Developing a Portable Method to Predict Dengue Virus Infection (UC Berkeley)

Team Members: Hope Biswas, Eva Harris, Aubree Gordon, Sanjit Biswas and Art Reingold

School: UC Berkeley

BI Filler Photo-01Dengue virus causes the most common mosquito-borne viral disease affecting humans, with 3 billion people at risk for infection and an estimated 50 million cases each year. The goal of this project is to prevent severe illness and death from dengue through the use of a portable method in the field to identify the most at-risk patients. The first part of the project will develop risk scores to predict which patients presenting with fever in dengue-endemic areas are infected with dengue virus and of those infected, who will progress to develop severe dengue. In order for the risk scores to be used effectively in the field, the project team will also develop a mobile application for the iPhone that will enable any health professional to instantly calculate a patient’s risk score. The iPhone risk score application will enable physicians to distinguish dengue cases from cases of other illnesses that cause fever, as well as mild dengue cases from severe dengue cases, so they can provide patients with the appropriate medical care sooner. Additionally, it will help physicians prioritize the treatment of dengue cases in lowresource settings, where medical care and supplies are limited.