Back

Understanding the spreading patterns of COVID-19 in UK and its impact on exit strategies

2020-05-21 health policy Title + abstract only
View on medRxiv
Show abstract

Prior to lockdown the spread of COVID-19 in UK is found to be exponential, with an exponent =0.207. In case of COVID-19 this spreading behaviour is quantitatively better described with a mobility-driven SIR-SEIR model [2] rather than the homogenous mixing models Lockdown has dramatically slowed down the spread of COVID-19 in UK, and even more significantly, has changed the growth in the total number of infected from exponential to quadratic. This significant change is due to a transition from a ...

Predicted journal destinations

1
Scientific Reports
701 training papers
Top 0.4% 27.5%
2
PLOS ONE
1737 training papers
Top 18% 27.5%
3
Royal Society Open Science
49 training papers
#1 7.4%
4
BMC Public Health
148 training papers
Top 12% 2.4%
5
Proceedings of the National Academy of Sciences
100 training papers
Top 4% 2.4%
6
PLOS Computational Biology
141 training papers
Top 6% 2.4%
7
Epidemics
96 training papers
Top 5% 2.3%
8
International Journal of Infectious Diseases
115 training papers
Top 11% 1.7%
9
Nature Communications
483 training papers
Top 41% 1.7%
10
Frontiers in Public Health
135 training papers
Top 19% 1.7%
11
BMJ Open
553 training papers
Top 55% 1.5%
12
eLife
262 training papers
Top 32% 1.5%
13
Journal of Theoretical Biology
29 training papers
Top 2% 1.2%
14
Eurosurveillance
77 training papers
Top 12% 0.9%
15
Vaccines
131 training papers
Top 12% 0.9%
16
International Journal of Environmental Research and Public Health
116 training papers
Top 28% 0.9%
17
Epidemiology and Infection
80 training papers
Top 13% 0.9%
18
Frontiers in Medicine
99 training papers
Top 20% 0.9%
19
EClinicalMedicine
21 training papers
Top 0.3% 0.9%
20
Chaos, Solitons & Fractals
17 training papers
Top 2% 0.9%
21
Viruses
79 training papers
Top 9% 0.9%
22
Journal of Medical Internet Research
81 training papers
Top 17% 0.9%
23
Journal of The Royal Society Interface
54 training papers
Top 7% 0.6%
24
Public Health
34 training papers
Top 8% 0.6%
25
F1000Research
28 training papers
Top 4% 0.6%
26
JMIR Public Health and Surveillance
45 training papers
Top 12% 0.6%
27
PNAS Nexus
22 training papers
Top 1% 0.6%
28
Nature Medicine
88 training papers
Top 24% 0.6%