Georeferencing and epidemiological mapping

• Enhancement of Georeferencing GeoMedicina® System: Data processing mined from environmental, clinical, and demographic Big Data

The Pelé Pequeno Príncipe Research Institute georeferences health and environmental data by joining its geographic coordinates to indicate location on maps. In the realm of epidemiology and healthcare, georeferencing plays a crucial role in analyzing disease spatial patterns, identifying high-risk areas, and carrying out effective interventions.

Using georeferenced epidemiological data, researchers can visualize the spatial distribution of disease rates and risk factors on maps. By applying statistical and artificial intelligence methods to the georeferenced data, researchers can identify geographical clusters and potential environmental factors contributing to disease outbreaks. This resource empowers public health collaborators to develop targeted strategies, allocate resources efficiently, and implement timely interventions to mitigate the spread of diseases.

This research focuses on epidemiological, genetics, environmental factors, and clinical and patient demographics from any region using data mined from Pelé Pequeno Príncipe Research Institute’s own lab results and other public databases.

The georeferencing system of the Research Institute, known as GeoMedicina®, is used to spatially characterize disease and exposure to risk factors and estimate the environment-disease relationships through geographic statistical models. The team involved in this scientific study is constantly aggregating new data and developing new tools for the enhancement of the GeoMedicina® System.

Unlocking the potential: Bioinformatics and georeferencing interacting together

The convergence of bioinformatics and georeferencing holds great promise for advancing research in various fields. By integrating georeferenced genomic, clinical, and demographic data of more than 600 families carrying the TP53 p.R337H and XAF1 p.E134* germline mutations with mortality rates in the last 15 years in Paraná state, researchers at the Pequeno Príncipe Complex gained a spatial understanding of the intricate relationship between genetics, environment, and the prevalence of breast and adrenocortical carcinomas.

For example, combining genomic data with georeferenced health records enables the identification of genetic factors that contribute to regional disparities in disease prevalence. This knowledge can lead to public health policies and interventions, facilitating the delivery of healthcare based on population genetic predispositions and environmental context.

Information technology (IT) captures technologies of clinical research, georeferencing, and bioinformatics, acting as a condenser and compiler of information while also facilitating interaction among the involved parties. In the case of Big Data, the relationship is directly between information. The use of machine learning (learn more in the “Big Data simplified” section) contributes to model optimization processes. Translational medicine, in turn, seeks to bring scientific discoveries into healthcare practice using simpler language, as well as to provide feedback to research based on the main challenges that healthcare professionals face daily. The results – which are used in society, directly benefiting it – include new forms of diagnosis and treatment, as well as lower cost and greater effectiveness of medications.

Objective

The objective of georeferencing and epidemiological mapping is to identify environmental and genetic risk factors that may compromise human health.

Teams

Meet the teams behind this research group.

Team 1 – GeoMedicina®

• Bonald Cavalcante de Figueiredo – Pelé Pequeno Príncipe Research Institute (lead researcher)
• Humberto C. Ibañez – Pelé Pequeno Príncipe Research Institute
• Marilea V. de Camargo Ibañez – Pelé Pequeno Príncipe Research Institute
• José H. G. Balbinotti – Pelé Pequeno Príncipe Research Institute

Team 2 – SEER and CDC (USA)

• Diancarlos P. Andrade – Pequeno Príncipe College

Published articles

Check the published articles of the Big Data group about georeferencing and epidemiological mapping.

• Environmental Contaminants Modulate Breast Cancer Development and Outcome in TP53 p.R337H Carriers and Noncarriers. Gerber, et al., 2022. Cancers (Basel). 2022 Jun 19; 14(12):3014.
• Spatial trends in congenital malformations and stream water chemistry in Southern Brazil. Ibañez H, et al., 2019. Science of the Total Environment. 2019 Feb 10; 650(Pt 1):1278-1291.
• Penetrance of the TP53 R337H Mutation and Pediatric Adrenocortical Carcinoma Incidence Associated with Environmental Influences in a 12-Year Observational Cohort in Southern Brazil. Costa, et al., 2019. Cancers (Basel). 2019 Nov 16; 11(11):1804.
• Andrade DP, Marques CM, Andrade DCR, Laureano H, Lenzi L, Oliveira CS, Pereira ME, and Figueiredo, BC. Population-based assessment of major congenital malformations in the United States: smoking risk association, has now been published in Journal of Developmental Origins of Health and Disease! You can view your article at https://doi.org/10.1017/S2040174425000054.