New Initiatives in Environmental Health and Malaria in India

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1 New Initiatives in Environmental Health and Malaria in India RAMESH C DHIMAN Scientist F Environmental Epidemiology National Institute of Malaria Research (ICMR) NEW DELHI, India dhimanrc@icmr.org.in

Potential malaria prone areas in Karnataka (based on landscape features associated with high malaria endimicity in Tumkur District Tank based irrigation

3 Potential malaria prone areas in Karnataka (based on landscape features associated with high malaria endimicity in Tumkur District Tank based irrigation which is related with high malaria endemicity is confined to Tumkur, Chitradurga, Hassan and Chikmaglur districts of southern Karnataka which are marked in red

4 UKP area (Almatti dam) IRS image Almatti Dam Irrigation Channel Network Krishna River

5 Ecological risk factors of malaria in Upper Krishna Project Districts (Bijapur, Gulberga and Raichur) by remote sensing. 46 villages of Almatti and 24villages of Narayanpur AMU were classified

6 Characteristics of River banks in Almatti and Narayanpur Narayanpur Devargaddi Melinagaddi Rocky bed pool a. Almatti - River banks with vegetation are visible b. Narayanpur -River with rocky bed pools are visible

7 HS Krishna river Krishna river Black soil Krishna river Masuati Kanchaganur Chavo Kamaldinni Low risk malarious villages under Almatti (IRS P6 MX) Don river HS VG VG HS VG HS IC Madlingnal Yarakinala Kurikanal High risk malarious villages under Almatti (IRS P6 MX Oct 2006) ( HS -Human settlement, VG -vegetation)

8 Classification of villages malaria risk in UKP Area AMU Villages low risk Moderate risk High Risk Almatti Narayan pur

Validation of relationship between Remote Sensing derived landscape features and malaria endemicity in Tumkur and Chitradurga districts of Southern Karnataka.

9 Validation of relationship between Remote Sensing derived landscape features and malaria endemicity in Tumkur and Chitradurga districts of Southern Karnataka. Presence of irrigation tanks(>5), vegetation cover ( >20 %), low barren area (< 10%) were associated with high malaria endemicity. Ground truth validation in unknown areas confirmed the earlier findings. High malarious villages Low malarious villages Satellite image (IRS P6 MX) showing high and low malarious villages in Kallembella (Sira Taluka, Tumkur)

10 IRS P6 Satellite Images of village of Kallembella PHC (Tumkur) (4 May 2007) Kogelinganahalli High malarious villages Kataviranahalli Toriyappanahalli Low malarious villages Uddayyanopalya

11 Categorization of villages into low/high malarious areas, southern Karnataka (based on Satellite data) District Taluka PHC Village low risk Moderate risk Tumkur Sira Kallembela Chitradu ga Tavrekere Tarur Hiriyur Ranganathpura Yelladakere Total High Risk

Ecological risk of malaria deducedfrom satellite data Ranganathpura PHC,Hiriyur Taluka, (Chitradurga ) 17 villages Yelladakere PHC, Hiriyur Taluka,

12 Ecological risk of malaria deducedfrom satellite data Ranganathpura PHC,Hiriyur Taluka, (Chitradurga ) 17 villages Yelladakere PHC, Hiriyur Taluka, (Chitradurga) 29 villages Tarur PHC,Sira Taluka, (Tumkur) 57 villages Tavarekere PHC, Sira Taluka (Tumkur) 22 villages Kallembela PHC,Sira Taluka (Tumkur) 28 villages

13 Prediction for the Epidemics of malaria in Kutch( India) Accumulated rainfall from May to Aug. (blue dots) could predict malaria cases in Sept. to December ( green dots) using VSEIRS model. (Laneri et al PLoS Com. Biol. 2010)

14 Impact of climate Change on Malaria in India

15 a T Ws of Malaria based on PRECIS Model b Uttarakhand Assam Mizoram TWs increased up to two months in a span of 30 years

16 Transmission Window ( TW) of malaria based on Temp. a Baseline A1B scenario ( ) and b. by the year 2030 Category Remarks Scenario (0) II (1-3) III (4-6) IV (7-9) V (10-12) ( NA) Baseline Projection (by 2030)

17 Transmission Windows of Dengue based on T and RH (A1 B Scenario) Baseline b. Projected ( 2030) Class Remarks I (0) ( PRECIS Scenario data not II (1-3) III (4-6) IV (7-9) V (10-12) available) Baseline Projection (by 2030)

18 Generic protocols for assessment of impact of climate change on VBDs and diarrhea by SEARO WHO

19 Future proposal Assessment of ecological and climatic risk of vector borne diseases

20 MARA MAPS Source: MARA

Duration of malaria transmission In the Months of Risk model, malaria transmission is strongly seasonal to epidemic (yellow = 1-3 months), seasonal and endemic (light green = 4-6 months) or perennial

21 Duration of malaria transmission In the Months of Risk model, malaria transmission is strongly seasonal to epidemic (yellow = 1-3 months), seasonal and endemic (light green = 4-6 months) or perennial and endemic (dark green = 7-12 months). Some areas shown as "No transmission" (white) may actually have endemic malaria because of the presence of surface water in an area where there is little or no rain. Source: MARA

22 Thanks

Situation Analysis of Malaria Control in Five Selected Pilot Areas in the Country for the Implementation of Roll Back Malaria Initiative

Situation Analysis of Malaria Control in Five Selected Pilot Areas in the Country for the Implementation of Roll Back Malaria Initiative Roll Back Malaria (RBM) is a new global initiative against malaria.