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Preface

Published: | Vol 3, Issue 1 (2020) | Cited by: 24

Authors

Abstract

This issue is dedicated to the study of the Corona Virus Disease pandemic, which is known as Covid-19. The focus on Covid-19 is to respond to the need for scientific communities to get information from the affecting region. The contributions from the authors are ranging from modeling and simulation, intervention, prediction, and data collections. Each paper went through the standard review process by at least two referees. We hope these publications could give insight information for a better understanding of the complicated transmission of Covid-19.

Keywords

Coronavirus disease 2019 (COVID-19); Bayes' theorem; Dengue fever; Bayesian probability; Computer science; Class (philosophy); Bayesian inference; Epidemic model; Statistics; Econometrics; Medicine; Mathematics; Artificial intelligence; Disease; Infectious disease (medical specialty); Virology

Research Intelligence

Data from OpenAlex ↗

Metrics

24
Citations
0.74
FWCIfield-weighted
79th
Percentilevs same year + field
Article
Work type
DIAMOND
Open Access

Topics

COVID-19 epidemiological studies Primary
1.00
Modeling and Simulation › Mathematics › Physical Sciences
Viral Infections and Outbreaks Research
0.97
Data-Driven Disease Surveillance
0.95

Related Research

Citation Trend

Citation Timeline

YearCitations
20243
20235
20228
20216
20202

Semantic Profile AI-classified research signals

Core Domains
Dengue fever 0.52
level 2
Bayesian probability 0.48
level 2
Computer science 0.48
level 0
Secondary Topics
Class (philosophy) 0.46 Statistics 0.39 Econometrics 0.39 Medicine 0.35 Mathematics 0.34 Artificial intelligence 0.30 Disease 0.29

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