Browsing by Author "Olival KJ"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Filoviruses in bats: current knowledge and future directions.
    (MDPI AG, 17/04/2014) Olival KJ; Hayman DTS
    Filoviruses, including Ebolavirus and Marburgvirus, pose significant threats to public health and species conservation by causing hemorrhagic fever outbreaks with high mortality rates. Since the first outbreak in 1967, their origins, natural history, and ecology remained elusive until recent studies linked them through molecular, serological, and virological studies to bats. We review the ecology, epidemiology, and natural history of these systems, drawing on examples from other bat-borne zoonoses, and highlight key areas for future research. We compare and contrast results from ecological and virological studies of bats and filoviruses with those of other systems. We also highlight how advanced methods, such as more recent serological assays, can be interlinked with flexible statistical methods and experimental studies to inform the field studies necessary to understand filovirus persistence in wildlife populations and cross-species transmission leading to outbreaks. We highlight the need for a more unified, global surveillance strategy for filoviruses in wildlife, and advocate for more integrated, multi-disciplinary approaches to understand dynamics in bat populations to ultimately mitigate or prevent potentially devastating disease outbreaks.
  • Thumbnail Image
    Item
    The future of zoonotic risk prediction
    (The Royal Society, 2021-11-08) Carlson CJ; Farrell MJ; Grange Z; Han BA; Mollentze N; Phelan AL; Rasmussen AL; Albery GF; Bett B; Brett-Major DM; Cohen LE; Dallas T; Eskew EA; Fagre AC; Forbes KM; Gibb R; Halabi S; Hammer CC; Katz R; Kindrachuk J; Muylaert RL; Nutter FB; Ogola J; Olival KJ; Rourke M; Ryan SJ; Ross N; Seifert SN; Sironen T; Standley CJ; Taylor K; Venter M; Webala PW
    In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges?