Identifying pre-outbreak signals of hand, foot and mouth disease based on landscape dynamic network marker

BMC Infectious Diseases

Yucong Pan¹  Xuhang Zhang²  Rong Xie³  Rui Liu⁴  Zhengrong Liu⁴  Pei Chen⁴ 

[1] Guangdong Science and Technology Infrastructure Center;School of Computer Science and Engineering, South China University of Technology;School of Information, Guangdong University of Finance and Economics;School of Mathematics, South China University of Technology;

关键词: Hand, foot and mouth disease (HFMD) outbreaks;    Pre-outbreak signals;    Critical transition;    City network;    Landscape dynamic network marker (L-DNM);   

DOI  :  10.1186/s12879-020-05709-w

来源: DOAJ

【 摘 要 】

Abstract Background The high incidence, seasonal pattern and frequent outbreaks of hand, foot and mouth disease (HFMD) represent a threat for billions of children around the world. Detecting pre-outbreak signals of HFMD facilitates the timely implementation of appropriate control measures. However, real-time prediction of HFMD outbreaks is usually challenging because of its complexity intertwining both biological systems and social systems. Results By mining the dynamical information from city networks and horizontal high-dimensional data, we developed the landscape dynamic network marker (L-DNM) method to detect pre-outbreak signals prior to the catastrophic transition into HFMD outbreaks. In addition, we set up multi-level early warnings to achieve the purpose of distinguishing the outbreak scale. Specifically, we collected the historical information of clinic visits caused by HFMD infection between years 2009 and 2018 respectively from public records of Tokyo, Hokkaido, and Osaka, Japan. When applied to the city networks we modelled, our method successfully identified pre-outbreak signals in an average 5 weeks ahead of the HFMD outbreak. Moreover, from the performance comparisons with other methods, it is seen that the L-DNM based system performs better when given only the records of clinic visits. Conclusions The study on the dynamical changes of clinic visits in local district networks reveals the dynamic or landscapes of HFMD spread at the network level. Moreover, the results of this study can be used as quantitative references for disease control during the HFMD outbreak seasons.

【 授权许可】

Unknown