Saxena Rekha, Das M K, Nagpal B N, Srivastava Aruna, Gupta Sanjeev Kumar, Kumar Anil, Tomar Arvind Singh, Sinha A T S, Vidyotma Rajkumari, Jeyaseelan A T, Baraik Vijay Kumar, Singh V P
National Institute of Malaria Research (ICMR), New Delhi, India.
J Vector Borne Dis. 2014 Dec;51(4):276-81.
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.
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.
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.
Focused interventions in integrated vector management (IVM) mode are required to be carried out in the district for better management and control of disease.
贾坎德邦首府兰契是疟疾的地方性流行区，尤其是邦杜初级卫生中心（PHC）受影响最为严重。因此，2009年启动了一项研究，利用遥感（RS）和地理信息系统（GIS）来确定该初级卫生中心高流行率的危险因素。
根据三年（2007 - 2009年）的流行病学数据，将兰契区的邦杜和安加拉分别确定为疟疾高流行和低流行的初级卫生中心。利用印度遥感卫星P6/LISS III - IV影像绘制了居住地、溪流、其他水体、地形、初级卫生中心和村庄边界专题地图，并确定了宏观层面的孳生地。利用Cartosat立体影像对生成了初级卫生中心的数字高程模型（DEM），并从DEM导出坡度图以计算平坦区域。从坡度导出坡向图以指示水流方向。测量了常年溪流的长度，计算了岩石地形面积以及溪流周围250米、500米和750米的缓冲区。使用高分辨率遥感影像确定微观层面的孳生地。基于宏观和微观孳生地，从每个初级卫生中心随机选取六个村庄，这些村庄具有代表所有生态类型的不同参数组合。2010 - 2011年在季风前和季风后季节按照标准技术收集了昆虫学数据并进行了统计分析。尝试进行差异分析以了解与疟疾传播相关的社会经济和其他决定因素。
基于生态、昆虫学、社会经济和其他当地参数，该研究确定了八个导致邦杜疟疾流行率高于安加拉初级卫生中心的危险因素。
该地区需要以综合病媒管理（IVM）模式开展有针对性的干预措施，以更好地管理和控制疾病。
