Overview

The MOOD project aims to develop innovative tools and open-source services in a single platform for the early detection, assessment, and monitoring of current and potential infectious disease threats in Europe in a context of global change and a profusion of big data in professional routines. Integrating research and applications, MOOD is crafting a novel Epidemic Intelligence platform involving epidemiologists, ecologists, modellers, data scientists and developers. The user-driven design of the tools and services ensures effective integration by Public Health & Animal Health (PH/AH) practitioners and surveillance officers into their epidemic intelligence/ surveillance systems and mitigation strategies. What are the risks of disease emergence? What are the drivers of disease outbreaks in specific areas? How to monitor media data? To help practitioners answers these questions, the MOOD platform will include three modules (components): 1. Data & covariates access: A one-stop “shop” for the visualization and download of relevant standardized covariates relative to the MOOD model diseases and, more generally, to infectious disease emergence in support of risk assessment and modelling; 2. Event-based Surveillance data (EBS): A visualization tool with the possibility to download data on disease outbreaks, extracted from online media news using text mining with Padi-Web, an online media monitoring tool. 3. Disease risk mapping: This module provides risk maps and other modelled outputs, aiming at highlighting areas suitable for the occurrence of (mainly) specific zoonoses in animals and humans, to support improved disease detection, monitoring and surveillance. This component is based on a set of 7 model diseases and health threats, each followed by a specific case study: HIGHLY PATHOGENIC AVIAN INFLUENZA (HPAI), WEST NILE VIRUS (WN), TICK-BORNE ENCEPHALITIS (TBE), TULAREMIA-LEPTOSPIROSIS, ZIKA-DENGUE-CHIKUNGUNYA, ANTIMICROBIAL RESISTANCE (AMR), COVID-19 (DISEASE-X).