@inproceedings{fa55524025454f8e8f8cc1001f5245a7,
title = "Modeling Dynamics of Covid-19 Infected Population with PSO",
abstract = "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.",
keywords = "COVID-19, MSEIR, PSO, SEIRH",
author = "Guangdong Huang and Aihua Li",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; null ; Conference date: 19-11-2021 Through 21-11-2021",
year = "2021",
doi = "10.1007/978-981-16-7913-1_6",
language = "English",
isbn = "9789811679124",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "75--89",
editor = "Limei Lin and Yuhong Liu and Chia-Wei Lee",
booktitle = "Security and Privacy in Social Networks and Big Data - 7th International Symposium, SocialSec 2021, Proceedings",
}