FROM OBSERVATION TO SIMULATION, AND RETURN PERSPECTIVES FOR DENGUE RESEARCHES

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1 European Colloquium in Theoretical and Quantitative Geography (ECTQG 13), Dourdan, France, 5 th -9 th sept FROM OBSERVATION TO SIMULATION, AND RETURN PERSPECTIVES FOR DENGUE RESEARCHES Daudé É. 1, Lefebvre B. 2, Telle O. 3, Maneerat S. 1, Vaguet A. 2, Vaguet Y. 2, Cebeillac A. 1, Misslin R. 1 1 UMIFRE CNRS-MAE, CSH, New Delhi, Inde 2 UMR IDEES, Rouen, France 2 Institut Pasteur Paris, France / CSH, New Delhi, Inde

2 2 200 millions individuals infected each year (Hay et al, 2013). Vector Borne disease (Aedes Aegypti et Aedes Albopictus). Unkown interaction of risk factors in cities (unlike rural areas) Aedes albopictus ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R..

3 ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R. 3

4 4 Micro Scale Meso Macro scale - Genetic - Antibodies (Herd immunity) - Population density - Immunity - Asymptomatic - Mobility -Age - Dengue Risk KAP (kowledge) - Socio-economical Micro - Virulence Meso - Serotype Macro - Strain Mutation 7 8 Virus 11 6 Host Aedes 2 1 Micro - Gravid - Age - Predation behavior Meso - Biting rate - Survival rate - Mobility behavior Macro - Aedes density - Contamination rate - Population age Environment Micro Meso Macro Container - Water storage - Temperature House condition - Landuse - Precipitation Humidity - Vectorial managment - Urban planning Figure 1: Dengue system and its main components ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

5 5 Micro Scale Meso Macro scale - Genetic - Antibodies (Herd immunity) - Population density - Immunity - Asymptomatic - Mobility - Dengue Risk KAP (kowledge) - Socio- -Age economical Micro - Virulence Meso - Serotype Macro - Strain Mutation 7 Virus Host Environment 2 3 Aedes 1 4 Micro - Gravid - Age - Predation behavior Meso - Biting rate - Survival rate - Mobility behavior Macro - Aedes density - Contamination rate - Population age Micro Meso Macro Container - Water storage - Temperature House condition - Landuse - Precipitation Humidity - Vectorial managment - Urban planning Relation De type Porte sur Surveillance Contrôle R1 E Ve R3 H Ve R4 Ve H R5 H E R6 E H R7 Vi H R8 H Vi R9 Vi Ve R10 Ve Vi R11 E Vi Influence Breeding site Breeding site checking Control of breeding site Constrain Low temperature (< 20 ) Meteorological survey - Transmission Virus Dengue surveillance system Transmission Virus Contaminated bitting rate Urban Planning (or not) Landuse, environment fragmentation GIS system Constrain Diffusion system Population mobility Fumigation of house being of infected individuals Individual prophilaxy to avoid Mosquito bitting Environment control Prevent dengue to reach nodes of the system Infect Cells NS1 virus isolation Fever, platelet surveillance Replication Antibodies Seroprevalence Vaccin Infect Cells % of infected mosquitoes Genetic modification of mosquito Replication virus Influence Température Virus virulence Temperature control ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

6 6 1 Relations between dengue cases and Socio-Environmental factors: Aedes aegypti - socio-economical contexts: wealth, employment, prevention -physico-environmental contexts: local temperatures, building density, land use - human mobilities : perimeter, frequency, places 2 Produce a dynamic model, spatially explicit, of Vector / Host Behaviours (Individual-based model): Aedes albopictus - To test hypothesis on Aedes aegypti population dynamic and on human mobilities - To explore scenarii (on environment / mosquito) for dengue control ECTQG 13 - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin A.

7 Spatial Integration (GIS) 7 DATA COLLECTION SPATIAL ANALYSIS SIMULATION Parameters / Input Data Agent-Based Models Epidemiological Data vector host Entomological Data Territorial Diagnosis environment virus Aedes aegypti Survey, Census, Retrospective Data, Satellite images Aedes albopictus Environmental Data Social Data Remote sensing Spatial analysis Monitoring System Calibration / validation Integration Simulation Decision Support Tool ECTQG 13 - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin A.

8 8 Retrospective study in Bangkok and Delhi ECTQG 13 - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin A.

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10 /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 2009 Number of cases PP C

11 /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

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13 Relation between Vectorial Data and Environment 175 Colonies are sampled by 2500 municipal employees between July and October Data of 2009 are analysed in the thesis (HI, CI, BI) and reveal strong relation between environment and abundance of aedes larvae (HI = House Index, CI= Container Index) Sampled colonies Min of HI Max of HI HI moyen stdev Min CI Max CI CI mean 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 Poor 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 ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

14 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. Dengue Cases Density ( ) 5,00 4,50 4,00 3,50 3,00 2,50 2,00 1,50 1,00 0,50 0, ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

15 Vectorial Index in different places of Delhi Semaine 28/06/ /08/ /09/ /09/ /09/ /10/ /10/ /11/2009 Hospital CI Train station CI JJ cluster HI Institution CI CPWD CI education CI House Index 3 1,6 2, ,32 3,4 8,5 9,78 8, ,53 12,4 6,7 10, ,5 17,6 7,2 5,6 7, ,2 2,22 4 8,8 6, ,25 5,5 11,77 5,125 ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

16 Conclusion: Geography of dengue is complex, depending of environment, vector behavior, virus (ie. asymptomatic cases) as well as individuals behavior. 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, role of environment and gouvernance need to be understand, since environement is the only determinant on which we can act to prevent population from dengue. Some research are currently in progress in Delhi and Bangkok. ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

17 17 ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

18 18 Each Individual-mosquito is a computer model of Aedes aegypti: - defined by stage and transitions (egg, larva, pupae, adult, virgin female, non-ovipositing, first gonotrophic, ovipositing, normal gonotrophic, dead), by behaviours related to stage (mating, feeding, ovipositing, hatching, biting, flying) and parameters - A population is a set of Individuals with the same behaviours (competences), differentiated according to their life stage and according to specific parameters category sub-category parameters values unity mating MATING_PROB 0,95 mating probabilities for a new emergent female MAX_ENERGY BLOOD_DETECT_DIST 4320minutes 3meters the value is based on the number of days that a mosquito can survive without feeding. It's 3 days AEDES'S ACTIVITIES BLOOD_GAIN_ENERGY_UL 1080minutes 1080 mn gain per 1 ul blood feeding. This value is based on the fact that Aedes take minimum 3 days from the last blood meal (4 ul max/meal) to finish gonotrophic cycle, so 1 ul blood is approximately equivalent to 1080 mn gain (4320mn/4ul). To confirm!!! In average, Aedes takes about 1mn for nectar feeding. If it can take blood meal for one minutes, it can earn 1080mn (1 ul), this value can also feeding NECTAR_GAIN_ENERGY 1080? minutes apply to nectar feeding? oviposition MIN_TEMP_FOR_OVIPOSITION 18 C MAX_STCKEGGS 120eggs 120 = max nb of eggs to lay per a gonotrophic cycle MIN_STCKEGGS 100eggs 100 = min nb of eggs to lay per a gonotrophic cycle MAX_SPEED_LAYEGG 0,05eggs 0.05 eggs/s = 3eggs/mn (cf: enquête auprès des entomologues) MIN_SPEED_LAYEGG 0,016eggs eggs/s = 1egg/mn egg hatching EGGS_HATCH_NO_FLOODING_PROB 0,197 EMBRYONATED_EGG_HATCH_PROB 0,596 MIN_TEMP_EGGHATCH 22 Biting MAX_QUANT_BLOOD 3mg MAX_TIME_BITING 15minutes a revérifier!!!! BITING_SUCC_RATE 0,8 including host defence rate flight TARGET_MAXDIST_TOLERENCE?? target reached tolerent distance PERCEPTION_TARGET_RADIUS 10meters the percepetion distance by Aedes is assumed here to 10 meters for all kind of targets MAX_SPEED 1meters/sec 1m/s MIN_SPEED 0,5meters/sec 0,53/s MAX_VERSPEED 0,8 MIN_VERSPEED 0,2 FLIGHT_ENERGY_LOST?? mn/s ECTQG 13 - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin A.

19 19 category data parameters values fheight {0,1,..,n} m fporosity [0,1] fbloodattractday [0,1] building fbloodattractnight [0,1] frestattractday [0,1] frestattractnight [0,1] fovipositattract [0,1] fnectarattract [0,1] fbloodattractday [0,1] fbloodattractnight [0,1] vegetation frestattractday [0,1] frestattractnight [0,1] fovipositattract [0,1] fsunexpo [0,1] fporosity [0,1] fbloodattractday [0,1] fbloodattractnight [0,1] thoroughfare frestattractday [0,1] LAND USE frestattractnight [0,1] fovipositattract [0,1] fsunexpo [0,1] fovipositattract [0,1] water surface fporosity [0,1] fporosity [0,1] fbloodattractday [0,1] empty space fbloodattractnight [0,1] frestattractday [0,1] frestattractnight [0,1] fovipositattract [0,1] fheight {0,1,..,n} fporosity [0,1] fbloodattractday [0,1] construction site fbloodattractnight [0,1] frestattractday [0,1] frestattractnight [0,1] fovipositattract [0,1] fsunexpo [0,1] DATE DD/MM/YYYY DAILY_MAX_TEMP x C DAILY_MIN_TEMP x C weather DAILY_MAX_WIND x km/h METEOROLOGY DAILY_TOT_RAIN_MM x mm fairsaturationdeficit (humidity) % fhourlytemp x C DATE DD/MM/YYYY sun SUNRISE H.MN SUNSET H.MN Female adult Aedes aegypti s activities decision diagram ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

20 20 Geosimulation of Dengue vector population dynamic Global monitoring Stages evolution Mosquitoe s Activities Spatial distribution ECTQG 13 - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin A.

21 21 Scenarii that can be tested : Spatial evolution of the disease according to localisation of first cases, temperature, rainfall and centrality of the area / mobilities of individuals. Local probability of dengue virus diffusion once a case is register Impact of fumigation during an epidemic Impact of environment management during inter-epidemic period (eradication of ecological niches for virus). Urban central nodes managment vs local managment of spaces Etc. ECTQG2013, - Daudé É., Lefebvre B., Telle O., Maneerat S., Vaguet A., Vaguet Y., Cebeillac A., Misslin R.

22 THANK YOU! Contact: Partners: Daudé Eric 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