This document describes how spatial analysis was used to identify risk areas for Highly Pathogenic Avian Influenza (HPAI) in Europe and evaluate current health surveillance strategies. Logistic regression and co-kriging models were developed using data on HPAI cases, wetlands, poultry density, and temperature. Risk maps identified high-risk areas and hotspots. The models also showed that current surveillance sampling was not well matched to risk, missing some high-risk areas. Spatial analysis is a useful tool for targeting surveillance to areas most likely to benefit from control measures. This can help reduce health costs and improve prevention and control of animal diseases.

1. Spatial analysis to identify risk areas
of an important animal disease
(Highly Pathogenic Avian Influenza)
and to evaluate current strategy
in health surveillance in Europe
Irene Iglesias iglesias@inia.es
Marta Martínez
Ana de la Torre
Mª Jesús Muñoz
JM Sánchez-Vizcaíno
(CISA-INIA UCM)

2. Animal diseases control
Affected animals and.....:
Trade in animal products
Vaccines
Control of disease: loss of livestock, compensation, health costs
Public confidence
......

3. Animal diseases control
Tuberculosis
Zoonotics Salmonella
Avian Influenza
…

4. Animal diseases control
Affected countries: stop spread
Free countries: early detection
Preventive
surveillance

5. Animal diseases control: SURVEILLANCE
random sampling
system
Preventive
surveillance

6. Animal diseases control: SURVEILLANCE
massive expansion
avian influenza
TARGET
SURVEILLANCE
Risk
assessment
random sampling
system
Preventive
EC 2010/367/EU
surveillance

7. Animal diseases control: SURVEILLANCE
TARGET
SURVEILLANCE
Risk
assessment
G.I.S.
Spatial analysis:
Exploring data
Risk assessment
Preventive
Modelling diseases surveillance

8. HighlyPathogenicAvianInfluenza
( SubtypeH5N1)
• Affected countries (2004-2010)

9. has killed ≈ 400 million domestic birds
artsandopinion.com new.dpi.vic.gov.au Cbc.ca
High economic losses ≈ ($20 billion)
Social alarm :332 fatal human cases
HighlyPathogenicAvianInfluenza
( SubtypeH5N1)

10. • has killed ≈ 400 million domestic birds
The main difference...
Natural reservoir Affected birds
Has killed ≈ 15.000 waterbirds
Highly Pathogenic Avian Influenza
( Subtype H5N1)

11. In the last 4 years...
Spread in Europe •Trade poultry
•Migrationrouteswaterbirds
HighlyPathogenicAvianInfluenza
( SubtypeH5N1)

12. Spatial analysis to identify risk areas
of Highly Pathogenic Avian Influenza
and to evaluate current strategy of
health surveillance in Europe

13. Spatial analysis process: Modelling
Data base
Visualization
Exploration
Statistics
Useful & efficient decision-
Modelling making tool for different
epidemiological situations
in animal health

14. Data base
Avian Influenza Avian Influenza
Cases in domestic birds Cases in wildbirds Modelling with G.I.S.
Domestic birds Wildbirds
Census/farms/location Census/location

15. WHERE should we do an efficient surveillance of
Avian Influenza in wildbirds???
TARGET
SURVEILLANCE

16. Spatial analysis to identify risk areas
of Highly Pathogenic Avian Influenza
in waterbirds

17. Importance of wetlands in spread of Avian _Influenza
1. Infected water represents a recognized mechanism for the virus transmission
within waterbird populations
2. Wetlands concentrate many waterbirds species → Increasing the risk of infection

18. Modelizationof ENVIRONMENTAL RISK FACTOR for European WETLANDS
Ramsar European Wetlands (Wetlands.org)
Distances
Avian influenza cases in wild birds (06-09)
!
( Ramsar wetland
Wetlands
Wildbirds outbreaks
Outbreaks
Infected wetlands
“Positive wetland”
Infected wetlands
Europe
16Km
• Analysis tools
• Spatial analysis

19. Modelizationof ENVIRONMENTAL RISK FACTOR for European WETLANDS
Water: Salinity, permanence
organic or mineral soil, ....
Study wetlands characteristics Land Use: Forestry, hunting,
Agriculture, aquaculture,...
Biological: Wintering birds area,
Logistic regression species, important area for fish..
analysis
•Mixosaline water
•Forestry around wetland
•Wintering waterbird area • Analysis tools
• Spatial analysis
Identification of risk factors
• Logistic regression

20. Risk map for ocurrence of Avian Influenza in wildbirds
Logistic regression model
GERMANY
! Ramsar wetland
(
2009
Waterbird cases
“Infected wetlands”
Europa
ROMANIA 2010
BULGARIA
2010
USEFUL
INFORMATION • Spatial analysis:
ON TARGET Kernel
SURVEILLANCE

21. Aplication of the model a national level: Spain
Logistic regression model Increased Nº wetlands
•Wetlands Ramsar+Spanish Wetlands
(NationalDatabase)
Interpolate data model : IDW
(Inverse Distance Weighting)
Provinces
Risk of model
High: 0.83
Low:0.10
Survival by temperature analysis
Adjust risk by climatic data
( temperature analysis)
Survival curve
• Geostatistical analysis:
IDW

22. MCD Logistic regression model
Multicriteria
Decision:
Salburua
Wildbird case in Pais Vasco (2006)
Almoguera
Farm affected
contact with wildbirds
(2009)
Provinces
Risk values (October)
October)
High
Low • Spatial analysis:
Europe
Math
Risk of ocurrence of Avian Influenza in
wildbirds

23. MCD Logistic regression model
Multicriteria USEFUL
Decision: INFORMATION
IMPROVE
SURVEILLANCE
PLANS
2006 High Surveillance Areas
Of the National surveillance Plan
(Ministery Agriculture and Food)
Provinces
Risk values (October)
October)
High
Low
Europe
Risk of ocurrence of Avian Influenza in
wildbirds

24. Spatial analysis to EVALUATE current
strategy in health surveillance in Europe.

25. Probability of ocurrence of Avian Influenza
Test points Co-kriging
Avian Influenza cases
+ co-variable
Wetlands (>20.000 Waterbirds)
• Geostatistical analysis:
Co-kriging
+ co-variante
Poultry density

26. Probability of ocurrence of Avian Influenza
Co-kriging
• Geostatistical analysis:
Co-kriging

27. Probability of ocurrence of Avian Influenza
Co-kriging
USEFUL
INFORMATION
EVALUATE
SURVEILLANCE
STRATEGIES
NL
DE
SP
Sampling> Risk Avian Influenza
$ • Geostatistical analysis:
Co-kriging
Sampling< Risk Avian Influenza $
• Spearman’s coefficient
• Grubb’s test, P<0.01

28. CONCLUSIONS
Spatial Analysis is an essential tool for Animal Health
Veterinary Authorities and
Organisations
Help to take decisions for TARGET SURVEILLANCE (According to EC
recommendations)
Identify HOT SPOT of RISK Adequate control mesures
Increase INFORMATION about dynamic of diseases improve
PREVENTION & CONTROL PLANS Prevent or reduce consequences
EVALUATE control and prevention strategies
Reduce health costs and improve efficiency
of veterinary intervention

29. Financial support: CC08-020, FAU2008-00001-C02-01
Laguna de Pitillas (Navarra) http://www.navarra.es/home_es/Actualidad/Informes