Browsing by Author "Sitharam, Nikita"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Enhancing genomic visualisations for epidemics to inform the public health response
    (Stellenbosch : Stellenbosch University, 2024-03) Sitharam, Nikita; De Oliveira, Tulio ; Baxter, Cheryl; Xavier, Joicymara; Stellenbosch University. Faculty of Medicine and Health Sciences. Centre for Bioinformatics & Computational Biology.
    ENGLISH ABSTRACT: Introduction: Infectious disease prevention relies on effective disease surveillance and communication in preventing and controlling epidemics. An important tool that is utilised for communication, in public health informatics, is a computational dashboard. Public health dashboards are an effective way of presenting complex biological data in a concise and visual manner. This decreases the knowledge gap between researchers and the public, and allows for stakeholders and policy-makers to make informed decisions. Genomic surveillance of arthropod-borne viruses has increased due to the advancements in sequencing technologies. However, the African continent remains challenged in controlling the spread of these viruses and its vectors, due to constrained resources. Climate Amplified Diseases and Epidemics (CLIMADE) Africa is a consortium that aims to increase the genomic surveillance of arboviruses in Africa through the sharing of protocols, software applications, and capacity building. Purpose: The purpose of this study was to build the CLIMADE Africa dashboard to communicate genomic data for the three most medically-prevalent arboviruses on the African continent, Dengue Virus, Chikungunya Virus, and Zika Virus. Communicating this data could help guide the public health response in Africa. The SARS-CoV-2 Africa dashboard was enhanced by the addition of an interactive phylogenetic visualisation. This increased the amount of complex information provided on the dashboard, in a clear and user-friendly manner. Methodology: The CLIMADE Africa dashboard was produced by adapting the computational architecture of the SARS-CoV-2 Africa dashboard. The arboviral data presented was sourced from the Bacterial and Viral Bioinformatics Resource Center. The data was processed using Pandas in Python, and implemented into the dashboard using the Pycharm application. The Nextstrain SARS-CoV-2 phylogenetic build, for the SARS-CoV-2 Africa dashboard, was produced using Nextstrain’s ncov workflow. This was implemented into the filter panel on the dashboard. Results: The CLIMADE Africa dashboard was created as an easy-to-use tool that showcases the genomic epidemiology of the three most prevalent arboviruses (Dengue Virus, Chikungunya Virus, and Zika Virus) in Africa, in a digestible manner and in near-real time. This dashboard is open source and the code is available at this GitHub repository. The phylogenetic Nextstrain build presented on the SARS-CoV-2 Africa dashboard, presents a full picture of the genomic landscape of the pandemic on the African continent. Conclusion: The information extracted from the CLIMADE Africa dashboard highlights the difference between reported outbreaks and genomic surveillance on the African continent. This could be used to improve surveillance, which could then potentially improve the public health response to these arboviruses. Dashboards need to be maintained, updated, and enhanced in order to be effective at communicating accurate and up-to-date scientific information. Thus, introducing a Nextstrain build for the SARS-CoV-2 Africa dashboard, allows for more complex information to be presented in a digestible way. Future work for this study could include fully automating the data acquisition and curation for the CLIMADE Africa dashboard and fully embedding the Africa-specific Nextstrain phylogenetic build in the SARS- CoV-2 Africa dashboard.