{"title":"基于急诊室真实近距离接触行为的呼吸道传染病传播","authors":"Bing Cao, Haochen Zhang, Nan Zhang","doi":"10.1016/j.idm.2025.07.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The risk of transmission of respiratory infectious diseases in emergency rooms is high, posing a severe threat to the health of healthcare workers (HCWs).</div></div><div><h3>Methods</h3><div>The study was conducted in an emergency room of a medical school at a university in Hong Kong during a clinical skills competition. A total of 19,246 s of video surveillance data were collected, recording the treatment of three types of patients (P1: infusion patient, P2: critically ill patient, P3: agitated patient). Taking coronavirus disease 2019 (COVID-19) as an example, a multi-route transmission model was established to assess the infection risk for HCWs and the effectiveness of various interventions.</div></div><div><h3>Results</h3><div>The average distances between HCWs and patients during the treatment of P1, P2, and P3 were 0.8 (25–75 percentile: 0.6, 1.1) m, 1.0 (0.8, 1.2) m, and 0.5 (0.4, 0.7) m, respectively. When treating P2, due to intubation procedures, the hourly risk of infection was highest at 43.4 % if no HCWs wore masks, which was 5.1 and 3.1 times higher than it during treatment of P1 (8.5 %) and P3 (13.9 %), respectively. During the treatment, without mask protection, the average hourly infection risk for nurses was 11.0 % (P1), 41.2 % (P2), and 16.8 % (P3), which was 1.8 times (P1), 0.9 times (P2), and 1.5 times (P3) that of doctors. If HCWs wear N95 respirators and surgical masks throughout, the total infection risk can be reduced by 94.7 % and 53.9 %, respectively. Increasing the ventilation rate from 1 ACH to 6 ACH reduced the infection risk through long-range airborne transmission by 43.8 % (P1), 36.1 % (P2), and 31.6 % (P3), with a total infection risk reduction of 2.4 % (P1), 5.6 % (P2), and 1.6 % (P3), respectively.</div></div><div><h3>Conclusions</h3><div>The findings of the study provide a scientific support for the precise prevention and control of respiratory infectious diseases under different treatments in emergency rooms.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1238-1251"},"PeriodicalIF":2.5000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transmission of respiratory infectious diseases based on real close contact behavior in an emergency room\",\"authors\":\"Bing Cao, Haochen Zhang, Nan Zhang\",\"doi\":\"10.1016/j.idm.2025.07.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>The risk of transmission of respiratory infectious diseases in emergency rooms is high, posing a severe threat to the health of healthcare workers (HCWs).</div></div><div><h3>Methods</h3><div>The study was conducted in an emergency room of a medical school at a university in Hong Kong during a clinical skills competition. A total of 19,246 s of video surveillance data were collected, recording the treatment of three types of patients (P1: infusion patient, P2: critically ill patient, P3: agitated patient). Taking coronavirus disease 2019 (COVID-19) as an example, a multi-route transmission model was established to assess the infection risk for HCWs and the effectiveness of various interventions.</div></div><div><h3>Results</h3><div>The average distances between HCWs and patients during the treatment of P1, P2, and P3 were 0.8 (25–75 percentile: 0.6, 1.1) m, 1.0 (0.8, 1.2) m, and 0.5 (0.4, 0.7) m, respectively. When treating P2, due to intubation procedures, the hourly risk of infection was highest at 43.4 % if no HCWs wore masks, which was 5.1 and 3.1 times higher than it during treatment of P1 (8.5 %) and P3 (13.9 %), respectively. During the treatment, without mask protection, the average hourly infection risk for nurses was 11.0 % (P1), 41.2 % (P2), and 16.8 % (P3), which was 1.8 times (P1), 0.9 times (P2), and 1.5 times (P3) that of doctors. If HCWs wear N95 respirators and surgical masks throughout, the total infection risk can be reduced by 94.7 % and 53.9 %, respectively. Increasing the ventilation rate from 1 ACH to 6 ACH reduced the infection risk through long-range airborne transmission by 43.8 % (P1), 36.1 % (P2), and 31.6 % (P3), with a total infection risk reduction of 2.4 % (P1), 5.6 % (P2), and 1.6 % (P3), respectively.</div></div><div><h3>Conclusions</h3><div>The findings of the study provide a scientific support for the precise prevention and control of respiratory infectious diseases under different treatments in emergency rooms.</div></div>\",\"PeriodicalId\":36831,\"journal\":{\"name\":\"Infectious Disease Modelling\",\"volume\":\"10 4\",\"pages\":\"Pages 1238-1251\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Disease Modelling\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468042725000636\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042725000636","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Transmission of respiratory infectious diseases based on real close contact behavior in an emergency room
Background
The risk of transmission of respiratory infectious diseases in emergency rooms is high, posing a severe threat to the health of healthcare workers (HCWs).
Methods
The study was conducted in an emergency room of a medical school at a university in Hong Kong during a clinical skills competition. A total of 19,246 s of video surveillance data were collected, recording the treatment of three types of patients (P1: infusion patient, P2: critically ill patient, P3: agitated patient). Taking coronavirus disease 2019 (COVID-19) as an example, a multi-route transmission model was established to assess the infection risk for HCWs and the effectiveness of various interventions.
Results
The average distances between HCWs and patients during the treatment of P1, P2, and P3 were 0.8 (25–75 percentile: 0.6, 1.1) m, 1.0 (0.8, 1.2) m, and 0.5 (0.4, 0.7) m, respectively. When treating P2, due to intubation procedures, the hourly risk of infection was highest at 43.4 % if no HCWs wore masks, which was 5.1 and 3.1 times higher than it during treatment of P1 (8.5 %) and P3 (13.9 %), respectively. During the treatment, without mask protection, the average hourly infection risk for nurses was 11.0 % (P1), 41.2 % (P2), and 16.8 % (P3), which was 1.8 times (P1), 0.9 times (P2), and 1.5 times (P3) that of doctors. If HCWs wear N95 respirators and surgical masks throughout, the total infection risk can be reduced by 94.7 % and 53.9 %, respectively. Increasing the ventilation rate from 1 ACH to 6 ACH reduced the infection risk through long-range airborne transmission by 43.8 % (P1), 36.1 % (P2), and 31.6 % (P3), with a total infection risk reduction of 2.4 % (P1), 5.6 % (P2), and 1.6 % (P3), respectively.
Conclusions
The findings of the study provide a scientific support for the precise prevention and control of respiratory infectious diseases under different treatments in emergency rooms.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.