Real-time Forecasting of the 2014 Dengue Fever Season in Thailand | Zendy

Nicholas G Reich | Zendy; Krzysztof Sakrejda | Zendy; Stephen A. Lauer | Zendy; Derek A. T. Cummings | Zendy; Paphanij Suangtho | Zendy; Soawapak Hinjoy | Zendy; Sopon Iamsirithaworn | Zendy; Hannah Clapham | Zendy; Henrik Salje | Zendy; Justin Lessler | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Real-time Forecasting of the 2014 Dengue Fever Season in Thailand

Author(s) -

Nicholas G Reich,

Krzysztof Sakrejda,

Stephen A. Lauer,

Derek A. T. Cummings,

Paphanij Suangtho,

Soawapak Hinjoy,

Sopon Iamsirithaworn,

Hannah Clapham,

Henrik Salje,

Justin Lessler

Publication year - 2015

Publication title -

online journal of public health informatics

Language(s) - English

Resource type - Journals

ISSN - 1947-2579

DOI - 10.5210/ojphi.v7i1.5961

Subject(s) - dengue fever , infectious disease (medical specialty) , population , climate change , data science , geography , computer science , econometrics , disease , virology , medicine , environmental health , mathematics , biology , ecology , pathology

Real-time surveillance of an infectious disease in a third world country poses many problems that are not conventionally confronted by statistical researchers. As the first ones - to our knowledge - to attempt real-time forecasts of dengue fever in Thailand, we have faced these problems head-on in our quest to build a model that accurately predicts case counts in the presence of erratic reporting, shifting population dynamics, and potential climate change.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research