@91porn_soul Weekly Briefings for China CDC Weekly, Vol 6, No. 37, 2024

Mapping the Characteristics of Respiratory Infectious Disease Epidemics in China Based on the Baidu Index from November 2022 to January 2023@91porn_soul

Dazhu Huo1*; @91porn_soulTing Zhang2*; Xuan Han2; Liuyang Yang2; Lei Wang3; Ziliang Fan4; Xiaoli Wang5; Jiao Yang2; Qiangru Huang2; Ge Zhang6; Ye Wang2; Jie Qian2; Yanxia Sun2; Yimin Qu2; Yugang Li2; Chuchu Ye7; Luzhao Feng2; Zhongjie Li2; Weizhong Yang2#; Chen Wang1#

1School of Health Policy and Management， Chinese Academy of Medical Sciences & Peking Union Medical College， Beijing， China;

2School of Population Medicine and Public Health， Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College， Beijing， China;

3Yichang Center for Disease Prevention and Control， Yichang City， Hubei Province， China;

4Weifang Center for Disease Prevention and Control， Weifang City， Shandong Province， China;

5Beijing Center for Disease Prevention and Control， Beijing， China;

6School of Public Health， Dali University， Dali City， Yunnan Province， China;

7Shanghai Pudong New Area Center for Disease Control and Prevention， Shanghai， China.

*Joint first authors.

#Corresponding authors: Chen Wang， cyh-birm@263.net; Weizhong Yang， yangweizhong@cams.cn.

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Infectious diseases pose a significant global health and economic burden， underscoring the critical need for precise predictive models. The Baidu index provides enhanced real-time surveillance capabilities that augment traditional systems. This study aimed to develop a surveillance model leveraging the Baidu index for accurate detection of disease propagation trends， facilitating timely and effective public health responses. Data on the keyword "fever" were extracted from the Baidu search engine across 255 cities in China from November 2022 to January 2023. Various onset and peak detection criteria combining thresholds and consecutive days were tested to identify the start and peak of influenza epidemics. The most effective scenario for indicating epidemic commencement involved a 90th percentile threshold exceeded for seven consecutive days， minimizing false starts. Peak detection was optimized using a 7-day moving average for its balance of stability and precision. The use of internet search data， such as the Baidu index， significantly improves the timeliness and accuracy of disease surveillance models. This innovative approach supports quicker public health interventions， demonstrating its potential in enhancing epidemic monitoring and response efforts.

 

基于百度指数画图呼吸说念传染病疫情流行特征 — 中国，2022年11月–2023年1月

霍大柱1*；张婷2*；韩萱2；杨柳飏2；王蕾3；范子亮4；王小莉5；杨娇2；黄蔷如2；张戈6；王也2；钱捷2；孙艳霞2；曲翌敏2；李玉刚2；叶楚楚7；冯录召2；李中杰2；杨维中2#；王辰1#

1 中国医学科学院北京协和医学院卫生健康处理计策学院，北京，中国；

2 中国医学科学院北京协和医学院群医学及宇宙卫生学院，北京，中国；

3 湖北省宜昌市疾病驻守死心中心，宜昌市，湖北省，中国；

4 山东省潍坊市疾病驻守死心中心，潍坊市，山东省，中国；

5 北京市疾病驻守死心中心，北京，中国；

6 大理大学宇宙卫生学院，大理市，云南省，中国；

7 上海市浦东新区疾病驻守死心中心，上海市，中国。

*共同第一作家

#通信作家：王辰，cyh-birm@263.net；杨维中，yangweizhong@cams.cn。

 

传染病不仅严重恫吓全球宇宙卫生，还对经济酿成要紧包袱。现存的传染病监测系统亟需扩大监测渠说念并通过引入新时刻进行普及其监测才气。本商酌旨在开发一种应用百度指数进行传染病传播趋势精确判断的监测模子，以已毕快速而灵验的宇宙卫生嘱托。从2022年11月至2023年1月，本商酌提真金不怕火了中国255个城市中对于“发烧”要道词的百度搜索引擎数据。测试了聚积阈值和联络天数的多种肇端和岑岭检测圭臬，以识别流行的运转和岑岭。商酌标明流交运转的最灵验场景是联络七天逾越90百分位的阈值，最猛经过地减少了误报。流行岑岭检测则通过使用7天迁徙平均值来优化，以均衡褂讪性和精确性。使用如百度指数的互联网搜索数据进行传染病监测，可在一定经过上普及传统传染病监测系统的实时性和准确性。这种立异步地救援更快的宇宙卫生侵扰，展示了其在增强传染病监控和反应方面的后劲。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.195

 

 

Establishment of a Lateral Flow Dipstick Detection Method for Influenza A Virus Based on CRISPR/Cas12a System

Xiaoyan Zhao1; Ximing Zheng1; Xiyong Yang1; Qi Guo3; Yi Zhang2#; Jun Lou1#

1 Department of Clinical Laboratory， Zhumadian Central Hospital， Zhumadian City， Henan Province， China;

2 National Institute for Viral Disease Control and Prevention， Chinese Center for Disease Control and Prevention， Beijing， China;

3 Laboratory of Virology， Beijing Key Laboratory of Etiology of Viral Diseases in Children， Capital Institute of Pediatrics， Beijing， China

#Corresponding author: Yi Zhang， zhangyicdc@126.com; Jun Lou， 13783378825@163.com.

 

This study aimed to develop a rapid， visual PCR-CRISPR/Cas12-LFD method for detecting influenza A by utilizing the conserved region of the matrix protein gene. We crafted universal degradation primers and clustered regularly interspaced short palindromic repeats RNA (CRISPR RNA， crRNA) targeting the conserved matrix protein gene of the influenza virus (IFV)， integrated with lateral flow dipstick (LFD) technology. This new PCR-CRISPR/Cas12-LFD approach was designed to determine its sensitivity and specificity through the analysis of various clinical samples collected in 2023. The developed nucleic acid assay for influenza A viruses (IAV) demonstrated a sensitivity of 10 copies/mL without cross-reactivity with other respiratory pathogens. Evaluation of 82 clinical samples showed high concordance with results from fluorescent Polymerase Chain Reaction (PCR)， achieving a kappa value of 0.95. A highly sensitive and specific PCR-CRISPR/Cas12-LFD method has been successfully established for the detection of influenza A， offering a robust tool for its diagnosis and aiding in the prevention and control of this virus.

 

基于CRISPR/Cas12a系统的甲型流感病毒试纸条检测步地的开发

赵小燕1；郑锡铭1；杨喜永1；郭琪3；张益2#；娄峻1#

1 驻马店市中心病院医学磨真金不怕火科，驻马店市，河南省，中国；

2 中国疾病驻守死心中心病毒病驻守死心所，北京，中国；

3 都门儿科商酌所病毒学商酌室，儿童病毒病原学北京要点试验室，北京，中国。

#通信作家：张益，Email: zhangyicdc@126.com；娄峻，Email: 13783378825@163.com。

 

本商酌基于基质卵白（M， Matrix）基因的保守区域，开发一种快速检测甲型流感的PCR-CRISPR/Cas12-LFD可视化检测步地。以流感病毒基质卵白（M， Matrix）基因的保守区域为靶标，瞎想合成通用型的简并引物和成簇轨则休止的短回环重迭序列 RNA（Clustered Regularly Interspaced Short Palindromic Repeats RNA，CRISPR RNA，crRNA），聚积侧流层析试纸条（Lateral flow dipstick， LFD）时刻，开发针对甲型流感病毒的PCR-CRISPR/Cas12-LFD步地，分析其灵敏度和特异性，并通过检测2023年流行的不同亚型临床样本进行考证。本商酌开发了针对甲型流感病毒的核酸检测步地，灵敏度达到10copies/mL，和其他呼吸说念病原体不存在交叉反应；考证了82份临床样本，检测成果和荧光PCR一致性较高，两种步地的kappa统统为0.95。开发一种针对甲型流感病毒的高灵敏度且特异性的检测步地，为甲型流感病毒的会诊提供了有劲的器具，有助于甲型流感病毒的驻守和死心。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.198

 

 

Development and Diagnosis Performance of IgM-Based Rapid Antigen Test for Early Detection of SARS-CoV-2 Infection in a Large Cohort of Suspected COVID-19 Cases — USA， Poland， and Sweden， 2021–2022

Yihua Huang1*; Yiyi Pu2*; Youhong Weng3@91porn_soul，4*; Yahan Wu3; Qing He3; Sofia Litchev5; Longyou Zhao1; Haojie Ding3; Yunru Lai1; Jie Li1; Xiaojun Zheng6; Jinshu Chen6; XianqinXiong6; Shaohong Lu3; Fei Gao6#; Meng Gao3#; Qingming Kong2#

1 Department of Laboratory Medicine， Lishui Second People's Hospital Affiliated to Wenzhou Medical University， Lishui City， Zhejiang Province， China;

2 Key Laboratory of Biomarkers and In Vitro Diagnosis Translation of Zhejiang province， School of Laboratory Medicine and Bioengineering， Hangzhou Medical College， Hangzhou City， Zhejiang Province， China;

3 School of Basic Medicine and Forensics， Key Laboratory of Bio-tech Vaccine of Zhejiang Province， Engineering Research Center of Novel Vaccine of Zhejiang Province， Hangzhou Medical College， Hangzhou City， Zhejiang Province， China;

4 Department of Chemistry & Biochemistry， University of California， Los Angeles， CA， USA;

5 The Fifth Affiliated Hospital of Wenzhou Medical University， Lishui City， Zhejiang Province， China;

6 Department of Research and Development， Hangzhou AllTest Biotech Co.， Ltd， Hangzhou City， Zhejiang Province， China.

*Joint first authors.

#Corresponding author: Fei Gao， soar.gao@alltests.com.cn; Meng Gao， yourgm@hotmail.com; Qingming Kong， qmkong_1025@163.com.

 

Antigen testing has been crucial in effectively managing the coronavirus disease 2019 (COVID-19) pandemic. This study evaluated the clinical performance of a nasopharyngeal swab (NPS)-based antigen rapid diagnostic test (Ag-RDT) compared to the gold standard real-time reverse transcription-polymerase chain reaction (RT-PCR) for early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We developed an IgM-based rapid antigen test for early detection of SARS-CoV-2 infection. Between July 2021 and January 2022， we analyzed 1，030 nasopharyngeal swab (NPS) samples from participants at three centers in different countries， using both antigen rapid diagnostic tests (Ag-RDT) and RT-PCR. The Ag-RDT demonstrated minimal detection limits as low as 0.1 ng/ml for recombinant N antigen and 100 TCID50/mL for heat-inactivated SARS-CoV-2 virus. Specificity assessments involving four human coronaviruses and 13 other respiratory viruses showed no cross-reactivity. The Ag-RDT assay (ALLtest) exhibited high sensitivity (93.18%–100%) and specificity (99.67%–100%) across all centers. Factors such as cycle threshold (Ct) values and the timing of symptoms since onset were influential， with sensitivity increasing at lower Ct values (<30) and within the first week of symptoms. The ALLtest Ag-RDT demonstrated high reliability and significant potential for diagnosing suspected COVID-19 cases.

 

基于IgM的严重急性呼吸详尽征冠状病毒2抗原快速检测试剂偏握在大领域疑似COVID-19病例部队中的早期检测性能商酌 — 好意思国，瑞典，波兰，2021-2022 年

黄益华1*；蒲依依2*；翁有红3，4*；吴亚寒3；何青3；Sofia Litchev5；赵龙友1；丁铁汉3；赖云茹1；李杰1；郑孝君5；陈金树5；熊先勤5；陆绍红3；高飞5#；高孟3#；孔庆明2#

1 温州医科大学附庸丽水市第二东说念主民病院磨真金不怕火科，丽水市，浙江省，中国；

2 浙江省生物标记物与体外会诊回荡要点试验室，杭州医学院磨真金不怕火医学院、生物工程学院，杭州市，浙江省，中国；

3 浙江省生物时刻疫苗要点试验室，新式疫苗浙江省工程商酌中心，杭州医学院基础医学与法医学院，杭州市，浙江省，中国；

4 温州医科大学附庸第五病院，丽水市，浙江省，中国；

5 杭州奥泰生物科技股份有限公司研发部，杭州市，浙江省，中国。

*共同第一作家。

#通信作家：高飞，soar.gao@alltests.com.cn；高孟，yourgm@hotmail.com；孔庆明，qmkong_1025@163.com。

 

抗原检测在灵验嘱托2019冠状病毒病（COVID-19）大流行中上演了要道扮装。本商酌旨在评估基于鼻咽拭子（NPS）的抗原快速会诊检测（Ag-RDT）与金圭臬实时逆转录团聚酶链反应（RT-PCR）在早期检测新式冠状病毒（SARS-CoV-2）中的临床性能。咱们开发了一种基于IgM的快速抗原检测步地，用于早期检测SARS-CoV-2感染。在2021年7月至2022年1月时间，咱们使用Ag-RDT和RT-PCR步地对来自不同国度3个中心的1，030份鼻咽拭子（NPS）样本进行了分析，这些样原本自2021年7月至2022年1月的参与者。Ag-RDT表露了极低的检测限，对于重组N抗原为0.1 ng/ml，对于热灭活的SARS-CoV-2病毒为100 TCID50/mL。对4种东说念主类冠状病毒和13种其他呼吸说念病毒的特异性评估未发现交叉反应。Ag-RDT检测（ALLtest）在统统中心发达出好意思妙锐性（93.18%–100%）和高特异性（99.67%–100%）。检测明锐性受Ct值和症状出刻下候等成分影响，在较低的Ct值（<30）和症状出现的第一周内检测明锐性较高。ALLtest Ag-RDT在会诊疑似COVID-19病例方面展现出出奇的可靠性和权贵的后劲。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.199

 

 

Development and Comparison of Time Series Models in Predicting Severe Fever with Thrombocytopenia Syndrome Cases — Hubei Province， China， 2013–2020

Zixu Wang1， 2*; Jinwei Zhang3*; Wenyi Zhang4*; Nianhong Lu1; Qiong Chen1; Junhu Wang1; Yingqing Mao1; Haiming Yi1; Yixin Ge1; Hongming Wang1; Chao Chen1; Wei Guo1; Xin Qi5; Yuexi Li7#; Ming Yue6#; Yong Qi1#

1 Huadong Research Institute for Medicine and Biotechniques， Nanjing City， Jiangsu Province， China

2 Bengbu Medical College， Bengbu City， Anhui Province， China;

3 Department of Anesthesiology， Nanjing Drum Tower Hospital， Affiliated Hospital of Medical School， Nanjing University， Nanjing City， Jiangsu Province， China;

4 Chinese PLA Center for Disease Control and Prevention， Beijing， China;

5 The Second People's Hospital of Yiyuan County， Zibo City， Shandong Province， China;

6 Department of Infectious Diseases， The First Affiliated Hospital of Nanjing Medical University， Nanjing City， Jiangsu Province， China;

7 School of Public Health， Nanjing Medical University， Nanjing City， Jiangsu Province， China.

† Joint first authors.

* Corresponding author: Yuexi Li， liyxi2007@126.com; Ming Yue， njym08@163.com; Yong Qi， qslark@126.com.

 

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus， which has a high mortality rate. Predicting the number of SFTS cases is essential for early outbreak warning and can offer valuable insights for establishing prevention and control measures. In this study， data on monthly SFTS cases in Hubei Province， China， from 2013 to 2020 were collected. Various time series models based on seasonal auto-regressive integrated moving average (SARIMA)， Prophet， eXtreme Gradient Boosting (XGBoost)， and long short-term memory (LSTM) were developed using these historical data to predict SFTS cases. The established models were evaluated and compared using mean absolute error (MAE) and root mean squared error (RMSE). Four models were developed and performed well in predicting the trend of SFTS cases. The XGBoost model outperformed the others， yielding the closest fit to the actual case numbers and exhibiting the smallest MAE (2.54) and RMSE (2.89) in capturing the seasonal trend and predicting the monthly number of SFTS cases in Hubei Province. The developed XGBoost model represents a promising and valuable tool for SFTS prediction and early warning in Hubei Province， China.

 

发烧伴血小板减少详尽征时候序列展望模子的开发与相比 — 湖北省，2013–2020年

王子旭1， 2*；张津玮3*；张文义4*；陆年宏1；陈琼1；王俊虎1；毛颖清1；易海鸣1；葛艺欣1；王洪铭1；陈超1；郭伟1；都新5；李越希7#；岳明6#；都永1#

1 华东医学生物时刻商酌所，南京市，江苏省，中国；

2 蚌埠医科大学，蚌埠市，安徽省，中国；

3 南京饱读楼病院，南京大学附庸病院，南京市，江苏省，中国；

4 中国东说念主民自若军疾病驻守死心中心，北京，中国；

5 沂源县第二东说念主民病院，淄博市，山东省，中国 ；

6 南京医科大学第一附庸病院，南京市，江苏省，中国；

7 南京医科大学宇宙卫生学院，南京市，江苏省，中国。

*共同第一作家。

#通信作家: 李越希， liyxi2007@126.com; 岳明， njym08@163.com; 都永， qslark@126.com。

 

发烧伴血小板减少详尽征(Severe fever with thrombocytopia syndrome， SFTS)是由发烧伴血小板减少详尽征病毒引起的一种新发传染病，具有很高的圆寂率。展望SFTS病例数对于早期暴发的预警至关伏击，并可为制定驻守和死心递次提供有价值的视力。采集2013-2020年湖北省每月SFTS病例贵府。应用这些历史数据，开发基于季节性差分自追忆滑动平均模子(seasonal auto-regressive integrated moving average， SARIMA)、Prophet、极点梯度普及算法（eXtreme Gradient Boosting， XGBoost)和詈骂时顾忌汇聚(long short-term memory， LSTM)等的多样时候序列模子来展望SFTS病例。接纳平均统统差错(mean absolute error， MAE)和均方根差错(root mean squared error， RMSE)对开发的模子进行评价和相比。开发的4种模子，均能较好地展望SFTS病例趋势。XGBoost模子与本体病例数拟合最接近，MAE(2.54)和RMSE(2.89)最小，在展望病例随时候的变化趋势和湖北省月度SFTS病例数方面优于其他模子。本商酌开发的XGBoost模子为湖北省SFTS疫情展望和预警提供了一个有长进和价值的器具。。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.200

 

 

A Norovirus-Related Gastroenteritis Outbreak Stemming from a Potential Source of Infection — Pudong New Area， Shanghai Municipality， China， April 2024

Zou Chen1，2; Hong Zhang1，2; Yifeng Shen1，2; Chuchu Ye1，2#

1 Shanghai   Pudong New Area Center for Disease Control and Prevention， Shanghai， China;

2 Fudan University Pudong Institute of Preventive Medicine， Shanghai， China.

# Corresponding Authors: Chuchu Ye， ccye@pdcdc.sh.cn.

 

On April 27， 2024， an outbreak of norovirus-related gastroenteritis occurred in Pudong New Area， Shanghai. Through investigation of the outbreak and laboratory testing， the objectives were to identify pathogens， characterize outbreaks and implement effective control strategies. There were 11 cases in the outbreak， the attack rate was 5.02% (11/219)， the main symptoms were vomiting (100%)， abdominal pain (82%)， all cases were mild. This outbreak was precipitated by a potential source of infection in a child resuming class after a 72-hour quarantine post-symptom resolution， leading to a cluster of cases within the class. Testing revealed that three case samples were positive for Norovirus GII nucleic acid， while all environmental samples tested negative. Through the implementation of public health response， including strengthening morning checks， case isolation， disinfection， and suspending collective activities. All cases recovered and resumed classes on May 6， with no new cases， and the outbreak was closed. The investigation showed that although a 72-hour quarantine post-symptom resolution of norovirus infection， the detoxification period of the virus may exceed 72 hours， and further investigation into the detoxification period of asymptomatic patients is recommended to improve outbreak control strategies.

 

一说念源自潜在感染源的诺如病毒关系胃肠炎暴发疫情拜访 — 中国上海市浦东新区，2024年4月

陈诹1，2；张鸿1，2；沈奕峰1，2；叶楚楚1，2#

1 上海市浦东新区疾病驻守死心中心，上海，中国；

2 复旦大学浦东驻守医学商酌院，上海，中国。

#通信作家：叶楚楚，ccye@pdcdc.sh.cn。

 

2024年4月27日，上海市浦东新区发生了一说念诺如病毒关系胃肠炎暴发疫情。通过暴发拜访和试验室检测，旨在识别病原体，阵势疫情特征和实施灵验死心策略。该疫情共敷陈11例病例，罹患率为5.02%（11/219），主要症状为吐逆（100%）和腹痛（82%），统统病例症状均较轻。拜访表露，疫情可能发祥于一个潜在感染源，又名儿童在症状缓解后72小时艰涩后复返教室，随后同班的儿童陆续出现症状。试验室检测表露三份病例样本诺如病毒GII核酸阳性，而环境样本均阴性。通过实施宇宙卫生反应递次包括加强晨检、病例艰涩、消毒、暂停集体举止等，5月6日，统统病例均康复复课，无新病例，疫情获得死心。拜访表露，尽管诺如病毒感染的艰涩期为症状缓解后72小时，但病毒排毒时候可能逾越72小时，仍有传播风险，提议对无症状感染者的排毒期进行更真切的商酌，以便矫正疫情死心策略。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.197

 

 

Intelligent Forest Hospital as a New Management System for Hospital-Acquired Infection Control

Yingxin Liu1; Zhousheng Lin2; Guanwen Lin3; Wanmin Lian4; Junzhang Tian5; Guowei Li1，6，7#; Hongying Qu1，5#

1 Center for Clinical Epidemiology and Methodology (CCEM)， The Affiliated Guangdong Second Provincial General Hospital of Jinan University， Guangzhou City， Guangdong Province， China;

2 Medical Department， The Affiliated Guangdong Second Provincial General Hospital of Jinan University， Guangzhou City， Guangdong Province， China;

3 Hospital-Acquired Infection Control Department， The Affiliated Guangdong Second Provincial General Hospital of Jinan University， Guangzhou City， Guangdong Province， China;

4 Information Department， The Affiliated Guangdong Second Provincial General Hospital of Jinan University， Guangzhou City， Guangdong Province， China;

5 Institute for Healthcare Artificial Intelligence Application， The Affiliated Guangdong Second Provincial General Hospital of Jinan University， Guangzhou City， Guangdong Province， China;

6 Father Sean O’Sullivan Research Centre， St. Joseph’s Healthcare Hamilton， Hamilton， ON， Canada;

7 Department of Health Research Methods， Evidence， and Impact (HEI)， McMaster University， Hamilton， ON， Canada.

*Corresponding author: Guowei Li， ligw@gd2h.org.cn; Hongying Qu， tggd2h@163.com.

 

A new system called Intelligent Forest Hospital (IFH) is being implemented at Guangdong Second Provincial General Hospital to enhance hospital-acquired infection (HAI) control， especially in the aftermath of the COVID-19 pandemic. IFH leverages advancements in artificial intelligence， 5G， and cloud networking to implement customized indoor air quality control strategies across various medical settings. The system utilizes intelligent disinfection devices and air purification systems to maintain safe indoor environments similar to forest sanatoriums. A dynamic 3D hospital model provides real-time monitoring of critical air quality parameters， enabling prompt risk alerts and automated disinfection when necessary. While challenges remain in areas like costs， privacy， and general applicability， the integration of IFH with cutting-edge technologies shows promise in enhancing HAI prevention and management. The aim is to create a safe and pleasant environment for patients， staff， and visitors， particularly in the context of COVID-19 and potential future pandemics. Further research is needed to optimize the system and address implementation barriers， but IFH represents an innovative approach to infection control in healthcare settings.

 

理智丛林病院行为病院感染防控的新式体系

刘颖欣1；林周胜2；林冠文3；连万民4；田军章5；黎国威1，6，7#；瞿红鹰1，5*

1 暨南大学附庸广东省第二东说念主民病院临床流行病与步地学中心，广州市，广东省，中国；

2 暨南大学附庸广东省第二东说念主民病院医务部，广州市，广东省，中国；

3 暨南大学附庸广东省第二东说念主民病院感染处理科，广州市，广东省，中国；

4 暨南大学附庸广东省第二东说念主民病院信息科，广州市，广东省，中国；

5 暨南大学附庸广东省第二东说念主民病院东说念主工智能医疗应用商酌所，广州市，广东省，中国；

6 圣约瑟夫医疗中心， 汉密尔顿市， 安好像省， 加拿大；

7 麦克马斯特大学， 汉密尔顿市， 安好像省， 加拿大。

*通信作家: 黎国威， ligw@gd2h.org.cn; 瞿红鹰， tggd2h@163.com。

 

近期，受新冠疫情院感的领导，广东省第二东说念主民病院上线了理智丛林病院系统，以便更好地灵验防控病院感染的风险。理智丛林病院系统通过会通东说念主工智能、5G和云汇聚等数字化科技，在宽阔场景中生动接纳空气质料处理模式，聚积多种智能消毒征战和空气质料处理系统，达到灵验杀灭无益物资、加多空气负离子浓度、打造病院“丛林氧吧”的观念。此外，理智丛林病院通过整合安保感控全方向感控系统、开发动态3D院区模子、实时监测病院的环境野心值，以已毕精确的风险预警，并在必要时进行自动空气消毒净化。尽管当前还存在多方面的挑战（如本钱死心、躲避保护和通用握行性等），该系统可为患者、医务东说念主员和家属创造一个洁净、安全、情景的医疗环境，是病院空气质料处理理念策略的一次告捷立异。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2024.201