ArticleJournal of the Royal Society, Interface2010
Risk factors for the evolutionary emergence of pathogens.
Article in Journal of the Royal Society, Interface, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers.
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
35 citing papers in PubMed.
- Pathogen host jump risk is not predicted by spillover rate, but rather by novelty.PLoS biology · 2026Article
- Spillover: Mechanisms, Genetic Barriers, and the Role of Reservoirs in Emerging Pathogens.Microorganisms · 2024Review
- Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England.PLoS pathogens · 2024Article
- Building pyramids against the evolutionary emergence of pathogens.Proceedings. Biological sciences · 2024Article
- Article
- Spreading processes with mutations over multilayer networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Swine coronaviruses (SCoVs) and their emerging threats to swine population, inter-species transmission, exploring the susceptibility of pigs for SARS-CoV-2 and zoonotic concerns.The veterinary quarterly · 2022Review
- The source of individual heterogeneity shapes infectious disease outbreaks.Proceedings. Biological sciences · 2022Article
- Multi-scale modelling reveals that early super-spreader events are a likely contributor to novel variant predominance.Journal of the Royal Society, Interface · 2022Article
- Equitable access to COVID-19 vaccines makes a life-saving difference to all countries.Nature human behaviour · 2022Article
- Bacterial-viral interactions: a factor that facilitates transmission heterogeneities.FEMS microbes · 2022Article
- Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.PLoS computational biology · 2021Article
- The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic.Current biology : CB · 2021Review
- Evolution, Ecology, and Zoonotic Transmission of Betacoronaviruses: A Review.Frontiers in veterinary science · 2021Review
- A systemic approach to assess the potential and risks of wildlife culling for infectious disease control.Communications biology · 2020Review
- The effects of evolutionary adaptations on spreading processes in complex networks.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Genetic Paths to Evolutionary Rescue and the Distribution of Fitness Effects Along Them.Genetics · 2020Article
- Infectious Disease Modeling and Epidemic Response Measures Analysis Considering Asymptomatic Infection.IEEE access : practical innovations, open solutions · 2020Article
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- Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent outbreaks of novel infectious diseases (e.g. SARS, influenza H1N1) have highlighted the threat of cross-species pathogen transmission. When first introduced to a population, a pathogen is often poorly adapted to its new host and must evolve in order to escape extinction. Theoretical arguments and empirical studies have suggested various factors to explain why some pathogens emerge and others do not, including host contact structure, pathogen adaptive pathways and mutation rates. Using a multi-type branching process, we model the spread of an introduced pathogen evolving through several strains. Extending previous models, we use a network-based approach to separate host contact patterns from pathogen transmissibility. We also allow for arbitrary adaptive pathways. These generalizations lead to novel predictions regarding the impact of hypothesized risk factors. Pathogen fitness depends on the host population in which it circulates, and the 'riskiest' contact distribution and adaptive pathway depend on initial transmissibility. Emergence probability is sensitive to mutation probabilities and number of adaptive steps required, with the possibility of large adaptive steps (e.g. simultaneous point mutations or recombination) having a dramatic effect. In most situations, increasing overall mutation probability increases the risk of emergence; however, notable exceptions arise when deleterious mutations are available.
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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.