Back

A logistic model of CoV-2 propagation

Weiss, R. F.

2020-07-26 epidemiology
10.1101/2020.07.20.20157826 medRxiv
Show abstract

We describe an elemental logistic model for the propagation of CoV-2 in a community and illustrate the sensitivity of the model to key parameters such as R0, the initial rate of infections per infected person, and A0, the fraction of infected people developing neutralizing antibodies. We demonstrate the importance of the duration of immunity in the population, the development of waves of new cases of infection, and the effect of premature opening of local economies.

Matching journals

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

1
Journal of Theoretical Biology
○ 162 papers in training set
Top 0.1%
14.6%
Similar papers in this journal
2
Journal of The Royal Society Interface
● 235 papers in training set
Top 0.4%
7.8%
Similar papers in this journal
3
Mathematical Biosciences
○ 49 papers in training set
Top 0.1%
6.6%
Similar papers in this journal
4
PLOS ONE
● 5266 papers in training set
Top 26%
6.2%
Similar papers in this journal
5
PLOS Computational Biology
● 1863 papers in training set
Top 7%
5.4%
6
Bulletin of Mathematical Biology
○ 92 papers in training set
Top 0.3%
5.4%
Similar papers in this journal
7
Physical Review E
● 112 papers in training set
Top 0.4%
4.3%
50% of probability mass above
8
Scientific Reports
○ 3612 papers in training set
Top 23%
4.3%
9
Physical Biology
○ 46 papers in training set
Top 0.2%
3.2%
10
Nature Communications
○ 5641 papers in training set
Top 38%
2.7%
11
Epidemiology and Infection
◐ 89 papers in training set
Top 0.7%
2.4%
12
Mathematical Medicine and Biology: A Journal of the IMA
◐ 10 papers in training set
Top 0.1%
2.1%
13
Royal Society Open Science
● 214 papers in training set
Top 3%
2.1%
14
Infectious Disease Modelling
○ 54 papers in training set
Top 0.7%
2.1%
15
Physical Review Research
● 49 papers in training set
Top 0.4%
1.9%
16
Journal of Mathematical Biology
○ 40 papers in training set
Top 0.3%
1.9%
17
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 30%
1.5%
18
Physical Review X
● 25 papers in training set
Top 0.3%
1.5%
19
Epidemics
○ 116 papers in training set
Top 1%
1.3%
20
Nonlinear Dynamics
○ 10 papers in training set
Top 0.2%
1.3%
21
Chaos, Solitons & Fractals
○ 32 papers in training set
Top 0.7%
1.1%
22
eLife
● 5828 papers in training set
Top 60%
1.1%
23
Demographic Research
● 11 papers in training set
Top 0.1%
1.0%
24
Chaos: An Interdisciplinary Journal of Nonlinear Science
● 17 papers in training set
Top 0.3%
0.8%
25
Virus Evolution
◐ 155 papers in training set
Top 1%
0.8%
26
PNAS Nexus
◐ 159 papers in training set
Top 4%
0.8%
27
Communications Physics
○ 14 papers in training set
Top 0.1%
0.8%
28
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
● 15 papers in training set
Top 0.3%
0.8%
29
Science Advances
● 1243 papers in training set
Top 31%
0.8%
30
The European Physical Journal Plus
○ 13 papers in training set
Top 0.4%
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.