Real-Time Forecasting of Hand-Foot-and-Mouth Disease Outbreaks using the Integrating Compartment Model and Assimilation Filtering

Zhicheng Zhan, Weihua Dong (Corresponding Author), Yongmei Lu, Peng Yang, Quanyi Wang, P. Jia

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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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.
Original languageEnglish
Article number2661
Pages (from-to)1-9
Number of pages9
JournalScientific reports
Volume9
DOIs
Publication statusPublished - 25 Feb 2019

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD

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