Predicting the impact of climate change on the re-emergence of malaria cases in China using LSTMSeq2Seq deep learning model: a modelling and prediction analysis study.

Journal: BMJ open
Published Date:

Abstract

OBJECTIVES: Malaria is a vector-borne disease that remains a serious public health problem due to its climatic sensitivity. Accurate prediction of malaria re-emergence is very important in taking corresponding effective measures. This study aims to investigate the impact of climatic factors on the re-emergence of malaria in mainland China.

Authors

  • Eric Kamana
    Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China.
  • Jijun Zhao
    Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China jjzhao@qdu.edu.cn.
  • Di Bai
    Complexity Science Institute, School of Automation, Qingdao University, Qingdao, China.