| RESEARCH ARTICLE |
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| Year : 2014 | Volume
: 51
| Issue : 4 | Page : 276-281 |
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Identification of risk factors for malaria control by focused interventions in Ranchi district, Jharkhand, India
Rekha Saxena1, MK Das2, BN Nagpal1, Aruna Srivastava1, Sanjeev Kumar Gupta1, Anil Kumar1, Arvind Singh Tomar1, A.T.S. Sinha3, Rajkumari Vidyotma3, AT Jeyaseelan4, Vijay Kumar Baraik5, VP Singh1
1 National Institute of Malaria Research (ICMR), New Delhi, India
2 IDVC Project Field Unit, Itki, Ranchi, India
3 State Health Department, Ranchi, India
4 Jharkhand Space Application Centre, Dhurwa, Ranchi, India
5 School of Sciences (SoS), Indira Gandhi National Open University, New Delhi, India
Correspondence Address:
B N Nagpal
Scientist 'F', National Institute of Malaria Research, Sector 8, Dwarka, New Delhi-110 077
India
 Source of Support: None, Conflict of Interest: None  | Check |
PMID: 25540958 
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Background & objectives: Ranchi, the capital of Jharkhand state is endemic for malaria, particularly the Bundu Primary Health Centre (PHC) is the worst affected. Therefore, a study was initiated during 2009 using remote sensing (RS) and geographical information system (GIS) to identify risk factors responsible for high endemicity in this PHC.
Methods: Bundu and Angara in Ranchi district were identified as high and low malaria endemic PHCs based on epidemiological data of three years (2007-09). The habitation, streams, other water body, landform, PHC and village boundary thematic maps were prepared using IRS-P6/LISS III-IV imageries and macro level breeding sites were identified. Digital elevation model (DEM) of the PHCs was generated using Cartosat Stereo Pair images and from DEM, slope map was derived to calculate flat area. From slope, aspect map was derived to indicate direction of water flow. Length of perennial streams, area under rocky terrain and buffer zones of 250, 500 and 750 m were constructed around streams. High resolution remote sensing imageries were used to identify micro level breeding sites. Based on macro-micro breeding sites, six villages from each PHC were selected randomly having combination of different parameters representing all ecotypes. Entomological data were collected during 2010-11 in pre- and post-monsoon seasons following standard techniques and analyzed statistically. Differential analysis was attempted to comprehend socioeconomic and other determinants associated with malaria transmission.
Results: The study identified eight risk factors responsible for higher malaria endemicity in Bundu in comparison to Angara PHC based on ecological, entomological, socioeconomic and other local parameters.
Conclusion: Focused interventions in integrated vector management (IVM) mode are required to be carried out in the district for better management and control of disease. |
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