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Forecasting trajectories of an emerging epidemic with mathematical modeling in an online dashboard: The case of COVID-19

Młocek, W.; Lew, R.

2020-05-23 epidemiology
10.1101/2020.05.21.20108753 medRxiv
Show abstract

We offer an efficient mathematical model for forecasting the course of an emerging epidemic, with COVID-19 as a use case. We predict the future course of confirmed cases in a number of countries, and present the results in a modern online dashboard, updated daily and accessible to the public.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 14%
12.6%
Similar papers in this journal
2
Scientific Reports
○ 3612 papers in training set
Top 4%
9.9%
Similar papers in this journal
3
PLOS Computational Biology
● 1863 papers in training set
Top 6%
5.5%
Similar papers in this journal
4
Frontiers in Public Health
○ 148 papers in training set
Top 0.9%
5.2%
Similar papers in this journal
5
Patterns
○ 78 papers in training set
Top 0.4%
4.1%
Similar papers in this journal
6
npj Digital Medicine
○ 118 papers in training set
Top 1%
4.1%
7
JMIR Public Health and Surveillance
◐ 45 papers in training set
Top 0.3%
2.7%
8
Mathematical Biosciences and Engineering
● 23 papers in training set
Top 0.3%
2.5%
9
Epidemics
○ 116 papers in training set
Top 0.8%
2.4%
10
Nature Communications
○ 5641 papers in training set
Top 41%
2.1%
50% of probability mass above
11
Quantitative Biology
○ 12 papers in training set
Top 0.1%
2.1%
12
Infectious Disease Modelling
○ 54 papers in training set
Top 0.7%
2.1%
13
Mathematical Biosciences
○ 49 papers in training set
Top 0.6%
1.7%
14
Journal of Medical Internet Research
◐ 87 papers in training set
Top 1%
1.7%
15
Journal of The Royal Society Interface
● 235 papers in training set
Top 2%
1.7%
16
IEEE Access
● 35 papers in training set
Top 0.7%
1.7%
17
Heliyon
○ 152 papers in training set
Top 4%
1.5%
18
Communications Medicine
○ 113 papers in training set
Top 2%
1.3%
19
IEEE/ACM Transactions on Computational Biology and Bioinformatics
● 38 papers in training set
Top 0.8%
1.1%
20
Swiss Medical Weekly
● 15 papers in training set
Top 0.1%
1.1%
21
BMC Public Health
○ 158 papers in training set
Top 4%
1.1%
22
Royal Society Open Science
● 214 papers in training set
Top 4%
1.1%
23
eLife
● 5828 papers in training set
Top 63%
1.0%
24
Nature Medicine
○ 125 papers in training set
Top 3%
1.0%
25
IEEE Journal of Biomedical and Health Informatics
● 37 papers in training set
Top 1%
1.0%
26
Chaos, Solitons & Fractals
○ 32 papers in training set
Top 0.8%
0.9%
27
BMC Infectious Diseases
○ 133 papers in training set
Top 4%
0.9%
28
JMIRx Med
◐ 32 papers in training set
Top 2%
0.9%
29
BMC Bioinformatics
○ 457 papers in training set
Top 5%
0.9%
30
Bulletin of Mathematical Biology
○ 92 papers in training set
Top 1%
0.9%

"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.