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SIDIR: Extending SIR with Detected and Isolated Populations for Pandemic Modeling

Garman, J.; MacAvaney, S.; Yang, E.; Frieder, O.

2020-07-26 epidemiology
10.1101/2020.07.20.20157834 medRxiv
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AO_SCPLOWBSTRACTC_SCPLOWWe extend the Susceptible Infected Recovered (SIR) model to include Detected (D) and Isolated (I) compartments (SIDIR). SIDIR improves COVID-19 outbreak behavior modeling by identifying infected populations as subsequently quarantined to reduce the spread of the infection (either in a hospital or self-quarantined). We present the model and provide a case study on COVID-19. The model estimates undetected cases (i.e., those infected but unconfirmed) and extrapolates when no additional undetected active (rogue) cases will remain, potentially guiding policy decisions that help control the spread of COVID-19 and future epidemics. A live demonstration of SIDIR on COVID-19 is available at: http://ir.cs.georgetown.edu/sidir.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
● 1863 papers in training set
Top 1%
19.2%
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2
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Top 0.1%
12.4%
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3
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4
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Top 26%
5.7%
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5
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50% of probability mass above
6
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Top 0.3%
4.2%
7
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○ 54 papers in training set
Top 0.6%
2.5%
8
eLife
● 5828 papers in training set
Top 44%
2.2%
9
Journal of The Royal Society Interface
● 235 papers in training set
Top 2%
2.2%
10
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 25%
2.0%
11
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○ 49 papers in training set
Top 0.6%
1.8%
12
Wellcome Open Research
○ 67 papers in training set
Top 0.6%
1.5%
13
iScience
○ 1154 papers in training set
Top 28%
1.1%
14
Nature
○ 645 papers in training set
Top 9%
1.1%
15
Royal Society Open Science
● 214 papers in training set
Top 6%
0.9%
16
Nature Medicine
○ 125 papers in training set
Top 3%
0.9%
17
Epidemiology and Infection
◐ 89 papers in training set
Top 2%
0.9%
18
Bioinformatics
◐ 1204 papers in training set
Top 8%
0.9%
19
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
● 12 papers in training set
Top 0.2%
0.9%
20
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○ 48 papers in training set
Top 1.0%
0.9%
21
BMC Public Health
○ 158 papers in training set
Top 5%
0.6%
22
Quantitative Biology
○ 12 papers in training set
Top 0.2%
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23
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Top 6%
0.6%
24
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0.6%
25
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○ 78 papers in training set
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26
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○ 457 papers in training set
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27
Journal of Theoretical Biology
○ 162 papers in training set
Top 2%
0.5%
28
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● 23 papers in training set
Top 1%
0.5%
29
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○ 12 papers in training set
Top 0.5%
0.5%
30
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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.