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
Case Facilitator
Maria Fernanda Vincenti Gonzalez
Postdoctoral Researcher at ULB, Belgium
Generic Data Access Module
William Wint
E.R.G.O., United Kingdom
EBS Generic Module
Mathieu Roche
Senior Research Scientist at CIRAD (TETIS group), France
Case Animator
Fanny Bouyer
Social Scientist at GERDAL
MOOD Coordinator
Elena Arsevska
Veterinary Epidemiologist at CIRAD, France
Developer
Guy Hendrickx
AVIA Gis, Belgium
Process
⦁ 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
Format
Online mini-workshop(s)
Target group
Surveillance officers involved in Avian Influenza surveillance
MOOD experts involved
Mathieu Roche (CIRAD), Elena Arsevska (CIRAD) Pascale Poncelet (LIRMM)
Contact person
Mathieu Roche (CIRAD)
Process
Risk mapping techniques based on Species Distribution Models (SDMs) will be applied to disease distribution data with a careful selection of predictor variables:
- Risk mapping on the probability of disease ocurrence among wild birds based on climatic and vegetation indexes
- Georeferenced genomic sequences of conversions leading LPAI to HPAI
- Clustering
- AI transmission risk at the interface of domestic poultry and wild birds (?) to determine risk level of introduction
Format
- Risk mapping
- Publications
- Technical documents
- Codes
Target group
Surveillance officers involved in AI, experts/scientists/researchers/modellers
MOOD experts involved
tbd
Contact-person
Maria F Vincenti-Gonzalez (ULB)maria.fernanda.vincenti.gonzalez@ulb.be
Process
⦁ Consultation on additional information that would be of relevance (choice of variables)
⦁ Presentation/Availability of the data
⦁ Integration of EBS outputs with IBS for risk-mapping
⦁ Question on the possibility for users to submit data “prospectively”
MOOD experts involved
Guy Hendricks (AVIA-GIS), Willy Wint (ERGO), Pascal Poncelet (LIRMM), Karine Chalvet-Monfray (Vet-Agro sup), Xavier Bailly (INRAE), Markus Neteler (mundialis)
Contact person
AVIA-gis
Target group
HPAI experts/scientists/researchers/modellers for data repository; Decision-makers/General public for maps
- First contact with participating potential end-users from FAO, EFSA, ESA platform from Cirad and INRAE;
- Despite moderate data availability on HPAI, public and animal health surveillance practitioners (users) expressed that further collaboration on data-sharing would be very benefitting;
- Users also found that risk mapping with different covariates, including wild bird species, is a topic of interest for HPAI;
- Two scenarios were emphasized for HPAI: risk of introduction and risk of the outbreak;
- Determining the interface between wild birds and poultry is relevant for determining the risk of introduction;
- Need to harmonize vocabulary among different platforms;
- Relevant questions:
Which is the best admin level?
How often are covariates updated?
Does the migration map from EFSA have an API that can be used? - HPAI Study case facilitator reminded that ULB-SpELL lab can support further modeling/analytical questions about HPAI.