West Nile Virus as a model for exotic pathogens transmitted by endemic vectors
West Nile virus (WNV) infection is a mosquito-borne zoonosis that is endemo-epidemic in Europe, affecting several countries in southern, eastern and western Europe. WNV incidence is increasing in Europe and its presence is expanding into new areas where it had never been observed before, becoming a global public health concern.
The virus is transmitted among host birds mainly via the bite of infected mosquitoes and incidentally, humans and other mammals may become infected. A number of abiotic (environmental) and biotic factors are known to determine its transmission dynamics.
Temperatures have been reported as one of the important environmental drivers influencing WNV transmission in suitable habitats in Europe as it affects either mosquito breeding success and the extrinsic incubation of the virus.
In face of climatic change, anomalous summer temperatures are considered among the factors affecting the incidence rate and the emergence of the virus into new areas, often associated with new cases in Europe.
Following the analysis of the needs expressed by Public Health and Veterinary Health practitioners from five different countries, MOOD is now working on the WNV case study, as a model for exotic pathogens transmitted by endemic vectors. Leading research experts, Public Health representatives (end-users), data and computer scientists and web developers are joining forces over the next two years to design and develop sustainable Epidemic Intelligence tools that will enhance preparedness and response to current and future WN outbreaks.
WN Tools
Generic tools for event-based surveillance
1a. PadiWeb + ProMED (tbc) connected to visualisation engine (EpiVis)
General 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 data access module
Data visualisation, query, download (vector, host, environment)
MOOD contacts for WN
Developer
Guy Hendricks
Avia-GIS
Case Animator
Fanny Bouyer
Social Scientist at GERDAL
MOOD Coordinator
Elena Arsevska
Veterinary Epidemiologist at CIRAD, France
Activities & Updates
Process
⦁ Review of current PADI-WEB keywords used for WN and output (feasible in February/March)
⦁ Suggestions for improvement by WN 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 WN surveillance
MOOD experts involved
Mathieu Roche (CIRAD), Elena Arsevska (CIRAD) Pascale Poncelet (LIRMM)
Contact person
Mathieu Roche (CIRAD)
Updates from 23-24 June 2022:
- Integration with existing Epidemic Intelligence tools will be taken into account by our developers to improve uptake of the product. The possibility for a national end-user/surveillance practitioner to load his/her own data in an offline version to compare EBS and IBS data would be a relevant feature of the visualization tool to be developed. One important point to keep in mind is that one needs to proceed with caution when using un-confirmed and unstructured event-based surveillance data and that human involvement is an important step in data validation. End users willing to try using Padi-web can send a mail to padi-web@cirad.fr to get access to the platform.
Process 1)
⦁ Literature review relevant to WN risk mapping
Process 2)
- Ecological niche modelling for WN
Format
TBD
Target group
WN experts/scientists/researchers/modellers
MOOD experts involved
Francesca Dagostin (FEM), Annapaola Rizzoli (FEM), Valentina Tagliapietra (FEM), Giovanni Marini (FEM), Gaëlle Nicolas (AVIA-GIS)
Contact-person
Francesca Dagostin (FEM)
Updates from 23-24 June 2022:
At this stage, MOOD will provide static risk maps updated yearly/monthly (TBD) that should be sufficient for the needs of surveillance practitioners. Another relevant feature of WNV risk maps will be the estimation of seasonality and transmission magnitude of the disease, so that surveillance practitioners know when to enhance surveillance efforts.
Risk maps and models will be described in great detail for end-users to have a complete understanding of disease drivers.
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
Cedric Marsboom (AVIA-GIS), Willy Wint (ERGO), Pascal Poncelet (LIRMM), Karine Chalvet-Monfray (Vet-Agro sup), Xavier Bailly (INRAE), Markus Neteler (mundialis)
Contact person
Cedric Marsboom (AVIA-GIS)
Target group
WN experts/scientists/researchers/modellers for data repository; Decision-makers/General public for maps
Updates from 23-24 June 2022:
Data will be made available on continental and national levels with a maximum resolution of 1 square kilometre, as well as, readily available with standardized polygons (NUTS3), but users will also have the possibility to upload their own shapefile with specific geographical units (polygons) and retrieve data prepared accordingly via an FTP link made available within a few days depending on the complexity of the request. Time series data will be updated yearly, while data reduction will be conducted every two years.
The MOOD platform will also provide guidance to end-users, with a comparison of different data sources for a similar parameter with a description of their strengths and weaknesses as well as a dashboard on which variables have been previously and most commonly used for modelling TBE and WNV.
Upcoming meetings
Any question? Contact MOOD!
Content validated by Annapaola Rizzoli (FEM), Elena Arsevska (CIRAD), and Fanny Bouyer (GERDAL)