ArticleCurrent opinion in infectious diseases1997
Viral evolution and epidemiology.
Article in Current opinion in infectious diseases, 1997. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell.Nature communications · 2025Article
- Genomic surveillance reveals COVID-19 outbreak clusters in a tertiary center in Malaysia: A cross-sectional study.IJID regions · 2025Article
- Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell.bioRxiv : the preprint server for biology · 2024Article
- An Epidemiological Analysis of SARS-CoV-2 Genomic Sequences from Different Regions of India.Viruses · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
This review highlights recent research on viral evolution and its use towards understanding disease pathogenesis and epidemiology. The development of techniques such as enzymatic amplification of viral genomes and automated sequencing has led to a dramatic increase in the amount of sequence information from clinical samples. These sequences (RNA or DNA, or the amino acids they encode) have been compared by complex computer algorithms to generate evolutionary trees or phylogenies of natural virus variants, which can sometimes be used to correlate viral genotype with phenotype. Understanding the rates and types of evolution that occur during the transmission of viruses has considerable impact on the design of methods for the control of virus diseases.
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.