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The construction of a hospital disease tracking and control system with a disease infection probability model

机译:基于疾病感染概率模型的医院疾病跟踪控制系统的构建

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摘要

With relatively short latency and rapid propagation, viral diseases could be transmitted through the air to medical personnel or the public during the incubation period. To reduce the possibilities of spread, this research creates an infection probability model based on the settling velocity and concentration distribution of infectious droplets. Then, radio frequency identification (RFID) technology is employed to track the travel history (time, date and place) of the infected patients. A tree structure algorithm and an infection probability model are applied to trace the transmission routes, discover the correlations between carriers and suspected cases, and finally calculate the infection probability on the basis of time interval. In case of an epidemic outbreak or once an infected case is confirmed, the disease tracking and control system could be initiated by accessing RFID logs to plot the carriers’ time of onset and to trace possible routes of transmission via tree diagrams. The disease tracking and control system developed in this research can assist hospitals in assessing the risk of infection among medical personnel, as well as in prompt implementation of infection prevention and control measures, in order to reduce hospital acquired infections and provide a safe health care setting.
机译:由于潜伏期较短且传播迅速,在潜伏期期间,病毒性疾病可通过空气传播给医务人员或公众。为了减少传播的可能性,本研究基于感染滴的沉降速度和浓度分布创建了一个感染概率模型。然后,采用射频识别(RFID)技术来跟踪受感染患者的旅行历史(时间,日期和地点)。应用树结构算法和感染概率模型跟踪传播路径,发现携带者与疑似病例之间的相关性,最后根据时间间隔计算出感染概率。在流行病暴发或确定感染病例的情况下,可以通过访问RFID日志来启动疾病跟踪和控制系统,以绘制出携带者的发病时间并通过树形图来追踪可能的传播途径。本研究开发的疾病跟踪和控制系统可以帮助医院评估医务人员中的感染风险,并迅速实施感染预防和控制措施,以减少医院获得的感染并提供安全的医疗环境。

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