GeoEPI

Spatio-Temporal Epidemiology of Emerging Viruses

Overview

The geoEpi project explores the spatio-temporal dynamics of emerging viruses, including SARS-CoV-2, Dengue, Chikungunya, Yellow Fever, Zika, and Ebola. These viruses pose significant global health challenges, and understanding the factors influencing their spread is crucial for improving disease monitoring and response.

By combining geodata and official health surveillance records, geoEpi seeks to enhance early disease detection and provide more accurate predictions about the spread of infectious diseases.

Project Goals

The project aims to develop innovative approaches for analyzing disease dispersal patterns by integrating multiple data sources and using machine learning techniques.

A particular focus lies in understanding how environmental conditions, land use, transport networks, and human movement patterns influence disease outbreaks. By quantifying these interactions, geoEpi aims to provide a more comprehensive framework for predicting and mitigating the spread of emerging viruses.

Methodology

Incorporating temporal dynamics into spatial epidemiology to improve outbreak monitoring.

Combining geodata with official health surveillance records for fine-scale disease tracking.

Developing machine learning algorithms to handle large-scale data and enhance traditional epidemiological models.

Identifying “socio-ecological corridors” that describe likely disease spread pathways based on mobility, demographic, and environmental factors.

Geovisual Analyics Tool for Dengue Serotypes

GeoDEN is a visual analytics tool created to help dengue researchers and epidemiologists better understand how DENV serotypes move and interact among populations.