Evidence map›Paper›PMID 29318441›Full record

ReviewFrontiers of medicine2018

Transforming bacterial disease surveillance and investigation using whole-genome sequence to probe the trace.

Biao Kan, Haijian Zhou, Pengcheng Du, Wen Zhang, Xin Lu, Tian Qin, Jianguo Xu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Frontiers of medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

7 authors.

Biao KanState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. kanbiao@icdc.cn.
Haijian ZhouState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Pengcheng DuBeijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China.
Wen ZhangState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Xin LuState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Tian QinState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Jianguo XuState Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. xujianguo@icdc.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two decades have passed since the first bacterial whole-genome sequencing, which provides new opportunity for microbial genome. Consequently, considerable genetic diversity encoded by bacterial genomes and among the strains in the same species has been revealed. In recent years, genome sequencing techniques and bioinformatics have developed rapidly, which has resulted in transformation and expedited the application of strategy and methodology for bacterial genome comparison used in dissection of infectious disease epidemics. Bacterial whole-genome sequencing and bioinformatic computing allow genotyping to satisfy the requirements of epidemiological study in disease control. In this review, we outline the significance and summarize the roles of bacterial genome sequencing in the context of bacterial disease control and prevention.We discuss the applications of bacterial genome sequencing in outbreak detection, source tracing, transmission mode discovery, and new epidemic clone identification. Wide applications of genome sequencing and data sharing in infectious disease surveillance networks will considerably promote outbreak detection and early warning to prevent the dissemination of bacterial diseases.

Indexed as

Genome, BacterialPopulation SurveillanceBacteriaBacterial InfectionsBacterial Typing TechniquesDisease OutbreaksGenotypeHumansWhole Genome Sequencingbacteriagenome sequencinggenomic epidemiologyinfectious diseasessurveillance

Identifiers

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.