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Model Based Covid-19 Case Studies in the UK, the USA and India

Basu, S.

2020-06-03 infectious diseases
10.1101/2020.05.31.20118760 medRxiv
Show abstract

Time dependent spread of Covid-19 among the population of the UK, the USA and India is analyzed using a recently developed mathematical model [1-3]. Results of model predictions of case growth in these countries during the next six weeks are also presented. The model is applicable to case studies and near term predictions for other countries and regions.

Matching journals

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

1
PLOS ONE
● 5266 papers in training set
Top 5%
27.7%
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2
Scientific Reports
○ 3612 papers in training set
Top 8%
7.6%
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3
Royal Society Open Science
● 214 papers in training set
Top 0.9%
4.2%
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4
Infectious Disease Modelling
○ 54 papers in training set
Top 0.4%
4.2%
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5
Chaos, Solitons & Fractals
○ 32 papers in training set
Top 0.3%
2.8%
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6
Mathematical Biosciences and Engineering
● 23 papers in training set
Top 0.3%
2.8%
7
BMC Infectious Diseases
○ 133 papers in training set
Top 1%
2.5%
50% of probability mass above
8
Cureus
○ 68 papers in training set
Top 2%
2.2%
9
Mathematical Biosciences
○ 49 papers in training set
Top 0.5%
2.0%
10
F1000Research
○ 88 papers in training set
Top 1%
1.8%
11
PLOS Computational Biology
● 1863 papers in training set
Top 14%
1.8%
12
Physical Review E
● 112 papers in training set
Top 0.7%
1.8%
13
BMC Research Notes
○ 33 papers in training set
Top 0.3%
1.8%
14
Frontiers in Public Health
○ 148 papers in training set
Top 4%
1.4%
15
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
● 15 papers in training set
Top 0.1%
1.4%
16
Nature Communications
○ 5641 papers in training set
Top 49%
1.2%
17
BMC Public Health
○ 158 papers in training set
Top 4%
1.1%
18
Physica A: Statistical Mechanics and its Applications
○ 13 papers in training set
Top 0.2%
1.1%
19
Tropical Medicine and Infectious Disease
○ 12 papers in training set
Top 0.2%
1.1%
20
Journal of The Royal Society Interface
● 235 papers in training set
Top 3%
1.1%
21
Applied Sciences
○ 25 papers in training set
Top 0.6%
1.1%
22
The European Physical Journal Plus
○ 13 papers in training set
Top 0.3%
1.0%
23
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 1%
1.0%
24
Journal of Public Health
◐ 24 papers in training set
Top 0.9%
1.0%
25
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 5%
1.0%
26
BMJ Open
● 601 papers in training set
Top 12%
0.9%
27
PLOS Global Public Health
● 344 papers in training set
Top 8%
0.9%
28
Nonlinear Dynamics
○ 10 papers in training set
Top 0.3%
0.9%
29
Epidemics
○ 116 papers in training set
Top 2%
0.6%
30
Epidemiology and Infection
◐ 89 papers in training set
Top 3%
0.6%

"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.