ArticlemedRxiv : the preprint server for health sciences2020
High Resolution analysis of Transmission Dynamics of Sars-Cov-2 in Two Major Hospital Outbreaks in South Africa Leveraging Intrahost Diversity.
Article in medRxiv : the preprint server for health sciences, 2020. 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, 20 citations in OpenAlex.
- Snake venom phospholipase ACellular and molecular life sciences : CMLS · 2021Article
- Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure.Scientific reports · 2021Article
- Acute SARS-CoV-2 infections harbor limited within-host diversity and transmit via tight transmission bottlenecks.PLoS pathogens · 2021Article
- Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts.PLoS pathogens · 2021Article
Corrections and comments
- Updated by
Authors and funding
15 authors at 3 institutions in 2 countries.
Funding
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes acute, highly transmissible respiratory infection in both humans and wide range of animal species. Its rapid spread globally and devasting effects have resulted into a major public health emergency prompting the need for methodological interventions to understand and control its spread. In particular, The ability to effectively retrace its transmission pathways in outbreaks remains a major challenge. This is further exacerbated by our limited understanding of its underlying evolutionary mechanism. Using NGS whole-genome data, we determined whether inter- and intra-host diversity coupled with bottleneck analysis can retrace the pathway of viral transmission in two epidemiologically well characterised nosocomial outbreaks in healthcare settings supported by phylogenetic analysis. Additionally, we assessed the mutational landscape, selection pressure and diversity of the identified variants. Our findings showed evidence of intrahost variant transmission and evolution of SARS-CoV-2 after infection These observations were consistent with the results from the bottleneck analysis suggesting that certain intrahost variants in this study could have been transmitted to recipients. In both outbreaks, we observed iSNVs and SNVs shared by putative source-recipients pairs. Majority of the observed iSNVs were positioned in the S and ORF1ab region. AG, CT and TC nucleotide changes were enriched across SARS-COV-2 genome. Moreover, SARS-COV-2 genome had limited diversity in some loci while being highly conserved in others. Overall, Our findings show that the synergistic effect of combining withinhost diversity and bottleneck estimations greatly enhances resolution of transmission events in Sars-Cov-2 outbreaks. They also provide insight into the genome diversity suggesting purifying selection may be involved in the transmission. Together these results will help in developing strategies to elucidate transmission events and curtail the spread of Sars-Cov-2.
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.