Development of a Recurrent Neural Network Model for Prediction of Dengue Importation

Description: 

In recent years, mosquito-borne diseases such as Zika, chikungunya, and dengue have become particularly problematic due to global climate change. Rising temperatures and changes in precipitation are considered to be associated with habitat suitability of mosquito vectors and viruses. To address such cross-border infectious diseases, countries have come up with various strategies to control and manage mosquito-borne diseases. In line with this, international efforts have been made to minimize the burden of global infectious diseases. In 2014, Global Health Security Agenda (GHSA) has been launched in collaboration with the international organizations, member countries of GHSA, and non-governmental organizations in order to improve national and global capacities against global public health threat. In addition, various quarantine programs have been operated in and between countries borderlines and airports with cutting edge ICT technologies. These efforts could be made more effective when the authorities have reliable predicted future trends or events, utilize their capacities more efficiently and provide timely alerts to the public. However, very few studies have been conducted to deal with imported disease, while much attention has been paid to the endemic diseases. In this study, we aim to develop a prediction model for imported infectious disease by using the approach of ANN. We have chosen to model the imported cases of dengue in Korea, as the number of imported dengue cases is larger than other mosquito-borne diseases. Additionally, Japan, one of South Korea's neighboring countries, has recently experienced autochthonous dengue virus transmission, which has raised concerns about localization in Korea as well as in Japan.

Objective: We aim to develop a prediction model for the number of imported cases of infectious disease by using the recurrent neural network (RNN) with the Elman algorithm, a type of artificial neural network (ANN) algorithm. We have targeted to predict the number of imported dengue cases in South Korea as the number of dengue cases is greater than other mosquito-borne diseases.

Primary Topic Areas: 
Original Publication Year: 
2019
Event/Publication Date: 
January, 2019

June 18, 2019

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