Improving Disease Management for HandFoot-Mouth Disease in Southwest China by Data Analytics

  • Xi Li , Peng Luo, Junhua Wang , Bernard T Han, Jiangping Zhang, Lulu Chen , Xiao Zhang

Abstract

Background: To improve health literacy, we used big data analysis to search for deep
information and used Electronic Medical Records software to analyze much of the healthcare
data, from individual to population data, to provide references for Hand-Foot-Mouth disease
(HFMD) in Southwest China. Methods: The data were supplied by the CDC in Southwest
China, and “Big Data” were cleaned for health analytics with popular tools – R and the
analytical methods of ARIMA – to develop an HFMD prediction model for disease prevention
and thus disease management. Results: The predictive model shows that in the coming 5 years,
the incidence of Hand-foot-Mouth disease will fluctuate. Conclusions: From our study, we still
need to increase our efforts to control HFMD in Southwest China to prevent epidemic-level
disease spread. The government needs to provide more funding for Hand-Foot-Mouth disease,
and the community needs to provide more educational information to the people to help them
improve their health literacy and improve their quality of life.

Published
2020-06-30
How to Cite
Xi Li , Peng Luo, Junhua Wang , Bernard T Han, Jiangping Zhang, Lulu Chen , Xiao Zhang. (2020). Improving Disease Management for HandFoot-Mouth Disease in Southwest China by Data Analytics. Design Engineering, 552 - 563. https://doi.org/10.17762/de.vi.553
Section
Articles