral Hemorrhagic Fever Lab using RNA extracted from confirmed cases by either an unbiased method on Illumina technologies, or an amplicon-based method using Oxford Nanopore technologies. Overall, UVRI attempted sequencing on 129 specimens and generated 120 genomes with greater than 90% coverage from 114 unique cases.

Here, we present how the Nextstrain tool was developed and utilized during the SUDV outbreak to share sequence and related meta-data. The Nextstrain dashboard presented phylogenetic trees, phylogeographic maps, mutation prevalence, and mutation rate. De-identified data is publicly available on Nextrain’s website allowing for efficient real-time data
sharing. The display of geographic location, time, and sample ID also makes meta-data readily available and easily interpreted; features that are critical when responding to an outbreak.

As outbreak data were collected, naturally occurring genotypic differences between Mubende cases and other districts became apparent, indicating mutation over time. These data can be used to evaluate competitive fitness between SUDV variants and design vaccines. Genotypic differences among sequences also made it possible to delineate unknown epidemiological linkages or transmission events. Finally, the calculated intra-outbreak mutation rate displayed in this Nextstrain build may help characterize the source of a future re-emergence event.