Agent-Based Modeling of COVID-19 Transmission in Philippine Classrooms

被引:0
|
作者
Macalinao, Rojhun O. [1 ]
Malaguit, Jcob C. [1 ]
Lutero, Destiny S. [1 ]
机构
[1] Univ Philippines Los Banos, Inst Math Sci & Phys, Coll Arts & Sci, Los Banos, Philippines
关键词
agent-based (multi-agent) modeling; classroom modeling; COVID-19; transmission; Philippines; disease modeling;
D O I
10.3389/fams.2022.886082
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Onsite classes in the Philippines have been prohibited since March 2020 due to the SARS-CoV-2 which causes the COVID-19. This forced millions of learners to adapt with new modes of instruction that may not be optimal for their learning. In this study, we implemented an agent-based model in Netlogo that followed common classroom layouts to assess the effects of human interactions to virus transmission. Results show that the highest value of cumulative proportion of infected individuals inside the classroom (CPI) is achieved when the total allowable seating capacity in the classroom is increased from 25 to 50%. Also, varying transmission rates between 5 and 20% does not pose any significant effect on CPI. Furthermore, in three of the four seating arrangements, allowing in-class mobility and class rotations can pose significant increases in CPI averaging from 40 to 70%. Results also showed that factors including maximum number of students and number of initially infected individuals, significantly affect the likelihood of infection apart from the seating arrangement itself. To minimize the risk of transmission inside the classroom setup considered, it is vital to control these factors by adhering to mitigation efforts such as increased testing and symptoms checking, limiting the maximum number of students, and redefining breaks and class rotations.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling
    Rebecca J. Rockett
    Alicia Arnott
    Connie Lam
    Rosemarie Sadsad
    Verlaine Timms
    Karen-Ann Gray
    John-Sebastian Eden
    Sheryl Chang
    Mailie Gall
    Jenny Draper
    Eby M. Sim
    Nathan L. Bachmann
    Ian Carter
    Kerri Basile
    Roy Byun
    Matthew V. O’Sullivan
    Sharon C-A Chen
    Susan Maddocks
    Tania C. Sorrell
    Dominic E. Dwyer
    Edward C. Holmes
    Jen Kok
    Mikhail Prokopenko
    Vitali Sintchenko
    [J]. Nature Medicine, 2020, 26 : 1398 - 1404
  • [22] Alternative COVID-19 mitigation measures in school classrooms: analysis using an agent-based model of SARS-CoV-2 transmission
    Woodhouse, M. J.
    Aspinall, W. P.
    Sparks, R. S. J.
    Brooks-Pollock, E.
    Relton, C.
    [J]. ROYAL SOCIETY OPEN SCIENCE, 2022, 9 (08):
  • [23] Agent-based Modeling of COVID-19 Infection Rate vis-a-vis the Philippine Government Community Quarantine and Face Covering Measures
    Agustin, Alfonso D.
    Ferrer, Justine C. Mark
    Bolingot, Harold Jay M.
    Celestre, John Donnie, I
    Oppus, Carlos M.
    Monje, Jose Claro N.
    [J]. 2021 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL, CONTROL AND INSTRUMENTATION ENGINEERING (IEEE ICECIE'2021), 2021,
  • [24] A stochastic agent-based model to evaluate COVID-19 transmission influenced by human mobility
    Chen, Kejie
    Jiang, Xiaomo
    Li, Yanqing
    Zhou, Rongxin
    [J]. NONLINEAR DYNAMICS, 2023, 111 (13) : 12639 - 12655
  • [25] COVID-19 Transmission Risks Assessment using Agent-Based Weighted Clustering Approach
    Sagar, P. Vidya
    Kumar, T. Pavan
    Chaitanya, G. Krishna
    Rao, Moparthi Nageswara
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (11) : 532 - 537
  • [26] An agent-based transmission model of COVID-19 for re-opening policy design
    Rodriguez, Alma
    Cuevas, Erik
    Zaldivar, Daniel
    Morales-Castaneda, Bernardo
    Sarkar, Ram
    Houssein, Essam H.
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2022, 148
  • [27] A stochastic agent-based model to evaluate COVID-19 transmission influenced by human mobility
    Kejie Chen
    Xiaomo Jiang
    Yanqing Li
    Rongxin Zhou
    [J]. Nonlinear Dynamics, 2023, 111 : 12639 - 12655
  • [28] An agent-based transmission model of COVID-19 for re-opening policy design
    Rodríguez, Alma
    Cuevas, Erik
    Zaldivar, Daniel
    Morales-Castañeda, Bernardo
    Sarkar, Ram
    Houssein, Essam H.
    [J]. Computers in Biology and Medicine, 2022, 148
  • [29] COVID-19 Transmission Risks Assessment using Agent-Based Weighted Clustering Approach
    Sagar P.V.
    Kumar T.P.
    Chaitanya G.K.
    Rao M.N.
    [J]. International Journal of Advanced Computer Science and Applications, 2020, 11 (11): : 532 - 537
  • [30] An LBS and agent-based simulator for Covid-19 research
    Du, Hang
    Yuan, Zhenming
    Wu, Yingfei
    Yu, Kai
    Sun, Xiaoyan
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)