边境地区症状监测预警系统的研究与实现

发布时间：2018-07-06 13:00

本文选题：传染病 + 边境地区　；参考：《昆明理工大学》2017年硕士论文

【摘要】：近年来,由于全球传染病人数的不断攀增,仅仅依赖发病率进行疾病监测的常规监测方式逐渐的出现较多弊端,无法满足人们对公共卫生预警的需求,因此将疾病监测转变为症状监测的全新方式体现了更多的预防优势,得到了更多业内人士的关注。我国某(由于本文所展现的数据涉及到个人隐私,所以把本文中所有涉及到个人以及地域的信息全部采用"××"或"某某"表示。)省边境地区气候炎热潮湿,适合多种病菌滋生,山高林密无天然和人工屏障。特殊的自然环境和社会环境,造成边境地区传染病频发。如何在疾控中心随时查询该地区每天、每月发病人数以及发病症状,如何将最新的疫情信息及时上报、在遇到突发问题时如何迅速的解决,这都成了疾控中心人员所面临的难题。综上所述,本文的研究课题——边境地区症状监测预警系统研究与实现具有较强的应用价值和理论价值。该项目是为我国某省边境地区开发一套《边境地区症状监测预警系统》,以代替目前我国某省边境地区疾病上报中所涉及到的业务流程。边境地区症状监测预警系统的应用,将会在一定程度上提高应对突发公共卫生时间的质量和效率、改进医疗机构上报疾病症状的方式,解决纸质记录症状信息、传染病爆发响应不及时等矛盾,以及提高预测传染病爆发的效率,实现症状监测工作现代化。本文主要完成的工作如下:1.系统的需求分析与总体设计。本文通过对目前我国某省边境地区疾病症状上报工作中存在的问题出发,分析原有疾病症状上报的业务流程,对该省边境地区症状监测预警系统的需求进行了详细的分析。在需求分析的基础上,又对系统的总体架构进行了设计,并进一步分析了边境地区症状监测预警系统各功能模块的详细设计。2.系统的实现与测试。在系统总体设计的基础上,对系统进行了实现工作,包括android终端症状上报软件、PC终端后台管理系统的实现,同时在文中展示了系统的部分界面,并给出了系统的测试推广。通过系统的测试以及推广使用证明,我们实现的系统满足系统需求。3.预警模型设计。在系统推广使用的基础上,根据收集到的数据,利用BP神经网络算法设计出根据各症状月上报总数预测当月所有症状上报总数的预警模型。并通过与实际上报症状数进行比较证明,BP神经网络预警模型确实可行。
[Abstract]:In recent years, due to the increase of the number of infectious diseases in the world, the routine surveillance method which only depends on the incidence of disease surveillance has gradually appeared more malpractices, which can not meet the need of public health early warning. Therefore, the transformation of disease surveillance to symptom monitoring reflects more advantages of prevention and gets more attention from the industry. Since the data presented in this paper relate to personal privacy, all information about individuals and regions in this paper is expressed as "脳脳" or "such and so". Provincial border areas hot and humid climate, suitable for a variety of bacteria breeding, mountain forest dense without natural and artificial barriers. Special natural environment and social environment, resulting in frequent incidence of infectious diseases in border areas. How to inquire at the CDC about the number of cases and symptoms in the area every day and every month, how to report the latest epidemic information in time, and how to solve the sudden problems quickly. All this has become a difficult problem for CDC personnel. To sum up, the research and realization of the symptom monitoring and early warning system in the border area has strong application value and theoretical value. The project is to develop a set of "Border area symptom Monitoring and early warning system" for a border area of our country, to replace the business process involved in disease reporting in a border area of our country at present. The application of the symptom monitoring and early warning system in border areas will, to a certain extent, improve the quality and efficiency of responding to public health emergencies, improve the way medical institutions report disease symptoms, and solve the problem of documenting symptom information on paper. It is necessary to improve the efficiency of predicting the outbreak of infectious diseases and to realize the modernization of symptom monitoring. The main work of this paper is as follows: 1. System requirement analysis and overall design. Based on the analysis of the existing problems in the reporting of disease symptoms in a border area of China, this paper analyzes the business process of reporting the disease symptoms, and makes a detailed analysis of the needs of the symptom monitoring and early warning system in the border area of this province. On the basis of requirement analysis, the overall architecture of the system is designed, and the detailed design of each function module of the symptom monitoring and warning system in border area is analyzed. System implementation and testing. On the basis of the overall design of the system, the implementation of the system is carried out, including the implementation of the android terminal symptom reporting software and the PC terminal background management system. At the same time, some interfaces of the system are shown, and the test and popularization of the system are given. Through the test of the system and the popularization and use of the system, we realized the system to meet the system requirements. 3. 3. Early warning model design. Based on the data collected and the BP neural network algorithm, an early warning model is designed to predict the total number of symptoms reported in the month. It is proved that the BP neural network early warning model is feasible by comparing with the actual reported symptoms.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.52;TP277

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