Evidence map›Paper›PMID 36662433›Full record

ReviewEnvironmental science and pollution research international2023

Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends.

Zhihan Gao, Min Gao, Chun-Hua Chen, Yifan Zhou, Zhi-Hui Zhan, Yuan Ren

Abstract readReview
In one paragraph

Review in Environmental science and pollution research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. A Survey on Unifying Large Language Models and Knowledge Graphs for Biomedicine and Healthcare.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2025
    Article
  3. Review
  4. Article
  5. 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

6 authors.

Zhihan GaoSchool of Environment and Energy, South China University of Technology, Higher Education Mega Center, 510006, Guangzhou, China.
Min GaoSchool of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China.
Chun-Hua ChenSchool of Software Engineering, South China University of Technology, 510006, Guangzhou, China.
Yifan ZhouSchool of Electronic and Information Engineering, South China University of Technology, 510006, Guangzhou, China.
Zhi-Hui ZhanSchool of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China.
Yuan RenSchool of Environment and Energy, South China University of Technology, Higher Education Mega Center, 510006, Guangzhou, China. ceyren@scut.edu.cn.ORCID http://orcid.org/0000-0003-2842-6399

Funding

National Natural Science Foundation of China 4187746Natural Science Foundation of Guangdong Province 2019A1515011037
6 · The paper itself

Abstract

Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields.

Indexed as

COVID-19HumansPattern Recognition, AutomatedRNA, ViralSARS-CoV-2Wastewater-Based Epidemiological MonitoringRNA, ViralDevelopment trendsKnowledge graphPaper mining analysisResearch hotspotsText extraction toolWastewater-based epidemiology

Identifiers

PMID36662433
PMCPMC9867605

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.