COVID19 fractional order spreading dynamics: modeling and prediction

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

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.