This journal publishes research on modeling and forecasting the spread of COVID-19 using various data sources and computational techniques. Articles analyze migration data, employ deep learning models like LSTM, estimate epidemiological parameters such as the effective reproduction number, and utilize social media data for case characterization. Growth models are applied to time series data to understand transmission dynamics.
University of Electronic Science and Technology of China
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Does the journal have a website?
✓ Linked
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Is the ISSN verified?
1001-0548
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Indexed in a trusted database?
Scopus
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Peer review process documented?
Peer Review
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Follows ethical publishing standards (COPE)?
N/A
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APC fees clearly disclosed?
N/A
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Not on predatory/blacklists?
✓ Clean
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Long-term digital preservation?
N/A
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Plagiarism detection in place?
N/A
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Listed in DOAJ (verified OA)?
N/A
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Primary language documented?
English, Chinese
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Publication & Citation Trend
Articles published
Times cited
2014
2015
2016
2017
2018
2019
2020
2021
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Electrical and Electronic EngineeringQ4
Subject Classification
Scopus Categories
Electrical and Electronic Engineering
Research Topics (OpenAlex)
Advanced Algorithms and ApplicationsAdvanced Computational Techniques and ApplicationsAdvanced Sensor and Control SystemsLegal and Regulatory AnalysisLinguistic, Cultural, and Literary Studies