Spatial prioritization of rabies zoonotic risk and applications for public health in Brazil

• Grant number: 24/20504-8
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: March 01, 2025
• End date: May 31, 2025
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Milton Cezar Ribeiro
• Grantee: Maria Eduarda Furlan
• Supervisor: David Hayman
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
• Institution abroad: Massey University, New Zealand
• Associated to the scholarship: 24/07056-6 - Inferring the circulation of the rabies virus and zoonotic risk with public health applications, BP.IC

Abstract

Economic activities in neotropical regions, particularly agricultural expansion, have led to highly fragmented landscapes, altering resources available to biodiversity and affecting species population dynamics. These environmental changes can influence species' success or decline, including the transmission of zoonotic diseases. Neotropical bats, particularly Desmodus rotundus, are impacted by such changes but benefit from fragmented areas, especially in livestock regions, which has contributed to their population growth and geographic expansion. This has significant public health implications, as D. rotundus is a key reservoir of the rabies virus (Lyssavirus ssp.). Understanding the spatial dynamics of these bats is crucial for assessing rabies circulation and zoonotic risk. This project aims to analyze rabies' zoonotic risk by examining the potential distribution of hematophagous bats, correlating it with rabies cases in livestock and humans, and landscape structure. Habitat suitability models will be used to cross-reference bat distribution with cattle herds and rabies cases. We will use updated livestock data from the Brazilian Government's Public Transparency System and a global livestock database, along with publicly available rabies case data, to estimate zoonotic risk at the highest possible spatial resolution or at the reporting municipality's centroid. The results can aid in the prevention and control of rabies, contributing to tailored disease prevention strategies and public health policy development at the municipality level.