Dengue in Delhi : a dialogue between Research and Public Health?

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1 COLLOQUE INTERNATIONAL «Dynamiques urbaines et enjeux sanitaires» Nanterre 2013 Dengue in Delhi : a dialogue between Research and Public Health? Telle O. 1*, Vaguet A. 2, Daudé E. 2*, R. Paul 1 1 Institut Pasteur Paris (GFMI) 2 UMR IDEES, Université de Rouen * Human Sciences Research Center, Delhi, India

2 2 200 millions individuals infected each year (Hay et al, 2013). Vector Borne disease (Aedes Aegypti et Aedes Albopictus). Unkown factor of risks in cities Aedes albopictus.

3 Geography of dengue in Delhi First aim was to observe diffusion model of dengue in a urban setting Second aim was to understand relation between dengue cases - vectors and urban fragmentation in a hyper-endemic city as Delhi.

4 7000 6000 5000 4000 3000 2000 1000 0 6259 3340 2882 606 900

5 Analyses of local and meso diffusion of Dengue Virus

6 Score K-Ripley 6 Cluster detection: Kernel analysis (Arcgis 10.1) Clusterseer Observed 2008 Expected Observed Distance en mètre

7 0 10 20 30 40 50 0 10 20 30 40 50 60 70 80 90 100 7/6 10/6 13/6 16/6 19/6 22/6 25/6 28/6 1/7 4/7 7/7 10/7 13/7 16/7 19/7 22/7 25/7 28/7 31/7 3/8 6/8 9/8 12/8 15/8 18/8 21/8 24/8 27/8 30/8 2/9 5/9

7 /6 10/6 13/6 16/6 19/6 22/6 25/6 28/6 1/7 4/7 7/7 10/7 13/7 16/7 19/7 22/7 25/7 28/7 31/7 3/8 6/8 9/8 12/8 15/8 18/8 21/8 24/8 27/8 30/8 2/9 5/9 8/9 11/9 14/9 17/9 20/9 23/9 26/9 29/9 2/10 5/10 8/10 11/10 14/10 17/10 20/10 23/10 26/10 29/10 1/11 4/11 7/11 10/11 13/11 16/11 19/11 22/11 25/11 28/11 1/12 4/12 7/12 10/12 13/12 16/12 19/12 22/12 25/12 28/12 Nb of cases PP and C 2008 Number of cases PP C

PP and C Nb of cases 100 80 Number of cases PP C 2009 50 40 8 60 30 40 20 20 10 0 28/12 25/12 22/12 19/12 16/12 13/12 10/12 7/12 4/12 1/12 28/11 25/11 22/11 19/11 16/11 13/11 10/11 7/11 4/11 1/11

8 PP and C Nb of cases Number of cases PP C /12 25/12 22/12 19/12 16/12 13/12 10/12 7/12 4/12 1/12 28/11 25/11 22/11 19/11 16/11 13/11 10/11 7/11 4/11 1/11 29/10 26/10 23/10 20/10 17/10 14/10 11/10 8/10 5/10 2/10 29/9 26/9 23/9 20/9 17/9 14/9 11/9 8/9 5/9 2/9 30/8 27/8 24/8 21/8 18/8 15/8 12/8 9/8 6/8 3/8 31/7 28/7 25/7 22/7 19/7 16/7 13/7 10/7 7/7 4/7 1/7 28/6 25/6 22/6 19/6 16/6 13/6 10/6 7/6 0

9 9 Kernel analyses of Dengue cases registered in Delhi

10 10

11 11

12 12

13 13 Nb of Cases per clusters Nb of cluster In 2008 Total Nb of cases % of cases in this type of cluster Nb of cluster In 2009 Nb of cases % of cases in this type of cluster Isolated % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % Total % %

14 14 Nb of cases per cluster * IC = 50 first cases Mean Day of IC* Mean nb of Index Cases within 300 meters Durat ion Nb of cases per cluster Mean Day of IC Nb of Index Cases within 300 meters Durat ion isolated Isolated Total Total

16 How to observe the socio-spatial fragmentation of Delhi? Methodology Geography of a disease is correlated with local environment. In Delhi, few data are avalaible at small scale while fragmentation occurs at this scale in Delhi (Dupont, 2001). We convey Property Tax and a GIS to reveals socio-spatial fragmentation Several informations are used : Property tax (gathering 10 informations) Build up density Typology of area (commercial, industrial, build up)

17 NDMC 22,5 3,2 0,0 - NDMC 0,1% Grand Total 39,2 3,3 0,9 39,4 100,0% Characterize urban fragmentation of Delhi : Method Details for each colony is avalaible Typology of space Property tax level Building density Row Labels % Residential % Commercial % Indus Property tax Typology % 1 31,5 2,8 0,5 29,9 Deprived area 13,3% 2 18,5 0,6 0,1 75,5 Rich 2 4,3% 3 33,0 2,1 0,5 51,4 Newly planned 11,5% 4 61,8 2,4 0,1 29,8 Deprived 2 12,7% 5 58,0 2,9 0,1 51,2 Planned 28,4% 6 7,6 2,1 16,7 46,8 Industrial 7,0% 7 40,6 31,3 0,0 43,9 Old commerci al area 3,3% 8 52,7 0,8 0,0 75,2 Rich 1 3,3% 9 11,3 1,2 0,3 28,3 Spontaneo us Habtita 16,0%

18 18 Spontaneous

19 19

20 Relation between Vectorial Data and Environment 175 Colonies are sampled by 2500 municipal employees between July and October 2009 (230 colonies in total from March to December) Data of 2009 are analysed in the thesis (HI, CI, BI) and reveal strong link between environment and abundance of aedes larvae (HI = House Index, CI= Container Index) Sampled colonies Min of HI Max of HI Mean HI stdev Min CI Max CI Mean CI stdev Industrial areas ,8 4 2,86 1,54 Old planified 29 2,6 8,89 3,88 2,07 1,3 9,09 3,23 2,01 Deprived area (1+2) 33 2,5 14,81 5,12 3,44 1,6 8,4 4,23 2,00 Spontaneous 44 2,1 15,63 5,04 3,23 2,3 5,4 4,00 3,89 Historical Center 6 1,9 8,89 4,03 3,18 1,8 9,5 3,11 2,99 Planified recent 19 1,6 8,04 3,65 1,80 1,2 8,52 3,36 1,81 Rich 9 0,9 4,44 2,71 1,33 1,5 3,57 2,54 0,64 NDMC 1 2,90 3,14 Grand Total 175 0,90 15,6 4,21 3,73 1,30 9% 3,65 2,57

21 Relation environment and dengue incidence Despite a strong relation with larvae index, geopgraphy of dengue case is not depend of environment of population. Case per KM² (of build up) are in 2008 located in Poor areas, while in 2009, cases are much more located in NDMC and rich areas of MCD. 18,000 16,000 14,000 Nb NB de of cases/ / km² build bâti up 2008 area Nb NB de of cases/ / km² build bâti up 2009 area (km²)2008 (km²) ,000 10,000 8,000 6,000 4,000 2,000 0,000 Industrial Industriel Peri Periurban ous 2 urbain Spontané Spontane Deprived Pauvre Deprived Pauvre 2 Historical Centre areas Historique Center Planifié Old ancien planned planifié Newly planned recent Riches NDMC Moyenne Mean (residential) Delhi Delhi

22 22 Aedes Index in different type of spaces: Hopitals CI Train station CI JJ Cluster HI Public building CI Urbain Village CI Residential CI Public work Education CI 28/06-01/08 02/09-29/09 30/09-03/10 04/10-01/11 3 1,6 2,4 5 3,7 3,9 5 6,32 8,5 9,78 8, ,2 4,2 6,53 12,4 10, ,65 4 6,5 17,6 5,6 7, ,9 3,1 4,2 2,22 Moyenne 8,8 6, ,25 4,6 3,8 5,5 11,77 Aedes Index and dengue cases evolution: Year House Index 12,1 8,52 7,68 4,8 4,2 Container Index 10 6,3 5,8 3,1 3,62 Dengue cases

Conclusion: Geography of dengue is complex, depending of environment, vector behaviour, virus (ie. asymptomatic cases) as well as individuals behaviour.

23 Conclusion: Geography of dengue is complex, depending of environment, vector behaviour, virus (ie. asymptomatic cases) as well as individuals behaviour. Intra-urban mobilities as well as the role of public spaces need to be understood in the diffusion of dengue Virus. Vectorial Data shows that index are higher in public spaces such as hospitals, train station, ect. This suggest that contamination could occurs in those space rather than in domestic area. However, in the absence of effective vaccine, environmental factors of risk (socio-economical and governance included) need to be understood since environment is the only determinant on which we can act to prevent population from dengue. Some research are currently in progress in Delhi and Bangkok.

THANK YOU! Contact: Telle.olivier@gmail.

24 THANK YOU! Contact: Partners: Daudé Éric Vaguet Alain Telle Olivier Lefebvre Bertrand Cebeillac Alexandre Maneerat Somsakun Misslin Renaud Taillandier Patrick Vaguet Yvette This research was founded by the EU project DENFREE: Dengue Research Framework for Resisting Epidemics in Europe (grant agreement: ), funded by the European Commission s Seventh Framework Research Programme and by the French project AEDESS: Analyse de l Emergence de la Dengue Et Simulation Spatiale, funded by the Agence Nationale de la Recherche, ANR 10 CEPL

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FROM OBSERVATION TO SIMULATION, AND RETURN PERSPECTIVES FOR DENGUE RESEARCHES

European Colloquium in Theoretical and Quantitative Geography (ECTQG 13), Dourdan, France, 5 th -9 th sept. 2013 FROM OBSERVATION TO SIMULATION, AND RETURN PERSPECTIVES FOR DENGUE RESEARCHES Daudé É. 1,