Joint Spatio-temporal modeling of co-occurrence of Zika and chikungunya incidence and their climate-environmental-socioeconomic factors, Brazil

• Grant number: 24/01315-0
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: April 29, 2024
• End date: October 25, 2024
• Field of knowledge: Health Sciences - Collective Health - Epidemiology
• Principal Investigator: Francisco Chiaravalloti Neto
• Grantee: Raquel Gardini Sanches Palasio
• Supervisor: Monica Pirani
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Imperial College London, England
• Associated to the scholarship: 21/10212-1 - "Spatial-temporal modeling of Zika and chikungunya in Brazil considering three different geographic scales and climate change", BP.PD

Abstract

Chikungunya and Zika are arboviruses that present similar signs and symptoms, making clinical and laboratory diagnosis difficult; they are transmitted by the same vectors, Aedes aegypti and Ae. albopictus. Their occurrence is likely related to the same climatic, environmental, and socioeconomic factors; a simultaneous occurrence in space and time is expected. Furthermore, the Pan American Health Organization warns of an increase in the number of cases and deaths from chikungunya and Zika in America and Brazil above those reported in recent years. This study aims to model the spatiotemporal pattern of the co-occurrence of Zika and chikungunya between 2015 and 2022 in Brazilian municipalities. Spatiotemporal models will be created to jointly analyze the incidence of Zika and chikungunya, assessing the role of environmental (climatic included), sociodemographic, and socioeconomic factors and using Bayesian statistics with the INLA approach. Data on precipitation, temperature, altimetry, vegetation index in urban areas, deprivation, mobility, percentage of vegetated and urbanized areas, percentage of households served with a sewage network, piped water, and garbage collection will be used. With the results of this work, we will be able to predict the risk areas for the co-occurrence of these diseases in Brazil. With this, we will contribute to choosing priority areas for implementing entomological and epidemiological surveillance and control activities, aiming to avoid or minimize their occurrences.