Back

The impact of current and future control measures on the spread of COVID-19 in Germany

Barbarossa, M. V.; Fuhrmann, J.; Meinke, J. H.; Krieg, S.; Varma, H. V.; Castelletti, N.; Lippert, T.

2020-04-24 epidemiology
10.1101/2020.04.18.20069955 medRxiv
Show abstract

The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020 [37]. In view of most recent information on testing activity [32], we present here an update of our initial work [4]. In this work, mathematical models have been developed to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended here to account for undetected infections, as well as for stages of infections and age groups. The models are calibrated on data until April 5, data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases and reduced contact to risk groups.

Matching journals

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

1
Scientific Reports
3102 papers in training set
Top 0.4%
22.3%
2
Swiss Medical Weekly
12 papers in training set
Top 0.1%
8.3%
3
PLOS ONE
4510 papers in training set
Top 29%
6.3%
4
The European Physical Journal Plus
13 papers in training set
Top 0.2%
4.8%
5
Royal Society Open Science
193 papers in training set
Top 0.5%
3.9%
6
PLOS Computational Biology
1633 papers in training set
Top 10%
3.6%
7
Mathematical Biosciences
42 papers in training set
Top 0.3%
3.6%
50% of probability mass above
8
Biology
43 papers in training set
Top 0.2%
3.2%
9
Journal of Clinical Medicine
91 papers in training set
Top 2%
2.7%
10
Peer Community Journal
254 papers in training set
Top 1%
2.6%
11
Viruses
318 papers in training set
Top 3%
1.7%
12
Nature Communications
4913 papers in training set
Top 52%
1.7%
13
Frontiers in Physics
20 papers in training set
Top 0.4%
1.7%
14
Infectious Disease Modelling
50 papers in training set
Top 0.9%
1.5%
15
Journal of The Royal Society Interface
189 papers in training set
Top 3%
1.5%
16
Epidemiology and Infection
84 papers in training set
Top 2%
1.5%
17
International Journal of Environmental Research and Public Health
124 papers in training set
Top 5%
1.3%
18
Epidemics
104 papers in training set
Top 1%
1.3%
19
Frontiers in Public Health
140 papers in training set
Top 6%
1.2%
20
Journal of Theoretical Biology
144 papers in training set
Top 1%
1.1%
21
International Journal of Infectious Diseases
126 papers in training set
Top 3%
0.9%
22
Mathematics
11 papers in training set
Top 0.3%
0.9%
23
BMC Infectious Diseases
118 papers in training set
Top 5%
0.8%
24
BMC Public Health
147 papers in training set
Top 6%
0.7%
25
Nonlinear Dynamics
10 papers in training set
Top 0.5%
0.7%
26
Mathematical Biosciences and Engineering
23 papers in training set
Top 0.8%
0.6%
27
Communications Biology
886 papers in training set
Top 29%
0.6%
28
JMIRx Med
31 papers in training set
Top 2%
0.6%