Forecasting distribuition of oral transmission chagas disease vectors using artificial intelligence tools

• Ano de defesa: 2024
• Autor(a) principal: Picanço, Mayara Moledo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa
• Palavras-chave em Português: Barbeiro (Inseto); Chagas, Doença de - Epidemiologia; Açaí; Inteligência artificial; CIENCIAS BIOLOGICAS::PARASITOLOGIA::ENTOMOLOGIA E MALACOLOGIA DE PARASITOS E VETORES
• Link de acesso: https://locus.ufv.br/handle/123456789/33802; https://doi.org/10.47328/ufvbbt.2024.469

Chagas disease is a neglected sickness caused by the protozoan Trypanosoma cruzi, which is transmitted by kissing bugs (Hemiptera: Reduviidae: Triatominae). Currently, six to seven million people have this disease and around 75 million people worldwide are at risk of infection. In recent years, oral infection has been the prevalent form of transmission in the Brazilian Amazon, which is associated with the consumption of açaí (Euterpe oleracea). Artificial intelligence (AI) tools can be used to determine models with good predictive capacity for complex systems such as those involved in disease transmission. Thus, this thesis aimed to determine models of spatiotemporal dynamics of oral transmission of Chagas disease using AI tools. The thesis was divided into two chapters: (i) modeling key factors influencing the oral transmission of Chagas disease using artificial neural networks, and (ii) predicting current and future distribution dynamics of kissing bugs and palm species associated with oral Chagas disease transmission. Atmospheric pressure, size of the cultivated area, and time elapsed since the beginning of the açaí harvest positively affected the disease's oral transmission rate, while air temperature, rainfall, and wind speed negatively affect transmission. The developed artificial neural network (ANN) model allowed strong predictive capacity for the disease's oral transmission rate across different regions and months over a seven-year period. Ecological niche models determined using MaxEnt indicate high suitability for Rhodnius kissing bugs in northern South America, southern Central America, central Africa, and Southeast Asia. An increase in areas with high climatic suitability is expected by 2040 for these kissing bugs. Climate change will likely lead to an increase in the areas of the world suitable for Rhodnius kissing bug species involved in the oral transmission of Chagas disease. In the Amazon, where the Chagas disease oral transmission rate is high, measures must be taken for its prevention, especially during the açaí harvest season. Keywords: Triatominae. Distribution dynamics. Climate change. Epidemiology. Emerging risks.