ReviewProceedings. Biological sciences2021
The three Ts of virulence evolution during zoonotic emergence.
Review in Proceedings. Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed.
- Virulent Parasites Emerge in Hosts With Rising Temperatures.Global change biology · 2026Article
- Article
- Virulence Evolution: Thinking Outside of the Host.Evolutionary applications · 2025Article
- Multispecies interactions and the community context of the evolution of virulence.Proceedings. Biological sciences · 2024Article
- SARS-CoV-2 variant of concern fitness and adaptation in primary human airway epithelia.Cell reports · 2024Article
- Trade-offs shaping transmission of sylvatic dengue and Zika viruses in monkey hosts.Nature communications · 2024Article
- Resource asynchrony and landscape homogenization as drivers of virulence evolution: The case of a directly transmitted disease in a social host.Ecology and evolution · 2024Article
- A meta-analysis highlights the idiosyncratic nature of tradeoffs in laboratory models of virus evolution.Virus evolution · 2024Article
- Variation among strains of Borrelia burgdorferi in host tissue abundance and lifetime transmission determine the population strain structure in nature.PLoS pathogens · 2023Article
- Interspecific host competition and parasite virulence evolution.Biology letters · 2023Article
- Specific resistance prevents the evolution of general resistance and facilitates disease emergence.Journal of evolutionary biology · 2023Article
- Assessing Variation in the Individual-Level Impacts of a Multihost Pathogen.Transboundary and emerging diseases · 2023Article
- The human monkeypox in Saudi Arabia and global tourism.Annals of medicine and surgery (2012) · 2022Article
- 2020 Hindsight: Should evolutionary virologists have expected the unexpected during a pandemic?Evolution; international journal of organic evolution · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
There is increasing interest in the role that evolution may play in current and future pandemics, but there is often also considerable confusion about the actual evolutionary predictions. This may be, in part, due to a historical separation of evolutionary and medical fields, but there is a large, somewhat nuanced body of evidence-supported theory on the evolution of infectious disease. In this review, we synthesize this evolutionary theory in order to provide a framework for clearer understanding of the key principles. Specifically, we discuss the selection acting on zoonotic pathogens' transmission rates and virulence at spillover and during emergence. We explain how the direction and strength of selection during epidemics of emerging zoonotic disease can be understood by a three Ts framework: trade-offs, transmission, and time scales. Virulence and transmission rate may trade-off, but transmission rate is likely to be favoured by selection early in emergence, particularly if maladapted zoonotic pathogens have 'no-cost' transmission rate improving mutations available to them. Additionally, the optimal virulence and transmission rates can shift with the time scale of the epidemic. Predicting pathogen evolution, therefore, depends on understanding both the trade-offs of transmission-improving mutations and the time scales of selection.
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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.