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Using Novel, Agent-Based Periodic Mobility Model with Super Spreaders to Analyze Vaccination Strategies for COVID-19

Jacob, M. K.; Guo, E. X.

2021-08-10 epidemiology
10.1101/2021.08.09.21261809 medRxiv
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The authors have withdrawn this manuscript because there have been a number of mutations of COVID-19, since the manuscript was posted, as well as changes in virus behavior, such as increased transmissibility. As a result, both the vaccination strategies and parameters used during the simulation are less applicable to the current situation, and thus the results from the simulations may be incorrect for the current situation. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
PLOS ONE
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Top 15%
12.3%
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2
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9.2%
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5.7%
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4.5%
7
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Top 11%
2.5%
8
Chaos, Solitons & Fractals
○ 32 papers in training set
Top 0.3%
2.5%
9
Applied Sciences
○ 25 papers in training set
Top 0.1%
2.5%
50% of probability mass above
10
Frontiers in Applied Mathematics and Statistics
○ 11 papers in training set
Top 0.1%
2.5%
11
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● 214 papers in training set
Top 3%
2.0%
12
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◐ 32 papers in training set
Top 0.7%
2.0%
13
PeerJ
◐ 308 papers in training set
Top 5%
1.8%
14
Epidemics
○ 116 papers in training set
Top 1%
1.7%
15
BMC Infectious Diseases
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Top 2%
1.7%
16
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 0.7%
1.5%
17
Quantitative Biology
○ 12 papers in training set
Top 0.1%
1.5%
18
Mathematical Biosciences
○ 49 papers in training set
Top 0.7%
1.5%
19
Nonlinear Dynamics
○ 10 papers in training set
Top 0.2%
1.2%
20
Cureus
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Top 3%
1.2%
21
Computers in Biology and Medicine
○ 128 papers in training set
Top 3%
1.2%
22
Chaos: An Interdisciplinary Journal of Nonlinear Science
● 17 papers in training set
Top 0.2%
1.1%
23
COVID
○ 14 papers in training set
Top 0.3%
1.0%
24
Bulletin of Mathematical Biology
○ 92 papers in training set
Top 1%
1.0%
25
Mathematics
○ 11 papers in training set
Top 0.2%
0.9%
26
BioMed Research International
○ 28 papers in training set
Top 2%
0.6%
27
Journal of Theoretical Biology
○ 162 papers in training set
Top 2%
0.6%
28
Biology
○ 45 papers in training set
Top 1%
0.6%
29
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30
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Top 1%
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.