Predictive study of tuberculosis incidence by time series method and Elman neural network in Kashgar, China.

ABSTRACT:

Objectives

Kashgar, located in Xinjiang, China has a high incidence of tuberculosis (TB) making prevention and control extremely difficult. In addition, there have been very few prediction studies on TB incidence here. We; therefore, considered it a high priority to do prediction analysis of TB incidence in Kashgar, and so provide a scientific reference for eventual prevention and control.

Design

Time series study.

Setting kashgar, china

Kashgar, China.

Methods

We used a single Box-Jenkins method and a Box-Jenkins and Elman neural network (ElmanNN) hybrid method to do prediction analysis of TB incidence in Kashgar. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the prediction accuracy.

SUBMITTER: Zheng Y 

PROVIDER: S-EPMC7825257 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature