Developing a dengue forecast model using machine learning: A case study in China.

ABSTRACT:

Background

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue.

Methodology/principal findings

Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the supp

SUBMITTER: Guo P 

PROVIDER: S-EPMC5658193 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature