ArticleJournal of the Royal Society, Interface2010
Protocols for sampling viral sequences to study epidemic dynamics.
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. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Transmission cluster characteristics of global, regional, and lineage-specific SARS-CoV-2 phylogenies.IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- Using multiple sampling strategies to estimate SARS-CoV-2 epidemiological parameters from genomic sequencing data.Nature communications · 2022Article
- Fundamental Identifiability Limits in Molecular Epidemiology.Molecular biology and evolution · 2021Article
- Sample size calculation for phylogenetic case linkage.PLoS computational biology · 2021Article
- Article
- Jointly Inferring the Dynamics of Population Size and Sampling Intensity from Molecular Sequences.Molecular biology and evolution · 2020Article
- Accounting for population structure reveals ambiguity in the Zaire Ebolavirus reservoir dynamics.PLoS neglected tropical diseases · 2020Article
- Identifying the patterns and drivers ofVirus evolution · 2019Article
- Dengue diversity across spatial and temporal scales: Local structure and the effect of host population size.Science (New York, N.Y.) · 2017Article
- Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men.Sexual health · 2017Review
- Estimating infectious disease transmission distances using the overall distribution of cases.Epidemics · 2016Article
- Inferences from tip-calibrated phylogenies: a review and a practical guide.Molecular ecology · 2016Review
- Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference.PLoS computational biology · 2016Article
- The effects of sampling strategy on the quality of reconstruction of viral population dynamics using Bayesian skyline family coalescent methods: A simulation study.Virus evolution · 2016Article
- Genetic diversity and evolutionary insights of respiratory syncytial virus A ON1 genotype: global and local transmission dynamics.Scientific reports · 2015Article
- Eight challenges in phylodynamic inference.Epidemics · 2015Article
- Enterovirus Migration Patterns between France and Tunisia.PloS one · 2015Article
- Phylodynamics of vampire bat-transmitted rabies in Argentina.Molecular ecology · 2014Article
- Molecular tools for studying HIV transmission in sexual networks.Current opinion in HIV and AIDS · 2014Review
- How the dynamics and structure of sexual contact networks shape pathogen phylogenies.PLoS computational biology · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
With more emphasis being put on global infectious disease monitoring, viral genetic data are being collected at an astounding rate, both within and without the context of a long-term disease surveillance plan. Concurrent with this increase have come improvements to the sophisticated and generalized statistical techniques used for extracting population-level information from genetic sequence data. However, little research has been done on how the collection of these viral sequence data can or does affect the efficacy of the phylogenetic algorithms used to analyse and interpret them. In this study, we use epidemic simulations to consider how the collection of viral sequence data clarifies or distorts the picture, provided by the phylogenetic algorithms, of the underlying population dynamics of the simulated viral infection over many epidemic cycles. We find that sampling protocols purposefully designed to capture sequences at specific points in the epidemic cycle, such as is done for seasonal influenza surveillance, lead to a significantly better view of the underlying population dynamics than do less-focused collection protocols. Our results suggest that the temporal distribution of samples can have a significant effect on what can be inferred from genetic data, and thus highlight the importance of considering this distribution when designing or evaluating protocols and analysing the data collected thereunder.
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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.