Evidence map›Paper›PMID 35721004›Full record

ArticleInformation processing & management2021

Enhancing Traceability of Infectious Diseases: A Blockchain-Based Approach.

Peng Zhu, Jian Hu, Yue Zhang, Xiaotong Li

Open access · greenAbstract read
In one paragraph

Article in Information processing & management, 2021. 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
13.9field-weighted citation impact, top 1% 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

8 citing papers in PubMed, 59 citations in OpenAlex.

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  7. Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping Review.International journal of environmental research and public health · 2022
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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

4 authors at 3 institutions in 2 countries.

Peng ZhuNanjing University of Science and Technology, Nanjing 210094, China.
Jian HuNanjing University of Science and Technology, Nanjing 210094, China.
Yue ZhangCalifornia State University, Northridge, Northridge, CA 91330-8372, USA.
Xiaotong LiUniversity of Alabama in Huntsville, AL 35899, USA.
Nanjing University of Science and Technology · CNCalifornia State University, Northridge · USUniversity of Alabama in Huntsville · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global pandemic of COVID-19 has brought significant attentions to three important features of disease direct reporting systems: traceability, reliability, and effectiveness. A traditional disease direct reporting system has a central node of control, with a hierarchical structure that goes up from locals (cities and counties) to regions and eventually reaches a central data repository. Such systems are often prone to easy data loss, arbitrary or unauthorized data changes, and unreliable traceability to individual nodes. Blockchain, as a new disruptive technology, provides a potential solution. Leveraging blockchain's features of decentralization, unforgeability, whole-process traceability, we develop a method for disease information tracing with key components including infectious disease information collection, information chain-style storage, and information query. Our blockchain-based infectious disease traceability method can promptly collect disease information and form the disease information time series blockchain. We demonstrate that the information chain constructed is authentic and transparent, and it can be queried and maintained at any node in the system. Consequently, the infectious disease information on the blockchain can be monitored and queried any time, thereby greatly facilitating the tracing of the propagation paths of infectious diseases.

Indexed as

BlockchainDistributed systemsInfectious diseasesTimestampTraceability

Identifiers

PMID35721004
PMCPMC9187510
OpenAlexW3135169451

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.