ArticlePLoS computational biology2013
How the dynamics and structure of sexual contact networks shape pathogen phylogenies.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed.
- Trial
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Sexual transmission of urogenital bacteria: whole metagenome sequencing evidence from a sexual network study.mSphere · 2024Article
- AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS.bioRxiv : the preprint server for biology · 2024Article
- AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.Frontiers in bioinformatics · 2024Article
- Phylogenetic identification of influenza virus candidates for seasonal vaccines.Science advances · 2023Article
- Predicting the short-term success of human influenza virus variants with machine learning.Proceedings. Biological sciences · 2020Article
- Assessing biases in phylodynamic inferences in the presence of super-spreaders.Veterinary research · 2019Article
- Transmission Trees on a Known Pathogen Phylogeny: Enumeration and Sampling.Molecular biology and evolution · 2019Article
- Host contact dynamics shapes richness and dominance of pathogen strains.PLoS computational biology · 2019Article
- Phylogenies from dynamic networks.PLoS computational biology · 2019Article
- Detection of HIV transmission clusters from phylogenetic trees using a multi-state birth-death model.Journal of the Royal Society, Interface · 2018Article
- Effects of contact network structure on epidemic transmission trees: implications for data required to estimate network structure.Statistics in medicine · 2018Article
- Incorporating genomic methods into contact networks to reveal new insights into animal behavior and infectious disease dynamics.Behaviour · 2018Article
- Phylodynamics on local sexual contact networks.PLoS computational biology · 2017Article
- Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men.Sexual health · 2017Review
- Inference of Transmission Network Structure from HIV Phylogenetic Trees.PLoS computational biology · 2017Article
- Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2016Review
- Reconstructing contact network parameters from viral phylogenies.Virus evolution · 2016Article
- Trends in the Mechanistic and Dynamic Modeling of Infectious Diseases.Current epidemiology reports · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The characteristics of the host contact network over which a pathogen is transmitted affect both epidemic spread and the projected effectiveness of control strategies. Given the importance of understanding these contact networks, it is unfortunate that they are very difficult to measure directly. This challenge has led to an interest in methods to infer information about host contact networks from pathogen phylogenies, because in shaping a pathogen's opportunities for reproduction, contact networks also shape pathogen evolution. Host networks influence pathogen phylogenies both directly, through governing opportunities for evolution, and indirectly by changing the prevalence and incidence. Here, we aim to separate these two effects by comparing pathogen evolution on different host networks that share similar epidemic trajectories. This approach allows use to examine the direct effects of network structure on pathogen phylogenies, largely controlling for confounding differences arising from population dynamics. We find that networks with more heterogeneous degree distributions yield pathogen phylogenies with more variable cluster numbers, smaller mean cluster sizes, shorter mean branch lengths, and somewhat higher tree imbalance than networks with relatively homogeneous degree distributions. However, in particular for dynamic networks, we find that these direct effects are relatively modest. These findings suggest that the role of the epidemic trajectory, the dynamics of the network and the inherent variability of metrics such as cluster size must each be taken into account when trying to use pathogen phylogenies to understand characteristics about the underlying host contact network.
Indexed as
Identifiers
What 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.