Artificial intelligence applied in the prevention, detection and control of dengue

Sinche-Crispín F.V.; Gordillo-Flores R.E.; Matos-Vila G.S.; Arias Valenzuela E.N.; Zegarra Perales A.N. · Boletin de Malariologia y Salud Ambiental (2023) · DOI: 10.52808/bmsa.8e7.63ee.001

Resumen

Dengue is one of the most important arboviruses present in tropical and subtropical climates affecting people of all ages and with an incidence in the world that continues to increase, becoming a real public health problem. It is transmitted by a human-mosquito-human cycle with the Aedes aegypti mosquito as the primary vector. Currently, it is estimated that there are between 100 and 400 million infections each year, being the most common arthropod-borne disease worldwide in terms of morbidity rate. The infection can cause a wide variety of alterations, although typically most infections are asymptomatic (80%). Currently there is no authorized prophylactic or therapeutic compound against the dengue virus, treatment is supportive and definitive diagnostic methods are not usually affordable for everyone, so technological advances have taken an important role in supporting prevention, control and early diagnosis of the disease. Artificial intelligence (AI) is a science associated with the automation of tasks and the design of intelligent systems which have a great capacity to perform multiple and advanced diagnostic and epidemiological analyzes, as well as to relate and contrast data from various sources. Several studies have shown that through AI and the use of machine learning classification algorithms, accuracy, speed, reliability and performance can be improved in the prevention, detection and control of dengue.

Instituciones: Universidad Nacional de Huancavelica; Universidad Continental; Universidad Peruana Los Andes