Avian Influenza as a model airborne pathogen (all virus types)
Avian influenza (AI), or bird flu, refers to the many subtypes of influenza viruses that usually exclusively infect birds. Although the AI virus does not usually infect humans, some subtypes that are highly pathogenic to poultry can be zoonotic, thus causing a severe flu-like illness in humans. One example is the global spread of the highly pathogenic avian influenza virus (HPAIV) H5N1 subtype in 2003 (CDC, 2018).
The viruses causing AI represent two types of risks for humans: 1) The risk that AI virus may transmit from birds to humans and result in severe human disease, especially in areas where people and domestic birds are in contact; 2) Influenza viruses evolve and can increase the risk of human transmission either through acquiring mutations or through the exchange of genome segments between different viral subtypes. Both situations are under surveillance by Public and Veterinary health agencies as they could lead to the generation of new pandemic subtypes (WHO).
MOOD’s case study dedicated to Avian Influenza aims to design and develop sustainable Epidemic Intelligence tools to meet the needs of Public and Veterinary Health practitioners for detection, monitoring, risk assessment and response activities.
MOOD Tools for Avian Influenza
Generic data access module
Data visualisation, query, download (vector, host, environment)
Generic tools for risk mapping
PadiWeb + ProMED (to be confirmed) connected to visualisation engine (EpiVis)
- How to better identify relevant OneHealth determinants and determine risk thresholds based on data?
- How to better understand environmental risk in terms of vector distribution, vector abundance, vector capacity of transmission and the lack of competence?
- How to automatize the processing and analysis of environmental data (machine learning) for the risk assessment of vector-borne diseases?
Generic tools for event-based surveillance
1a. PadiWeb + ProMED (tbc) connected to visualisation engine (EpiVis)
MOOD Contacts for Avian Influenza
Maria Fernanda Vincenti Gonzalez
Postdoctoral Researcher at ULB, Belgium
Generic Data Access Module
E.R.G.O., United Kingdom
EBS Generic Module
Senior Research Scientist at CIRAD (TETIS group), France
Social Scientist at GERDAL
Veterinary Epidemiologist at CIRAD, France
AVIA Gis, Belgium
⦁ Review of current PADI-WEB keywords used for Avian Influenza and output (feasible in February/March)
⦁ Suggestions for improvement by Avian Influenza experts
⦁ Update/addition of keywords
⦁ Analysis of outputs
⦁ At a later stage: comparison/complementarity: LIRMM visualization versus PADI-WEB outputs
Surveillance officers involved in Avian Influenza surveillance
MOOD experts involved
Mathieu Roche (CIRAD), Elena Arsevska (CIRAD) Pascale Poncelet (LIRMM)
Mathieu Roche (CIRAD)