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Prevent the resurgence of infectious disease with asymptomatic carriers

Zhang, Z.

2020-04-19 epidemiology
10.1101/2020.04.16.20067652 medRxiv
Show abstract

After reaching the peak of the COVID-19 outbreak, many regions are in search of a reopening plan that would minimize resurgence. Here we show to prevent resurgence local governments need to estimate how early and how many COVID-19 cases can be detected. It is safe to end social distancing if the majority of cases are detected early in the infection window. If cases are detected later, a 2-layer quarantine may be necessary to prevent resurgence. If fewer cases are detected, community events, schools, and large businesses may need to remain in virtual mode. Our results demonstrate that detecting more cases earlier is essential for preventing COVID-19 resurgence.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Scientific Reports
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Top 2%
12.8%
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2
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9.6%
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8.8%
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5
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6
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Top 0.9%
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eLife
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Top 28%
4.3%
50% of probability mass above
8
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○ 118 papers in training set
Top 1%
4.0%
9
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Top 0.4%
4.0%
10
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Top 0.6%
3.5%
11
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Top 0.8%
2.4%
12
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2.4%
13
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Top 1%
2.4%
14
Nature Medicine
○ 125 papers in training set
Top 1%
2.1%
15
Journal of The Royal Society Interface
● 235 papers in training set
Top 2%
2.1%
16
Frontiers in Public Health
○ 148 papers in training set
Top 4%
1.7%
17
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○ 113 papers in training set
Top 2%
1.5%
18
Emerging Infectious Diseases
● 105 papers in training set
Top 1%
1.4%
19
Influenza and Other Respiratory Viruses
○ 46 papers in training set
Top 0.5%
1.1%
20
IEEE Access
● 35 papers in training set
Top 0.9%
1.1%
21
iScience
○ 1154 papers in training set
Top 31%
1.0%
22
BMC Medicine
○ 176 papers in training set
Top 4%
1.0%
23
Swiss Medical Weekly
● 15 papers in training set
Top 0.2%
0.8%
24
PLOS Biology
● 486 papers in training set
Top 14%
0.6%
25
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● 72 papers in training set
Top 2%
0.6%
26
PLOS Digital Health
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27
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Top 9%
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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.