Back

Analysis and Prediction of COVID-19 Characteristics Using a Birth-and-Death Model

Viswanath, N. C.

2020-06-24 epidemiology
10.1101/2020.06.23.20138719
Show abstract

Its spreading speed together with the risk of fatality might be the main characteristic that separates COVID-19 from other infectious diseases in our recent history. In this scenario, mathematical modeling for predicting the spread of the disease could have great value in containing the disease. Several very recent papers have contributed to this purpose. In this study we propose a birth-and-death model for predicting the number of COVID-19 active cases. It relation to the Susceptible-Infected-Recovered (SIR) model has been discussed. An explicit expression for the expected number of active cases helps us to identify a stationary point on the infection curve, where the infection ceases increasing. Parameters of the model are estimated by fitting the expressions for active and total reported cases simultaneously. We analyzed the movement of the stationary point and the basic reproduction number during the infection period up to the 20th of April 2020. These provide information about the disease progression path and therefore could be really useful in designing containment strategies.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
PLOS ONE
based on 1737 papers
Top 22%
18.2%
2
Chaos, Solitons & Fractals
based on 17 papers
Top 0.1%
16.5%
3
Scientific Reports
based on 701 papers
Top 10%
11.9%
4
Infectious Disease Modelling
based on 50 papers
Top 0.7%
6.8%
50% of probability mass above
5
Mathematical Biosciences and Engineering
based on 14 papers
Top 0.2%
3.0%
6
Frontiers in Public Health
based on 135 papers
Top 11%
2.6%
7
Epidemiology and Infection
based on 80 papers
Top 3%
2.6%
8
Frontiers in Physics
based on 11 papers
Top 0.4%
2.4%
9
Mathematical Biosciences
based on 15 papers
Top 1.0%
1.7%
10
Journal of Theoretical Biology
based on 29 papers
Top 2%
1.4%
11
Journal of Medical Virology
based on 95 papers
Top 6%
1.4%
12
International Journal of Environmental Research and Public Health
based on 116 papers
Top 15%
1.4%
13
PeerJ
based on 46 papers
Top 6%
1.4%
14
Royal Society Open Science
based on 49 papers
Top 4%
1.4%
15
PLOS Computational Biology
based on 141 papers
Top 8%
0.9%
16
International Journal of Infectious Diseases
based on 115 papers
Top 15%
0.9%
17
Heliyon
based on 57 papers
Top 10%
0.9%
18
Biology
based on 11 papers
Top 1%
0.9%
19
Epidemics
based on 96 papers
Top 6%
0.9%
20
Frontiers in Medicine
based on 99 papers
Top 17%
0.9%
21
BMC Infectious Diseases
based on 110 papers
Top 19%
0.7%
22
BMC Public Health
based on 148 papers
Top 23%
0.7%
23
Science of The Total Environment
based on 80 papers
Top 5%
0.7%