PICTUREE—Aedes: A web application for dengue data visualization and case prediction

Authors: YI, CHUNLIN - Kansas State University; VAJDI, ARAM - Kansas State University; FERDOUSI, TANVIR - Kansas State University; Cohnstaedt, Lee; SCOGLIO, CATERINA - Kansas State University

Submitted to: Pathogens
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/19/2023
Publication Date: 5/29/2023
Citation: Yi, C., Vajdi, A., Ferdousi, T., Cohnstaedt, L.W., Scoglio, C. 2023. PICTUREE—Aedes: A web application for dengue data visualization and case prediction. Pathogens. 12(6):771. https://doi.org/10.3390/pathogens12060771.
DOI: https://doi.org/10.3390/pathogens12060771

Interpretive Summary: Dengue fever is a significant public health concern in many tropical and subtropical countries, with more than 400 million people infected yearly. Dengue virus is transmitted by Aedes genus mosquitoes, specifically Aedes albopictus and Aedes aegypti. PICTUREE—Aedes (Predicting Insect Contact and Transmission Using histoRical Entomological and Environmental data) is a tool that can assess dengue transmission risk in a timely manner world-wide. This research describes a web page which can collect and analyze dengue-related data, display simulation results, and forecast outbreak incidence. PICTUREE—Aedes automatically updates global temperature and precipitation data and contains historical records of dengue incidence (1960 – 2012) and Aedes mosquito occurrences (1960 - 2014) in its database. The application utilizes a mosquito population model to estimate mosquito abundance, dengue cases, and dengue risk. To predict future dengue outbreak incidence, PICTUREE—Aedes applies various forecasting techniques which are all based on user-entered case data. The PICTUREE—Aedes’ risk estimation identifies favorable conditions for potential dengue outbreaks, and its forecasting accuracy is validated by available outbreak data from Cambodia.

Technical Abstract: Dengue fever remains a significant public health concern in many tropical and subtropical countries, and there is still a need for a system that can effectively combine global risk assessment with timely incidence forecasting. This research describes an integrated application called PICTUREE—Aedes, which can collect and analyze dengue-related data, display simulation results, and forecast outbreak incidence. PICTUREE—Aedes automatically updates global temperature and precipitation data and contains historical records of dengue incidence (1960 – 2012) and Aedes mosquito occurrences (1960 - 2014) in its database. The application utilizes a mosquito population model to estimate mosquito abundance, dengue reproduction number, and dengue risk. To predict future dengue outbreak incidence, PICTUREE—Aedes applies various forecasting techniques, including the ensemble Kalman filter, recurrent neural network, particle filter, and super ensemble forecast, which are all based on user-entered case data. The PICTUREE—Aedes’ risk estimation identifies favorable conditions for potential dengue outbreaks, and its forecasting accuracy is validated by available outbreak data from Cambodia.