Climatic Dynamics and Dengue Dissemination in Guatemala: A Comprehensive Research Initiative for Zoonotic Transmission 2331

Abstract Description Dengue burdens Guatemala’s healthcare system, exacerbated by global warming, and rising temperatures may facilitate the spread of the virus. We carry out prospective dengue serotyping and genotyping to assess the environmental impact on the viral spread and inform advanced preparedness, validate the novel early predictive biomarkers of disease severity in cell transcriptomics and proteomics, and develop an artificial intelligence (AI) platform to identify the dengue outbreak prediction and disease severity based on the DENV symptoms, clinical tests, plasma biomarkers, climate factor, and circulating strains we will apply two machine learning algorithm. The study employed regression adjustments and the Maximum Entropy method, an ongoing two-year prospective study on dengue serotyping within endemic regions, a temporal analysis of the daily viral load and cytokine levels (elevated IL-8, IL-10, IL-6, GM-CSF, MCP-1, IL-13, and IL-4 and decreased IL-12, MIP-1β) discharge, and finally, a machine learning algorithms. Our preliminary results showed high accuracy (AUC of 88 to 92) and identified precipitation in the coldest quarter (Bio19), temperature seasonality (Bio4), and isothermal (Bio3) as the most influential variables affecting the distribution of these species. There was a significant overlap in areas with typical temperatures of about 22 °C. The results indicate that dengue incidence may decline when temperatures rise over 30 °C and monthly precipitation above 400 mm. Funding Sources The System Virology Laboratory-Ujjwal Neogi, Department of Laboratory Medicine at the Karolinska Institue (KI). https://ki.se/en/people/ujjwal-neogi BioBox Guatemala https://bioboxgt.org/ Resultados Convocatoria Diferenciada DIGI 2024. Universidad de SanCarlos de Guatemala. Topic Categories Viral Immunology (VIR)