This page was initially prepared to partly document a joint effort in predicting time series of COVID19 under ILI (influenza-like illness) framework. See the CFP (PDF). See ILI Nearby. Hypothesis: We believe the mixture of seasonality and long memory must be characterized simultaneously so the prediction can make better than the best sense possible.
FOG-SEIR: Our proposed model is a generalized SEIR (G-SEIR) consisting of susceptible, insusceptible, exposed, infectious, quarantined, recovered and closed cases. The distinguishing feature of this model is the use of fractional order differential to characterize the temporal dynamics (FOG-SEIR) with a benefit of mitigations handling as well as inter-city coupling network effect. For example, social distancing rule at the macroscopic level could be captured into the (non-integer) order of the FOG SEIR model. Additionally, various stages of policies could be captured by a variable order idea in the model. These are unique aspects of the model never explored in the epidemic modeling. Much higher performance of COVID-19 spreading prediction can be achieved. For networked version of FOG-SEIR model, we can consider multi zone (cities, states) coupling effect to study the lock down effectiveness in virus spreading behaviors. Long memory and long range interaction mechanism can be both studied.
Topic-1 (MMODS): Multi-Model Outbreak Decision Support (MMODS) https://midasnetwork.us/mmods/ post-lockdown strategies
Topic-2 https://covid19forecasthub.org/doc/
News
- Feb. 2021. Nonlinear Dynamics Conferences NODYCON-2021, Rome, Italy. https://nodycon.org/2021/keynotes SPECIAL SESSION and PANEL: “Complex dynamics of COVID-19: modeling, prediction and control”
- YangQuan Chen. “Modeling, prediction, mitigation and vaccine policy for COVID-19 using big data and fractional calculus” (PPTs, Youtube)
- 1/25/21. Our first vaccine control paper is out:
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- Fudong Ge, YangQuan Chen. Optimal vaccination and treatment policies for regional approximate controllability of the time-fractional reaction–diffusion SIR epidemic systems. https://doi.org/10.1016/j.isatra.2021.01.023 ISA Transactions. Jan. 2021.
- 1/24/2021. https://midasnetwork.us/new-funding-opportunity-midas-covid-19-modeling-urgent-grant-program/ "Receding Horizon Vaccine Policy Study for COVID-19" submitted. (Yanting Zhao)
- MMODS team paper "COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support" in public https://www.medrxiv.org/content/10.1101/2020.11.03.20225409v1 (trying Nature)
- NODYCON2021 full papers submitted, reviewed, accepted.
- A fractional order age-structured generalized SEIR model: The role of “COVID-19 Symptom Data Challenge" dataset
- Prediction and control of the impact of the onset of influenza season on the spread of COVID-19
- 10/6/2020. Facebook Symptom Data Challenge entry submitted thanks to Yanting and Lihong.
- 9/14/2020. ND paper is online now with free access: Forecast analysis of the epidemics trend of COVID-19 in the USA by a generalized fractional-order SEIR model
- 08/09/2020. ND paper is online now with free access: A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects
- 8/05/2020. Our model "UCM-MESALab_FoGSEIR" is shown in https://viz.covid19forecasthub.org/
- 7/30/2020. ISA Trans. SI on COVID19 (modeling analysis control designs) submissions due, titles:
- Conghui: Forecast and fitting analysis of the outbreak of COVID-19 by a generalized fractional-order SEIR model
- Zhenzhen: The effect mitigation measures for COVID-19 by a fractional-order SEIHRDP model with individuals migration
- Yanting: Epidemiological analysis and persistent forecast of COVID-19 by a fractional order epidemic model using SLDO
- Lihong: A COVID-19 epidemic model with heterogeneity and mobility factors for re-opening study
- Weiyuan: Qualitative and quantitative analysis of the COVID-19 pandemic by a two-sides fractional order compartmental model
- Fudong: Optimal Vaccination and Treatment Policies for Regional Approximate Controllability of the Time-Fractional Reaction-Diffusion SIR Epidemic Systems
- 7/26/2020: First submission to https://covid19forecasthub.org Good job Yanting Zhao! (Github assistance: Guoxiang Zhang) and our team is now listed in the hub https://github.com/reichlab/covid19-forecast-hub/
- 7/17/2020: Project funded by the Binational Collaboration Addressing COVID-19 program under Alianza UCMX and the National Autonomous University of Mexico (UNAM). See news item here.
- 7/12/2020: Round-2 MMODS submitted. Model info: Guo L, Zhao Y, Chen Y Q. Management strategies and prediction of COVID-19 by a fractional order generalized SEIR model[J]. medRxiv, 2020. https://www.medrxiv.org/content/10.1101/2020.06.18.20134916v1
- 6/26/2020: Re-check https://covid19forecasthub.org/doc/
- 6/16/2020. MMODS two models submitted. (Effort led by Lihong Guo)
- 6/15/2020. MMODS reports uploaded to medrXiv.org
- 6/8-11. https://www.aub.edu.lb/cams/Pages/Covid19.aspx
- 6/6/2020. Some other special issues CSF, Advances in Difference Equations, Alexandria Engineering Journal.
- 6/1/2020. Welcome Mr. LUIS GARCIA-VELASQUEZ, undergraduate research summer intern suported by UROC for working on COVID-19 modeling project remotely with the group.
- 6/1/2020. MMODS Multi-Model Outbreak Decision Support (MMODS) collaboration.
- 6/1/2020. ISA Trans. Special Issue on "Modeling, Prediction and Control of COVID-19 Spreading Dynamics" CFP online
- 5/28-29, 2020: CityU HK International Forum on Data Science Approaches to the COVID-19 Pandemic [Online booklet]
- 4/27/2020. Conghui Xu, Yongguang Yu, QuanChen Yang, Zhenzhen Lu. Forecast analysis of the epidemics trend of COVID-19 in the United States by a generalized fractional-order SEIR model. https://arxiv.org/abs/2004.12541 see also https://www.medrxiv.org/content/10.1101/2020.04.24.20078493v1 (ND Special Issue “Nonlinear dynamics of COVID-19 pandemic: modeling, control, and future perspectives”) https://doi.org/10.1101/2020.04.24.20078493
- 4/26/2020. Zhenzhen Lu, Yongguang Yu, YangQuan Chen, Guojian Ren, Conghui Xu, Shuhui Wang, Zhe Yin. A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects. https://arxiv.org/abs/2004.12308 see also https://www.medrxiv.org/content/10.1101/2020.04.25.20079806v1 (ND Special Issue “Nonlinear dynamics of COVID-19 pandemic: modeling, control, and future perspectives”)
- Weekly Meeting MESA Lab group. # 4 4/2
- Weekly Meetings all. 3/26 3/30
- Weekly meeting with Sabir and Kenric since Feb. 2020.
- First MESA Lab meeting 3-19-2020. Sample reference (PDF). Dr. Chen's book on fractional processes and fractional order signal processing (PDF)
- August 15, 2019 and Jan. 17, 2020. Conghui Xu and Zhenzhen Lu gave seminar presentations to Profs. Yu and Chen.
- Global dynamics for a class of reaction-diffusion multi-group SIR epidemic model with time fractional-order derivatives
PIs:
- YangQuan Chen, Mechanical Engineering Dept, and EECS, UC Merced
- Sabir Umarov, Math Dept., University of New Haven
- Kenric Nelson
- Professor Yongguang Yu, Beijing Jiao Tong University, College of Science, Beijing, China
Team members:
- Prof. Dr. Weiyuan Ma, MESA Lab member, Visiting Professor, Math Dept., Northwestern Minzhu University, China
- Ms. Lihong Guo, MESA Lab member, Ph.D. candidate, Math. Dept., Jilin University, China
- Ms. Yanting Zhao, MESA Lab member, Ph.D. student, School of Automation Science and Engineering, University of Science and Technology of China.
- Prof. Dr. Fudong Ge, School of Information Science, China University of Geology (Wuhan), China (Regional analysis, spreading control - more info)
- Mr. Conghui Xu, Ph.D. candidate, Math. Dept. of Beijing Jiao Tong University, China
- Ms. Zhenzhen Lu, Ph.D. student, Math. Dept. of Beijing Jiao Tong University, China
Created 3/19/2020 by Professor YangQuan Chen. 4/29/20 6/16/2020 7/26 updated. 1/25/21 updated.
