Evidence map›Paper›PMID 31277583›Full record

SynthesisBMC infectious diseases2019

Prevalence of Zika virus in blood donations: a systematic review and meta-analysis.

Rongfei Liu, Xuanzhuo Wang, Yu Ma, Jianyong Wu, Chen Mao, Lihong Yuan, Jiahai Lu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 4 pooled it
–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

14 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Zika Virus.Pathogens (Basel, Switzerland) · 2020
    Review
  14. Review
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.

Rongfei LiuSchool of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong Province, China.
Xuanzhuo WangSchool of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong Province, China.
Yu MaGuangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong Province, China.
Jianyong WuSchool of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong Province, China.
Chen MaoDepartment of Epidemiology, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
Lihong YuanSchool of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong Province, China. yuanlh3@mail.sysu.edu.cn.
Jiahai LuSchool of Public Health, Sun Yat-sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong Province, China. lujiahai@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-8593-3402

Funding

National Natural Science Foundation of China 31872499the National Science and Technology Major Project 2018ZX10101002-001-001
6 · The paper itself

Abstract

backgroundTransfusion-Transmitted Zika virus (TT-ZIKV) has become an emerging threat to world blood banks due to the fast spread of ZIKV epidemics and high rate of asymptomatic infections. For the risk assessment of ZIKV infection in blood products, relevant studies in blood donations or blood donors tested for ZIKV were collected and analyzed systematically. The overall prevalence of ZIKV infection were estimated through meta-analysis and potential risk factors were detected. The results will provide important clues for the protocol design of blood screening tests.

methodsRelevant articles about the rate of ZIKV detected in blood samples were identified from PubMed, Scopus and Web Of Science using key terms search strategy until October 7, 2017. Eligible articles were screened following inclusion and exclusion criteria. Meta-analysis and subgroup analyses were performed by software R3.4.1. Overall postdonation and posttransfusion follow-ups were analyzed.

resultsTen literatures (528,947 blood samples) were included for meta-analysis. The overall pooled prevalence of ZIKV (RNA and antibody) in blood donations was 1.02% (95%CI 0.36-1.99). The pooled prevalence of ZIKV RNA in blood donations was 0.85% (95%CI 0.21-1.88) less than the pooled prevalence of anti-ZIKV antibodies 1.61% (95%CI 0.03-5.21), however the difference was not statistically significant (p = 0.52). The prevalence varied significantly in different geographical regions (p < 0.001). Blood donations were more than two times likely to be infected by ZIKV in Zika epidemic period (1.37, 95%CI 0.91-1.91) than in non-epidemic period (0.61, 95%CI 0-2.55). The prevalence of anti-ZIKV antibodies (1.61, 95%CI 0.03-5.21) was almost twice as much as ZIKV nucleic acid detected in blood donations (0.85, 95%CI 0.21-1.88). However, statistically significant differences were not observed. A total of 122 ZIKV positive blood donors were followed, of which 48 (39%) reported symptoms postdonation, but none of the 13 followed recipients reported any clinical symptoms related to Zika infection posttransfusion.

conclusionThe pooled prevalence of Zika infection in blood donations was 1.02%. The prevalence varied greatly and reached to high-risk level in most of the situations. The results suggest that nucleic acid tests (NAT) for blood screening and pathogen reduction/inactivation technology (PRT) should be implemented in Zika-endemic areas and appropriate strategies should be designed according to different conditions. More studies are needed in the future to provide more evidence.

Indexed as

Zika VirusZika Virus InfectionAntibodies, ViralBlood DonorsHumansPrevalenceRNA, ViralAntibodies, ViralRNA, ViralBlood donors/donationsBlood screening testsZika virus (ZIKV)

Identifiers

PMID31277583
PMCPMC6612077

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.