A hybrid model for predicting the prevalence of schistosomiasis in humans of Qianjiang City, China.

ABSTRACT:

Backgrounds/objective

Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schistosomiasis. Our aim is to explore the application of a hybrid forecasting model to track the trends of the prevalence of schistosomiasis in humans, which provides a methodological basis for predicting and detecting schistosomiasis infection in endemic areas.

Methods

A hybrid approach combining the autoregressive integrated moving average (ARIMA) model and the nonlinear autoregressive neu

SUBMITTER: Zhou L 

PROVIDER: S-EPMC4131990 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature