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Note: Forecasting COVID-19 spread in Lebanon February 8-21,2021

Omar El Deeb; Maya Jalloul

2021-02-12 epidemiology
10.1101/2021.02.09.21251447 medRxiv
Show abstract

This note implements an iterative method in order to predict the number of active cases with COVID-19, and consequently forecast the number of inpatients to hospitals and ICU in Lebanon according to different scenarios after end of the complete closure and curfew implemented between January 13 and February 7, 2021. The forecast predicts a decrease in the number of infections and people in need for hospitalization and ICU during the 2 weeks after the curfew (until February 21st), with varying extents depending on the subsequent commitment to mitigation measures, except for the case of a 2% absolute increase from the current rate of infection, which would bring back the numbers of cases back to a increasing trend.

Matching journals

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

1
PLOS ONE
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Top 10%
18.8%
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Top 30%
3.3%
8
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○ 332 papers in training set
Top 2%
3.3%
9
PLOS Computational Biology
● 1863 papers in training set
Top 10%
3.3%
50% of probability mass above
10
BMC Infectious Diseases
○ 133 papers in training set
Top 0.9%
3.2%
11
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○ 49 papers in training set
Top 0.5%
2.1%
12
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◐ 89 papers in training set
Top 0.8%
2.1%
13
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Top 0.1%
1.9%
14
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1.9%
15
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Top 6%
1.8%
16
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Top 0.3%
1.5%
17
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◐ 308 papers in training set
Top 6%
1.5%
18
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Top 2%
1.4%
19
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● 214 papers in training set
Top 4%
1.1%
20
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Top 4%
1.1%
21
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Top 0.8%
1.1%
22
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Top 4%
1.1%
23
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Top 1%
1.0%
24
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Top 1%
0.9%
25
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○ 152 papers in training set
Top 8%
0.9%
26
BMC Public Health
○ 158 papers in training set
Top 5%
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27
Journal of The Royal Society Interface
● 235 papers in training set
Top 4%
0.6%
28
Vaccines
○ 198 papers in training set
Top 4%
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29
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○ 120 papers in training set
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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.