ReviewNature microbiology2021
The science of the host-virus network.
Review in Nature microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses 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
40 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Exploring the Mosquito-Arbovirus Network: A Survey of Vector Competence Experiments.The American journal of tropical medicine and hygiene · 2023Pooled it
- Worldwide transmission and infection risk of mosquito vectors of West Nile, St. Louis encephalitis, Usutu and Japanese encephalitis viruses: a systematic review.Scientific reports · 2023Pooled it
- A general framework for modeling pathogen transmission in co-roosting host communities.Ecology · 2026Article
- The dual threat: exploring the emergence of human metapneumovirus and SARS-CoV-2 coinfections in respiratory infections.3 Biotech · 2025Review
- Pathogens and planetary change.Nature reviews. Biodiversity · 2025Article
- Bioinformatic Resources for Exploring Human-virus Protein-protein Interactions Based on Binding Modes.Genomics, proteomics & bioinformatics · 2024Review
- Identification and genetic characterization of five novel bat coronaviruses from Yunnan, China.BMC veterinary research · 2024Article
- Virus-host interactions predictor (VHIP): Machine learning approach to resolve microbial virus-host interaction networks.PLoS computational biology · 2024Article
- Predicting host range expansion in parasitic mites using a global mammalian-acarine dataset.Nature communications · 2024Article
- Rapid taxonomic categorization of short, abundant virus sequences for ecological analyses.Ecology and evolution · 2024Article
- Temporal Dynamics, Discovery, and Emergence of Human-Transmissible RNA Viruses.Molecular biology and evolution · 2024Article
- Evaluating the zoonotic potential of RNA viromes of rodents provides new insight into rodent-borne zoonotic pathogens in Guangdong, China.One health (Amsterdam, Netherlands) · 2023Article
- HostNet: improved sequence representation in deep neural networks for virus-host prediction.BMC bioinformatics · 2023Article
- Robust evidence for bats as reservoir hosts is lacking in most African virus studies: a review and call to optimize sampling and conserve bats.Biology letters · 2023Review
- Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots.Nature communications · 2023Article
- Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?FEMS microbiology reviews · 2023Review
- Phylogeographic Aspects of Bat Lyssaviruses in Europe: A Review.Pathogens (Basel, Switzerland) · 2023Review
- Real-time genomics for One Health.Molecular systems biology · 2023Review
- Novel pathogen introduction triggers rapid evolution in animal social movement strategies.eLife · 2023Article
- Concurrent loss of ciliary genesRoyal Society open science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.
Indexed as
Identifiers
34819645What OpenQuestion holds
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.