Real-Time Forecasting of Hand-Foot-and-Mouth Disease Outbreaks using the Integrating Compartment Model and Assimilation Filtering
Date
2019-02
Authors
Zhan, Zhicheng
Dong, Weihua
Lu, Yongmei
Yang, Peng
Wang, Quanyi
Jia, Peng
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Publishing Group
Abstract
Hand-foot-and-mouth disease (HFMD) is a highly contagious viral infection, and real-time predicting of HFMD outbreaks will facilitate the timely implementation of appropriate control measures. By integrating a susceptible-exposed-infectious-recovered (SEIR) model and an ensemble Kalman filter (EnKF) assimilation method, we developed an integrated compartment model and assimilation filtering forecast model for real-time forecasting of HFMD. When applied to HFMD outbreak data collected for 2008-11 in Beijing, China, our model successfully predicted the peak week of an outbreak three weeks before the actual arrival of the peak, with a predicted maximum infection rate of 85% or greater than the observed rate. Moreover, dominant virus types enterovirus 71 (EV-71) and coxsackievirus A16 (CV-A16) may account for the different patterns of HFMD transmission and recovery observed. The results of this study can be used to inform agencies responsible for public health management of tailored strategies for disease control efforts during HFMD outbreak seasons.
Description
Keywords
hand-foot-and-mouth disease, viral infections, outbreaks, public health management, Geography and Environmental Studies
Citation
Zhan, Z., Dong, W., Lu, Y., Yang, P., Wang, Q., & Jia, P.. (2019). Real-Time Forecasting of Hand-Foot-and-Mouth Disease Outbreaks using the Integrating Compartment Model and Assimilation Filtering. Scientific Reports, 9(2661).
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Rights Holder
© 2019 The Authors.
Rights License
This work is licensed under a Creative Commons Attribution 4.0 International License.