Complex Networks and Systems Group, Institute for Scientific Interchange Foundation, Torino, Italy.
PLoS One. 2011 Feb 28;6(2):e17144. doi: 10.1371/journal.pone.0017144.
Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals.
We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25% of the contacts involved a ward assistant, 23% a nurse, 22% a patient, 22% a caregiver, and 8% a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections.
Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings.
医院感染给医疗保健系统带来了巨大负担，是当前公共卫生的主要问题之一，需要付出大量努力来预防。了解医院环境中感染传播的动态对于量身定制干预措施和预测个体之间的传播至关重要。数学模型需要有关于个体之间接触的准确数据来提供信息。
我们使用可穿戴式有源射频识别设备 (RFID) 以约 1.5 米的空间分辨率和 20 秒的时间分辨率来检测个体之间的面对面接触。该研究在一家普通儿科医院病房进行，为期一周，包括 119 名参与者，其中 51 名医护人员、37 名患者和 31 名护理人员。在研究期间记录了近 16000 次接触，参与者每天的中位数约为 20 次接触。总体而言，25%的接触涉及病房助理，23%的接触涉及护士，22%的接触涉及患者，22%的接触涉及护理人员，8%的接触涉及医生。大多数接触持续时间较短，但也发现了长时间和频繁的接触，特别是在患者和护理人员之间。在所研究的环境中，护理人员不会对大量个体的感染传播构成重大潜在威胁，因为他们的互动主要涉及相应的患者。护士由于在感染潜在传播途径中的核心作用，应该成为预防策略的优先考虑对象。
我们的研究表明，在医院环境中准确且可重复地测量接触模式是可行的。所获得的结果对于研究呼吸道感染的传播、监测关键模式以及制定针对性的预防策略特别有用。接近感应技术应被视为在特定环境中测量此类模式和评估医院感染预防策略的有价值工具。
