Presented by M. Gilbert (Université Libre de Bruxelles) at the Livestock Systems and Environment (LSE) Seminar, ILRI, Nairobi, 23 January 2014

1. M. Gilbert
Université Libre de Bruxelles
Livestock Systems and Environment (LSE) Seminar
ILRI, Nairobi, 23 January 2014
Spatial epidemiology of avian influenza in Asia and intensifying poultry production systems

2. Spatial epidemiology of avian influenza in Asia and intensifying poultry production systems
M. Gilbert
Biological control and spatial ecology,
Université Libre de Bruxelles
http://lubies.ulb.ac.be/Spatepi.html

3. HPAI H5N1 (FAO Empres-I): 2004-2012

4. A moving target #1: distribution in Thailand
1 Jan 2004 – 1 Jul 2004
1 Jul 2004 – 1 Jul 2005
1 Jul 2005 – end 2008

5. A moving target #2: distribution in Indonesia
2004 - 2008
2009
2010
2011

6. 2006 A moving target #3: distribution in India & Bangladesh
2007-2011
2012

7. Outbreaks
A moving target #3: distribution in China
Human cases
Positive markets

8. How to deal with those different situations ?
Pattern of spread
•Absence can be suitable
Pattern of surveillance and control
•What is an absence ?
Analysis
•Break down by country / epidemic phase
Comparative analysis
•Gain a general understanding from multiple studies

9. Focus on a limited set of factors
•What animal is infected
•Pattern of excretion (quantity, duration)
•Contacts with other hosts
Hosts
•How host are moved;
•How fomites are moved;
•Surveillance, prevention, control
Anthropogenic
•How and where the virus persists outside the host
•How and where poultry are raised
Environment

10. Time line
0
200
400
600
800
1000
1200
1400
2004
2005
2006
2007
2008
2009
2010
2011
2012
EMPRES-I HPAI H5N1 records (Asia)
THA
IDN
CHN
IND
BGD
VNM

11. 2004 First steps: firefighting in Thailand

12. HPAI H5N1 & ducks in Thailand
Farm chicken
Native chicken
HPAI H5N1 Gilbert et al. (2006) EID 12(2):227-234

13. HPAI H5N1 & ducks in Thailand
Farm ducks
Free grazing ducks
HPAI H5N1 Gilbert et al. (2006) EID 12(2):227-234

14. Free-grazing ducks can be mapped using
remotely sensed indicators
Gilbert et al. (2007) Ag., Eco. Env. 119:409-415

15. Thailand and Vietnam model

16. • Cropping intensity, domestick duck density, human population
density, chicken density (VNM) as main risk factors
• In Thailand: Paul et al. (2010); Tiensin et al. (2009)
• In Vietnam: Pfeiffer et al. (2007)
Spatial model: building and validation 0.0 0.2 0.4 0.6 0.8 1.0
0.0 1 - Specificity
0.0 0.2 0.4 0.6 0.8 1.0
0.0 1 - Specificity
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.4 0.8
1 - Specificity
Sensitivity
AUC = 0.66 +/- 0.0081
Vietnam: Wave I
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.4 0.8
1 - Specificity
Sensitivity
AUC = 0.742 +/- 0.0142
Vietnam: Wave II
0.8
0.8
1.0
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0
1 - Specificity
Sensitivity
Vietnam
Wave I
Wave II
Wave III
Gilbert et al. (2008) PNAS 105: 4769-4774

17. Spatial model: predictions
Gilbert et al. (2008) PNAS 105: 4769-4774

18. Predictions in Indonesia
Loth et al. (2011) Prev. Vet. Medecine. Doi:10.1016/j.prevetmed.2011.06.006

19. Predictions in South Asia Gilbert et al. (2010) Ecohealth 7(4):448-58

20. Outbreak density profile in Thailand
Thailand
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0.000 0.004 0.008 0.012
Gilbert et al. (2010) Ecohealth 7(4):448-58

21. Outbreak density profile in Thailand vs.
Vietnam
Thailand
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0.000 0.004 0.008 0.012
THA
Vietnam
0.004 0.008
VNM

22. Outbreak density profiles
Thailand
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0.000 0.004 0.008 0.012
Vietnam
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0.000 0.004 0.008
India
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0e+00 4e-04
Bangladesh
Outbreak Density
0.0 - 0.2
0.2 - 0.5
0.5 - 0.8
0.8 - 1.0
1.0 - 1.2
1.2 - 1.5
1.5 - 1.8
1.8 - 2.0
2.0 - 2.2
2.2 - 2.5
2.5 - 2.8
2.8 - 3.0
3.0 - 3.2
3.2 - 3.5
3.5 - 3.8
3.8 - 4.0
0.000 0.002 0.004
Gilbert et al. (2010) Ecohealth 7(4):448-58

23. Production structure in Thailand Van Boeckel et al. (2012) Ag., Eco. Env. 10.1016/j.agee.2011.12.019

24. Disagregating poultry data Van Boeckel et al. (2012) Ag., Eco. Env. 10.1016/j.agee.2011.12.019

25. BRT model in Thailand Van Boeckel et al. PLOS ONE 7(11): e49528. doi:10.1371/journal.pone.0049528

26. Different duck systems
Delineate areas where HPAI can persist
Free-grazing, local movements e.g. Bangladesh, India, Indonesia, Nigeria
Free-grazing intensive movements e.g. Central plain of Thailand, Vietnam deltas
Farmed e.g. North- eastern Thailand

27. Review paper on HPAI H5N1 risk factors

28. Review paper on HPAI H5N1 risk factors
•Factors have been studied at various scale: farm to country level;
•Factors were very different from one study to another: real difficulty in comparing studies outcomes;
•Overall, some factors showed consistent association with the risk of HPAI H5N1 presence across countries and scales:
•Domestick duck density;
•Anthropogenic (Human pop. density, distance to roads, markets)
•Indicators of water presence
•The effect of chicken density is variable, most likely due to differences in production systems

29. Review of HPAI H5N1 risk factors
•Factors have been overlooked:
•Socio-economic;
•Trade and market networks;
•Wild bird distribution and movement;

30. Duck distribution

31. Intensification of duck production in China
First report of H5N1

32. China: 75% of ducks
•Outbreaks (mainly in chicken farms)
•H5N1 positives from markets Martin et al. (2011) Plos Pathogens 7(3): e1001308

33. BRT model
•Outbreaks
•Chicken and human pop. density;
•More emphasis on the intensive productions areas
•Market surveillance
•Hpop, duck density, and % water.
•Duck/rice ecosystem in the south Martin et al. (2011) Plos Pathogens 7(3): e1001308

34. •Poyang lake: main lake for migratory watefowls

38. •Poyang lake: wild geese farms

39. •Poyang lake: main lake for migratory watefowls
Poyang lake populations
0.5 million wild birds (75 species);
3 millions « farmed » wild birds;
Surrounded by 10 counties with
26 million ducks and geese in farms;
21 million domestic chicken in farms;
6 million people;

40. Temporal patterns in Poyang lake Cappelle et al. (in revision)

41. Spatial patterns in Poyang lake Cappelle et al. (in revision)

42. Live-bird market networks Martin et al. (2011)

43. Intensified poultry production rapidly, duck population that outweights all other coutries
In regions with extensive interface with the wild avifauna
Connectivity between regions is facilitated by long-distance trade between live-bird markets
Relevance to H7N9 ?
China

44. A quick virtual tour in Huzhou
Detailed investigation for all 12 confirmed H7N9 cases in Huzhou, Zhejiang province (http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=20481). Linked to markets with: Chickens infection rate of samples = 36 / 129 = 27% Pigeon infection rate of samples = 2 / 6 = 33%

45. A quick virtual tour in Huzhou

46. A quick virtual tour in Huzhou

47. A quick virtual tour in Huzhou

48. A quick virtual tour in Huzhou

49. H7N9 in China: geographic space

50. H7N9 in China: var space
•Human population
•Duck population
•Chicken population
•% of land occupied by water
•% of land occupied by rice paddy fields
•Accessibilit y(travel time to major cities)
•Live-bird market density

51. BRT profiles

52. H7N9 risk maps

53. Combined risk

54. Live bird markets
•Important and widespread in China, Vietnam, Bangladesh, Indonesia, Cambodia
•Can allow disease spread and persistence through the meta-population of live-bird markets
•Social Network Analysis combined with mathematical modelling shows potential for targetting markets where intervention would be most beneficial (Fournie et al. 2012, 2013)
•The current missing elements to understand AI (H5N1/H7N9) persistence and spread ?

55. Intensification of duck production in China
First report of H5N1

56. Global trends
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57. Where are we going ?
•On-going intensification in China, extensive wild bird interface, high LBM density
•India / Bangladesh: intensification, duck population, extensive interface with wild birds, live bird markets
•Is large-scale farming with high biosafety the only way to intensify production safely ?
•Can subsistance and commercial poultry farming co- exist ?

58. Back to Thailand
One of the highest density of domestick ducks;
Extensive irrigated land;
Large commercial sector;
Smallholders & native chickens;
High human population density;
Few or no live-bird markets

59. Conclusion
•Key role of ducks => differ according to production systems
•Intensification of duck production in contact with WB genetic pool of viruses
•Spread to other poultry and human exposure facilitated by LBM networks
•Try not having both

60. Thank you
Acknowledgments: J. Cappelle, L. Hogerwerf, L. Loth, V. Martin, S. Newman, M. Paul, D. Pfeiffer, D. Prosser, T. Robinson, J. Slingenbergh, K. Stevens, W. Thapongtharm, T. Boeckel, R. Wallace, W. Wint, X. Xiao ,