ArticlePLoS computational biology2016
Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 46 citations in OpenAlex.
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Epidemiology and economics of foot-and-mouth disease: current understanding and knowledge gaps.Veterinary research · 2025Review
- Pairwise Accelerated Failure Time Regression Models for Infectious Disease Transmission in Close-Contact Groups With External Sources of Infection.Statistics in medicine · 2024Article
- A Bayesian inference method to estimate transmission trees with multiple introductions; applied to SARS-CoV-2 in Dutch mink farms.PLoS computational biology · 2023Article
- Quantifying the value of viral genomics when inferring who infected whom in the 2014-16 Ebola virus outbreak in Guinea.Virus evolution · 2023Article
- Network methods and design of randomized trials: Application to investigation of COVID-19 vaccination boosters.Clinical trials (London, England) · 2022Article
- Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification.PLoS computational biology · 2022Article
- Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review.Pathogens (Basel, Switzerland) · 2022Review
- Combining epidemiological and ecological methods to quantify social effects onRoyal Society open science · 2021Article
- Evaluation of Phylogenetic Methods for Inferring the Direction of Human Immunodeficiency Virus (HIV) Transmission: HIV Prevention Trials Network (HPTN) 052.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Bayesian reconstruction of transmission trees from genetic sequences and uncertain infection times.Statistical applications in genetics and molecular biology · 2020Article
- Sampling and summarizing transmission trees with multi-strain infections.Bioinformatics (Oxford, England) · 2020Article
- Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole-genome-sequence data.Statistics in medicine · 2020Article
- Transmission Trees on a Known Pathogen Phylogeny: Enumeration and Sampling.Molecular biology and evolution · 2019Article
- Model diagnostics and refinement for phylodynamic models.PLoS computational biology · 2019Article
- Statistical outbreak detection by joining medical records and pathogen similarity.Journal of biomedical informatics · 2019Article
- outbreaker2: a modular platform for outbreak reconstruction.BMC bioinformatics · 2018Article
- Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.Microbial genomics · 2018Article
- Phylogenetic patterns recover known HIV epidemiological relationships and reveal common transmission of multiple variants.Nature microbiology · 2018Article
- The Puzzle of HIV Neutral and Selective Evolution.Molecular biology and evolution · 2018Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology.
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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.