For a territorial diagnosis of a health risk on a fine scale An attempt to model environmental variables of MALARIA South Benin Charlotte Pierrat Université Paris 1 – Panthéon Sorbonne IRD UMR 216 Paris Descartes « Santé de la mère et de l’enfant en milieu tropical » 2010 ENRGHI DATA – METHODS – PRELIMINARY RESULTS

INTRODUCTION Environment and malaria : an old and complex relationship Natural background Society Environment Risk = encounter on a territory of a vector hazard and a population vulnerability Malaria A vectorConditions in favour of transmission to human Socio-economic factors of vulnerability Anopheles (Gambiae)

1 to 3 millions death / year Parasitosis / vector borne disease Strikes most children under 5 (85% oh death) and Sub-Saharan Africa Epidemiological situation of malaria Insatisfying access to treatments / Difficulty of diagnosis High mortality and morbidity due to : Drug resistance Misuse of means of prevention (bed nets…) Re-emergence and urban malaria High necessity to understand the environmental determinants of transmission

Research Questions Which conditions on the natural background are in favour of the existence of anopheles ? Which socio-economic conditions create a higher vulnerability of individuals ? On which variables can we act to reduce the burden of malaria ? -> Prevention PLAN 1. Measure of the risk : Micro-scale essential 4. Limits of climatic models 3. Methodology and data 5. Preliminary results 2. The determinants of malaria IS THERE A TARRITORIALITY OF THE RISK ? AT WHICH SCALE ? Characterization of the pathogenic system for this territory

Study Area

Malaria transmission and Infection - Measure of the risk :Density of mosquitoes / Number of human infections (Human component) - Link between Mosquitoes and Malaria infections : well known on large scale On a fine scale : much less clear !!! Difficulty of measures For Geographers : risk = ill people 1. Measure of the risk - micro-scale approach needed Question of the scale of observation = When there are Anopheles, what makes the disease ? At stake : if vector control impossible, can we act on other factors ?

Area of presence of Anopheles Gambiae (Carte V. Robert) OMS, 2008 Malaria endemicity 1. Measure of the risk - micro-scale approach needed

On a micro-scale : Exemple of Tori Bossito, Southern Benin Need to analyse the caracteristics of each house and their inhabitants Malaria casesNumber of Anopheles Micro-scale Mirco-scale approach essential

2. The determinants of malaria risk VECTOR POPULATION VULNERABILITY Climate Soil occupation Anti-vectorial fight Habits of prevention Houses caracteristics Education Economic situation Representations Multi-scales variables Acessibility to health services Which of these variables are relevant on a fine scale ? Individual / Collective factors How do they express in space ? What kind of territoriality do they determine ?

Methodology 1. Choice a priori of environmental variables 2. Elaboration of the Conceptual Data Model (MCD) 3. Fieldwork 4. Remote sensing -> creation of data 5. Elaboration of the GIS 6. Interrogation of the GIS 3. Methodology and data

DATA : new born cohort[ IRD program in Benin (ANR funding) ] Variables chosen : 2 scales : Village (n= 9)House (n = 600) Rainfall Temperature Humidity Habitat caracteristics Social caracteristics NDVI Fragmentation Index BIOLOGICAL DATA Number and date of TDR + Number of Anopheles Gambiae On 41 houses Fieldwork Routine collection Remote sensing Captures missions

Tropical climate Malaria endemicity 4. Preliminary results (1) Malaria endemicity and climate : limits of models Link Climate / Malaria well known on large scale ARMA Climate model of malaria - OMS

However : on a fine scale : -Same convective clouds systems - Difficulty of fine measures BUT : great variability of anopheles Gambiae density Climate doesn’t explain the variability of transmission on a village-scale Total number of An. Gambiae captured from august 2008 to july 2009 CLIMATE = Necessary condition but not sufficient 4. Preliminary results (1) OVER – ESTIMATION of the role of CLIMATE

High landscape fragmentation 4. Preliminary results (2) High An. Gambiae variability High transmission variability 8 classes SPOT 5 – 10mC Isoclust (234) ! # scales of measures

4. PRELIMINARY RESULTS (3) Soil occupation - Fragmentation Index Indicator of human presence in landscape

4. PRELIMINARY RESULTS (3) Soil occupation - NDVI Linked with the ecological caracteristics of niches - Further analysis in process to assess link with anopheles density - Variability of these variables between houses = on fine scale

4. PRELIMINARY RESULTS (4) Social determinants - 2 hot spots : Gbetaga and Zoungoudo ? - Particular cases = houses with no transmission very close to : - High number of anopheles - houses with high transmission How to explain : How works territoriality of transmission ? Role of ethnic groups economic situation For definition of territories ?

4. PRELIMINARY RESULTS (4) Social determinants : first observations Ethnic groups in Tori Bossito Tori ethnic group dominant Few Fon ethnic group in the southern villages BUT : No real village specificity Gbetaga & Zoungoudo : 3 ethnic groups Need to assess if the cases occur in specific ethnic groups = Back to the house-scale for the analysis 95 % use bed net HABITS ! Bias in data ETHNIC GROUPS

4. PRELIMINARY RESULTS (5) House characteristics A priori not relevant in transmission Roof / walls / soil Further analysis in process : caracteristics of close surroundings of houses (Presence of watershed, constructions areas…) Idem other variables : good repartition on territory Link with socio-economic situation of inhabitants Habitat = indicator of poverty / factor of vulnerability BUT : can be indirect indicators of other causes of vulnerability !

Perspectives from these preliminary results Habits of population : role of Vaudou rituals / ethnic groups Further analysis needed through interrogation of the GIS : - At the house scale : surroundings… - Social variables : Complex question of the role of population density Link between all the social variables to assess a SOCIAL CONTEXT in favour of transmission Malaria representations To understand the link between presence of An. Gambiae and level of transmission Question of the scale : CENTRAL To understand malaria dynamics, it’s necessary to make zoom in (indentification of factors) AND THEN out (generalization possible ???) What are the stakes of prevention ? vector control ? Health communication/ education ? What is the relevant scale for prevention ? Health policies ?

THANK YOU ! Charlotte Pierrat Université Paris 1 – Panthéon Sorbonne IRD UMR 216 Paris Descartes « Santé de la mère et de l’enfant en milieu tropical » 2010 ENRGHI