Qayum Abdul, Arya Rakesh, Kumar Pawan, Lynn Andrew M
Centre for Biology & Bioinformatics, School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
Indira Gandhi National Forest Academy, Dehradun, India.
Malar J. 2015 May 7;14:192. doi: 10.1186/s12936-015-0685-4.
Malaria is a major health problem in the tropical and subtropical world. In India, 95% of the population resides in malaria endemic regions and it is major public health problem in most parts of the country. The present work has developed malaria maps by integrating socio-economic, epidemiology and geographical dimensions of three eastern districts of Uttar Pradesh, India. The area has been studied in each dimension separately, and later integrated to find a list of vulnerable pockets/villages, called as malarial hotspots.
The study has been done at village level. Seasonal variation of malaria, comparison of epidemiology indices and progress of the medical facility were studied. Ten independent geographical information system (GIS) maps of socio-economic aspects (population, child population, literacy, and work force participation), epidemiology (annual parasitic index (API) and slides collected and examined) and geographical features (settlement, forest cover, water bodies, rainfall, relative humidity, and temperature) were drawn and studied. These maps were overlaid based on computed weight matrix to find malarial hotspot.
It was found that the studied dimensions were inter-weaving factors for malaria epidemic and closely affected malaria situations as evidenced from the obtained correlation matrix. The regions with water logging, high rainfall and proximity to forest, along with poor socio-economic conditions, are primarily hotspot regions. The work is presented through a series of GIS maps, tables, figures and graphs. A total of 2,054 out of 8,973 villages studied were found to be malarial hotspots and consequently suggestions were made to the concerned government malaria offices.
With developing technology, information tools such as GIS, have captured almost every field of scientific research especially of vector-borne diseases, such as malaria. Malarial mapping enables easy update of information and effortless accessibility of geo-referenced data to policy makers to produce cost-effective measures for malaria control in endemic regions.
疟疾是热带和亚热带地区的一个主要健康问题。在印度，95%的人口居住在疟疾流行地区，这是该国大部分地区的一个主要公共卫生问题。本研究通过整合印度北方邦东部三个地区的社会经济、流行病学和地理维度，绘制了疟疾地图。对每个维度分别进行了研究，随后进行整合以找出易受影响的地区/村庄清单，即疟疾热点地区。
该研究在村庄层面开展。研究了疟疾的季节性变化、流行病学指标的比较以及医疗设施的进展情况。绘制并研究了十张独立的地理信息系统（GIS）地图，分别涉及社会经济方面（人口、儿童人口、识字率和劳动力参与率）、流行病学（年度寄生虫指数（API）以及采集和检测的玻片数量）和地理特征（定居点、森林覆盖、水体、降雨量、相对湿度和温度）。基于计算得出的权重矩阵对这些地图进行叠加，以找出疟疾热点地区。
研究发现，所研究的维度是疟疾流行的相互交织因素，并如相关矩阵所示，对疟疾情况有密切影响。积水、降雨量大且靠近森林的地区，以及社会经济条件较差的地区，主要是热点地区。研究结果通过一系列GIS地图、表格、图表和图形呈现。在研究的8973个村庄中，共有2054个被发现是疟疾热点地区，随后向相关政府疟疾防治办公室提出了建议。
随着技术的发展，诸如GIS等信息工具已几乎涵盖了科学研究的各个领域，尤其是媒介传播疾病领域，如疟疾。疟疾地图绘制使信息能够轻松更新，政策制定者能够毫不费力地获取地理参考数据，从而为流行地区的疟疾控制制定具有成本效益的措施。
