Evidence map›Paper›PMID 28768904›Full record

ArticleJCI insight2017

Mapping the clinical outcomes and genetic evolution of Ebola virus in Sierra Leone.

Tao Li, Hong-Wu Yao, Di Liu, Hong-Guang Ren, Yi Hu, David Kargbo, Yue Teng, Yong-Qiang Deng, Hui-Jun Lu, Xiong Liu and 16 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. The first step in the success or failure of emerging pathogens.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors at 5 institutions in 2 countries.

Tao LiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Hong-Wu YaoState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Di LiuInstitute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Hong-Guang RenState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Yi HuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
David KargboSierra Leone Ministry of Health and Sanitation, Freetown, Sierra Leone.
Yue TengState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Yong-Qiang DengState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Hui-Jun LuKey Laboratory of Jilin Province for Zoonosis Prevention and Control, Changchun, China.
Xiong LiuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Kun LiuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Nian-Zhi NingState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Gary WongInstitute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Foday DafaeSierra Leone Ministry of Health and Sanitation, Freetown, Sierra Leone.
Abdul KamaraSierra Leone Ministry of Health and Sanitation, Freetown, Sierra Leone.
AiPing WuCenter for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Suzhou Institute ofSystems Medicine, Suzhou, China.
Tai-Jiao JiangCenter for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Suzhou Institute ofSystems Medicine, Suzhou, China.
Zhan LiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Jie HuangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Yu SunState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Jun QianKey Laboratory of Jilin Province for Zoonosis Prevention and Control, Changchun, China.
Brima KargboSierra Leone Ministry of Health and Sanitation, Freetown, Sierra Leone.
Jia-Fu JiangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Hui WangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Wu-Chun CaoState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Institute of Microbiology · CNMinistry of Health and Sanitation · SLChinese Academy of Medical Sciences & Peking Union Medical College · CNJilin University · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sierra Leone was the most severely affected country in Western Africa during the 2013-2016 outbreak of Ebola virus disease (EVD). Previous genome surveillance studies have revealed the origin, diversity, and evolutionary dynamics of the Ebola virus (EBOV); however, the information regarding EBOV sequences is insufficient, especially the clinical outcomes, given that the correlation between the clinical outcomes and the genetic evolution of EBOV is still not clear. Here, we collected and curated a comprehensive data set that includes 514 EBOV genome sequences from patients with confirmed EVD (including 60 sequences not previously studied), >87.5% of which have residence information and definitive clinical outcomes. Phylogenetic reconstruction revealed 11 lineages of EBOV in Sierra Leone. The median-joining haplotype network showed that haplotypes that are associated with lethal outcomes tend to contribute more to the spread of the EBOV in Sierra Leone than those with live outcomes. Analyses of the spatial-temporal distribution unraveled the lineage-distinctive distribution patterns. Different viral lineages have different case fatality rates (CFRs) during the same stage of the outbreak, implying that several lineages featuring SNPs may correlate with increased/decreased CFRs. This study provides invaluable data sets of EBOV infection and highlights the potential SNPs for further in-depth investigation.

Indexed as

Genetics

Identifiers

PMID28768904
PMCPMC5543915
OpenAlexW2741802347

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.