ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021
The future of zoonotic risk prediction.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of health risk assessment in Africa's bushmeat trade: Are there any risks assessed?PLoS neglected tropical diseases · 2026Pooled it
- Article
- Review
- Post-pandemic changes in population immunity have reduced the likelihood of emergence of zoonotic coronaviruses.Nature communications · 2026Article
- Human-wildlife conflict and its impacts on livelihoods, health, and the environment in Chebera Churchura National Park, Southwest Ethiopia: a phenomenological study using a One Health approach with an urgent call for action.One health outlook · 2026Article
- Public health risks of traditional zootherapeutic practices in Africa.One health (Amsterdam, Netherlands) · 2025Review
- The Effect of Climate Change on Emergence and Evolution of Zoonotic Diseases in Asia.Zoonoses and public health · 2025Review
- Upscaling effects on infectious disease emergence risk emphasize the need for local planning in primary prevention within biodiversity hotspots.Scientific reports · 2025Article
- Mammalian antiviral proteins ZAP and KHNYN can independently restrict CpG-enriched avian viruses.PLoS biology · 2025Article
- Mammalian ZAP and KHNYN can independently restrict CpG-enriched avian viruses.bioRxiv : the preprint server for biology · 2025Article
- A global map of travel time to access veterinarians.Nature communications · 2025Article
- Deciphering Probabilistic Species Interaction Networks.Ecology letters · 2025Review
- Hidden challenges in evaluating spillover risk of zoonotic viruses using machine learning models.Communications medicine · 2025Article
- Wildlife hunting and the increased risk of leprosy transmission in the tropical Americas: a pathogeographical study.Infectious diseases of poverty · 2025Article
- Viral genome sequencing methods: benefits and pitfalls of current approaches.Biochemical Society transactions · 2024Review
- Emerging and Endemic Infections in Wildlife: Epidemiology, Ecology and Management in a Changing World.Pathogens (Basel, Switzerland) · 2024Article
- Temporal Dynamics, Discovery, and Emergence of Human-Transmissible RNA Viruses.Molecular biology and evolution · 2024Article
- How do host population dynamics impact Lyme disease risk dynamics in theoretical models?PloS one · 2024Article
- One Health governance: theory, practice and ethics.Science in One Health · 2024Review
- Uncovering the Holocene roots of contemporary disease-scapes: bringing archaeology into One Health.Proceedings. Biological sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
33 authors.
Funding
Abstract
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? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.