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An Advanced Data-Driven Hybrid Model of SARIMA-NNNAR for Tuberculosis Incidence Time Series Forecasting in Qinghai Province, China.

Yongbin WangChunjie XuYuchun LiWeidong WuLihui GuiJingchao RenSanqiao Yao
Published in: Infection and drug resistance (2020)
The best-mimicking SARIMA-NNNAR hybrid model outperforms the best-simulating basic SARIMA and NNNAR models, and has a potential application in forecasting and assessing the TB epidemic trends in Qinghai. Furthermore, faced with the major challenge of the ongoing upsurge in TB incidence in Qinghai, there is an urgent need for formulating specific preventive and control measures.
Keyphrases
  • mycobacterium tuberculosis
  • risk factors
  • south africa
  • pulmonary tuberculosis
  • emergency department
  • risk assessment