Dengue fever has been considered to be one of the global public health problems of the twenty-first century, especially in tropical and subtropical countries of the global south. The high morbidity and mortality rates of Dengue fever impose a huge economic and health burden for middle and low-income countries. It is so prevalent in such regions that enforcing a granular level of surveillance is quite impossible. Therefore, it is crucial to explore an alternative cost-effective solution that can provide updates of the ongoing situation in a timely manner. In this paper, we explore the scope and potential of a local newspaper-based dengue surveillance system, using well-known data-mining techniques, in Bangladesh from the analysis of the news contents written in the native language. In addition, we explain the working procedure of developing a novel database, using human-in-the-loop technique, for further analysis, and classification of dengue and its intervention-related news. Our classification method has an f-score of 91.45%, and matches the ground truth of reported cases quite closely. Based on the dengue and intervention-related news, we identified the regions where more intervention efforts are needed to reduce the rate of dengue infection. A demo of this project can be accessed at: http://erdos.dsm.fordham.edu:3009/
翻译:登革热的高发病率和死亡率给中低收入国家带来了巨大的经济和健康负担。登革热在这些地区非常普遍,因此,必须探索一种成本效益高的替代解决办法,以便及时提供当前状况的最新信息。在本文件中,我们利用以当地语言撰写的新闻内容分析,探讨孟加拉国基于地方报纸的登革热监测系统的范围和潜力。此外,我们解释了开发新数据库的工作程序,利用“人就地”技术,进一步分析和分类登革热及其与干预有关的新闻。我们的分类方法有91.45%的基数,与所报道案件的地面真相非常吻合。根据登革热和与干预有关的新闻,我们查明了需要更多干预努力降低登革热感染率的区域。Ang/ANDUM/ANDUM。这个项目可以访问。