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Study of spatial statistics methods to evaluate the association between dengue incidence and proximity to places hypothesized as sources of increased risk in Campinas municipality, Brazil

Grant number: 19/22787-9
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): February 01, 2021
Effective date (End): April 30, 2021
Field of knowledge:Humanities - Geography - Human Geography
Principal researcher:Marcos César Ferreira
Grantee:Jessica Andretta Mendes
Supervisor abroad: Sophie Vanwambeke
Home Institution: Instituto de Geociências (IG). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Research place: Universitè Catolique de Louvain (UCL), Belgium  
Associated to the scholarship:17/19446-0 - Influence of proximity to potential risk properties on the incidence of Dengue, in the city of Campinas, São Paulo, Brazil, BP.DR


The main purpose of the doctorate project which is under FAPESP financial support is to seek if there is any relationship between dengue occurrences and supposed focus (buildings with characteristics that favor the emergence and development of Aedes aegypti or are points of dissemination of dengue virus, due to the great flow and circulation of people). Recognizing the importance of spatial analysis and statistical techniques to conduct the research proposed in the original project, we believe that it is important to improve the knowledge of some techniques and to learn new ones. First, we are going to evaluate the spatial distribution of dengue cases, using smoothing functions, such as Kernel, and seek for possible clusters of dengue incidence, applying a set of classic global and local clustering methods, including Moran's I, Ripley's K, GI*, LISA, and Spatial Scan Statistic. Then, to evaluate the effect of the distance of supposed focus we intend to use distance ranges around these buildings and to apply statistical methods such as Stone's test, score tests and logistic regressions techniques. Some of these methods were proposed in the initial project and others are proposed to complement the research. We hope that this Research Internship Abroad can be an opportunity to expand knowledge and experience about methods and techniques of spatial analysis and spatial statistics. Therefore, this opportunity of knowledge exchange could contribute to define which of these methods and techniques offer the best results to the proposed doctorate project. (AU)

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