Mathematical models for COVID-19: applications, limitations, and potentials.
作者信息
Wang Jin
机构信息
Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA.
出版信息
J Public Health Emerg. 2020 Jun;4. doi: 10.21037/jphe-2020-05. Epub 2020 Jun 25.
Abstract
摘要
相似文献
1
Mathematical models for COVID-19: applications, limitations, and potentials.2019冠状病毒病的数学模型：应用、局限性与潜力
J Public Health Emerg. 2020 Jun;4. doi: 10.21037/jphe-2020-05. Epub 2020 Jun 25.
2
A study on the spread of COVID 19 outbreak by using mathematical modeling.一项关于使用数学模型研究新冠疫情传播情况的研究。
Results Phys. 2020 Dec;19:103605. doi: 10.1016/j.rinp.2020.103605. Epub 2020 Nov 23.
3
Strengths and limitations of mathematical models in pandemicsthe case of COVID-19 in Chile.大流行中数学模型的优势与局限性——以智利的新冠疫情为例
Medwave. 2020 Apr 8;20(3):e7876. doi: 10.5867/medwave.2020.03.7874.
4
Comments on "Optimal control analysis of a COVID-19 and tuberculosis co-dynamics model".关于《COVID-19与结核病共同动力学模型的最优控制分析》的评论
Inform Med Unlocked. 2022;32:101068. doi: 10.1016/j.imu.2022.101068. Epub 2022 Aug 29.
5
Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.《韩国 COVID-19 传播及干预的数学建模：文献综述》。
Yonsei Med J. 2023 Jan;64(1):1-10. doi: 10.3349/ymj.2022.0471.
6
A review of mathematical model-based scenario analysis and interventions for COVID-19.基于数学模型的 COVID-19 情景分析和干预措施综述。
Comput Methods Programs Biomed. 2021 Sep;209:106301. doi: 10.1016/j.cmpb.2021.106301. Epub 2021 Jul 27.
7
Mathematical Models Supporting Control of COVID-19.支持新冠疫情防控的数学模型
China CDC Wkly. 2022 Oct 7;4(40):895-901. doi: 10.46234/ccdcw2022.186.
8
9
COVID-19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy.非洲的 COVID-19 疫苗接种策略：利用数学模型为政策提供信息的范围综述。
Trop Med Int Health. 2024 Jun;29(6):466-476. doi: 10.1111/tmi.13994. Epub 2024 May 13.
10
System identification and mathematical modeling of the pandemic spread COVID-19 in Serbia.塞尔维亚新冠疫情传播的系统识别与数学建模
IFAC Pap OnLine. 2022;55(4):19-24. doi: 10.1016/j.ifacol.2022.06.003. Epub 2022 Jul 20.
引用本文的文献
1
Canada's provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses.加拿大省级 COVID-19 大流行建模工作：对数学模型及其对应对措施的影响的回顾。
Can J Public Health. 2024 Aug;115(4):541-557. doi: 10.17269/s41997-024-00910-9. Epub 2024 Jul 25.
2
How robust are estimates of key parameters in standard viral dynamic models?标准病毒动力学模型中关键参数估计的稳健性如何？
PLoS Comput Biol. 2024 Apr 16;20(4):e1011437. doi: 10.1371/journal.pcbi.1011437. eCollection 2024 Apr.
3
Enhanced SARS-CoV-2 case prediction using public health data and machine learning models.利用公共卫生数据和机器学习模型增强对2019冠状病毒病病例的预测
JAMIA Open. 2024 Feb 10;7(1):ooae014. doi: 10.1093/jamiaopen/ooae014. eCollection 2024 Apr.
4
A Mechanistic Model for Long COVID Dynamics.一种关于长期新冠病毒感染动态的机制模型。
Mathematics (Basel). 2023 Nov;11(21). doi: 10.3390/math11214541. Epub 2023 Nov 3.
5
Modeling long COVID dynamics: Impact of underlying health conditions.建模长新冠动态：潜在健康状况的影响。
J Theor Biol. 2024 Jan 7;576:111669. doi: 10.1016/j.jtbi.2023.111669. Epub 2023 Nov 15.
6
Infection prediction in swine populations with machine learning.利用机器学习预测猪群感染。
Sci Rep. 2023 Oct 18;13(1):17738. doi: 10.1038/s41598-023-43472-5.
7
A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile.一种用于分析智利 COVID-19 传播和控制模型可识别性的计算方法。
J Biol Dyn. 2023 Dec;17(1):2256774. doi: 10.1080/17513758.2023.2256774.
8
Modeling the XBB strain of SARS-CoV-2: Competition between variants and impact of reinfection.建模 SARS-CoV-2 的 XBB 株：变种之间的竞争和再感染的影响。
J Theor Biol. 2023 Oct 7;574:111611. doi: 10.1016/j.jtbi.2023.111611. Epub 2023 Aug 26.
9
Physics-Informed Neural Networks Integrating Compartmental Model for Analyzing COVID-19 Transmission Dynamics.物理信息神经网络整合房室模型分析 COVID-19 传播动力学。
Viruses. 2023 Aug 16;15(8):1749. doi: 10.3390/v15081749.
10
A two-phase fluid model for epidemic flow.一种用于疫情传播的两相流体模型。
Infect Dis Model. 2023 Jul 13;8(3):920-938. doi: 10.1016/j.idm.2023.07.001. eCollection 2023 Sep.
本文引用的文献
1
Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates.新型冠状病毒 2019-nCoV (COVID-19)：流行病学参数和疫情规模的早期估计。
Philos Trans R Soc Lond B Biol Sci. 2021 Jul 19;376(1829):20200265. doi: 10.1098/rstb.2020.0265. Epub 2021 May 31.
2
Corrigendum to "Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents" [J Hosp Infect 104 (2020) 246-251].《关于“冠状病毒在无生命表面的持久性及其被消毒剂灭活”的勘误》[《医院感染杂志》104 (2020) 246 - 251]
J Hosp Infect. 2020 Jun 17;105(3):587. doi: 10.1016/j.jhin.2020.06.001.
3
First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment.中国湖北省以外地区采取控制措施后第一波 COVID-19 的传染性和严重程度，以及第二波疫情情景规划：模型影响评估。
Lancet. 2020 Apr 25;395(10233):1382-1393. doi: 10.1016/S0140-6736(20)30746-7. Epub 2020 Apr 8.
4
Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions.公共卫生干预下中国新冠疫情趋势的改进型SEIR模型及人工智能预测
J Thorac Dis. 2020 Mar;12(3):165-174. doi: 10.21037/jtd.2020.02.64.
5
Commentary on Ferguson, et al., "Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand".评 Ferguson 等人的“减少 COVID-19 死亡率和医疗需求的非药物干预（NPIs）的影响”一文。
Bull Math Biol. 2020 Apr 8;82(4):52. doi: 10.1007/s11538-020-00726-x.
6
Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1.与严重急性呼吸综合征冠状病毒1（SARS-CoV-1）相比，严重急性呼吸综合征冠状病毒2（SARS-CoV-2）在气溶胶和表面的稳定性
N Engl J Med. 2020 Apr 16;382(16):1564-1567. doi: 10.1056/NEJMc2004973. Epub 2020 Mar 17.
7
Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2).大量未记录的感染使新型冠状病毒（SARS-CoV-2）迅速传播。
Science. 2020 May 1;368(6490):489-493. doi: 10.1126/science.abb3221. Epub 2020 Mar 16.
8
Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions.2019新型冠状病毒传播风险评估及其对公共卫生干预措施的启示
J Clin Med. 2020 Feb 7;9(2):462. doi: 10.3390/jcm9020462.
9
Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.实时预测和预报源自中国武汉的 2019-nCoV 疫情在国内和国际的潜在传播：一项建模研究。
Lancet. 2020 Feb 29;395(10225):689-697. doi: 10.1016/S0140-6736(20)30260-9. Epub 2020 Jan 31.
Zotero 插件