TY - GEN
T1 - Modeling Dynamics of Covid-19 Infected Population with PSO
AU - Huang, Guangdong
AU - Li, Aihua
N1 - Publisher Copyright:
© 2021, Springer Nature Singapore Pte Ltd.
PY - 2021
Y1 - 2021
N2 - This study focuses on the Covid-19 spreading dynamics in Bergen County, New Jersey, USA. Due to limited covid-19 testing capacity, it was difficult to assess the real data about the virus spreading in New Jersey counties. Our study is based on the available incomplete daily data from March 15 to July 15 of 2020. In order to capture an overall picture of the local dynamics of the infected population and predict reasonable future situations, we perform several traditional dynamic modeling methods. A region-stage-modified-SEIR model (denoted MSEIR) and a SEIRH model are constructed to describe the dynamics of the infected population. Particle Swarm Optimization (PSO) is used to identify the parameters of the developed models. In order to predict the cumulative number of the infected individuals, the produced models are used to simulate the dynamics of the population in four epidemiological groups respectively: susceptible, exposed, infected, and recovered groups. By this process, we obtain a better picture of the COVID-19 infected individuals in the target county.
AB - This study focuses on the Covid-19 spreading dynamics in Bergen County, New Jersey, USA. Due to limited covid-19 testing capacity, it was difficult to assess the real data about the virus spreading in New Jersey counties. Our study is based on the available incomplete daily data from March 15 to July 15 of 2020. In order to capture an overall picture of the local dynamics of the infected population and predict reasonable future situations, we perform several traditional dynamic modeling methods. A region-stage-modified-SEIR model (denoted MSEIR) and a SEIRH model are constructed to describe the dynamics of the infected population. Particle Swarm Optimization (PSO) is used to identify the parameters of the developed models. In order to predict the cumulative number of the infected individuals, the produced models are used to simulate the dynamics of the population in four epidemiological groups respectively: susceptible, exposed, infected, and recovered groups. By this process, we obtain a better picture of the COVID-19 infected individuals in the target county.
KW - COVID-19
KW - MSEIR
KW - PSO
KW - SEIRH
UR - http://www.scopus.com/inward/record.url?scp=85120579192&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-7913-1_6
DO - 10.1007/978-981-16-7913-1_6
M3 - Conference contribution
AN - SCOPUS:85120579192
SN - 9789811679124
T3 - Communications in Computer and Information Science
SP - 75
EP - 89
BT - Security and Privacy in Social Networks and Big Data - 7th International Symposium, SocialSec 2021, Proceedings
A2 - Lin, Limei
A2 - Liu, Yuhong
A2 - Lee, Chia-Wei
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2021
Y2 - 19 November 2021 through 21 November 2021
ER -