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Predictive ecological modeling for Brazilian Spotted Fever occurrence in the State of São Paulo

Grant number: 19/13505-0
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): October 28, 2019
Effective date (End): April 27, 2020
Field of knowledge:Health Sciences - Collective Health - Public Health
Principal researcher:Adriano Pinter dos Santos
Grantee:Claudia Araujo Scinachi
Supervisor abroad: Andrew Townsend Peterson
Home Institution: Superintendência de Controle de Endemias (SUCEN). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil
Research place: University of Kansas, United States  
Associated to the scholarship:17/05255-8 - Avaliation of domestic dogs as competent amplifier hosts to the bacterium Rickettsia rickettsii to Amblyomma aureolatum ticks and predictive spacial ecological modeling for occurrence of Brazilian Spotted Fever in the State of São Paulo, BP.DR


Brazilian Spotted Fever (BSF) is a vector-borne zoonosis that has the bacteria Rickettsia rickettsii as pathogenic agent. In the São Paulo Metropolitan Region (SPMR), the vector responsible for the transmission is the tick Amblyomma aureolatum, which depends on typical environmental characteristics of the Atlantic Forest biome to survive (temperature and humidity). As known, spatial ecology is based on the determination of the role of space in ecological processes at local and global scale, and one of its objectives is to determine which factors influence species distribution. This can also help to determine disease distribution and transmission risk. The BSF distribution in the SPMR is associated with the presence of the vector as well as the ecological profile of the area (degradation of the forest in contact with the urban matrix). This study intends to determine, through spatial modeling using Maxent, which areas are more or less likely to present BSF cases taking into account the conditions necessary for the occurrence of the vetor A. aureolatum, as well as the ecological aspects that facilitate the interaction of the vector with its hosts in the environment. The results could help to anticipate the occurrence of the disease, facilitating the epidemiological surveillance and the evaluation of priority areas for preventive and control actions.

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