World Health Day 2025: Time to ChangeMindset Beyond Global Commitment to Maternal Health and Women’s Well-Being

Minmin Wang^1,2;Minghui Ren^1,2,3,4,#

1.Department of Global Health, School of Public Health, Peking University,Beijing, China;

2.Beijing Institute for Health Development, Peking University, Beijing, China;

3.Institute for Global Health, Peking University, Beijing, China;

4.China Center for Health Development Studies, Peking University, Beijing, China.

^# Corresponding authors: Minghui Ren, renminghui@pku.edu.cn.

The World Health Day 2025 calls for globalcommitment to maternal health. Maternal health has long been a central focus inthe global health agenda, prominently featured in both the MillenniumDevelopment Goals and Sustainable Development Goals. Substantial progress hasbeen made in reducing maternal mortality through international collaboration.However, significant challenges persist, including reductions in global healthfinancing and emerging threats such as climate change. Mindset changes areurgently needed for maternal health and broader global health governance.Sustainable investment and health system strengthening are imperative. Globalhealth governance should be reformed through a paradigm shift toward anaccountable, fair, efficient, and transparent ecosystem.

2025年世界卫生日：革新观念，超越全球承诺，维护孕产妇健康和妇女福祉

王敏敏^1,2；任明辉^1,2,3,4,#

1. 全球卫生学系，公共卫生学院，北京大学，北京，中国；

2. 首都卫生与健康发展研究院，北京大学，北京，中国；

3. 全球卫生研究院，北京大学，北京，中国；

4. 中国卫生发展研究中心，北京大学，北京，中国。

^# 通信作者：任明辉，renminghui@pku.edu.cn。

2025年世界卫生日聚焦全球孕产妇健康。孕产妇健康是全球卫生的核心议题，是千年发展目标和可持续发展目标的核心组成。在国际社会的共同努力下，全球孕产妇死亡率显著下降。然而，当前全球卫生治理面临多重挑战，国际卫生援助资金大幅缩减、气候变化持续加剧等新兴挑战，对孕产妇保健体系的可持续发展构成严峻威胁。孕产妇保健体系和更广泛的全球卫生治理亟需观念革新。可持续筹资与加强卫生体系建设迫在眉睫。改革全球卫生治理，亟需构建一个具备问责机制、彰显公平、运行高效且兼具透明度的全球卫生体系。

For more information:https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.074

Changing Patterns of EpidemiologicalCharacteristics and Spatial-Temporal Clusters of Human Brucellosis Based onCounty Level — China, 2011–2023

Shijian Zhou¹; Huijie Qin²; Qingnan Shi¹;Sihan Li¹; Junyuan Chen²; Qiulan Chen^1,#

1. NationalKey Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases,Chinese Center for Disease Control and Prevention, Beijing, China;

2. School of Public Health, Guangxi Medical University, Nanning City,Guangxi Zhuang Autonomous Region, China;

^# Corresponding author:Qiulan Chen, chenql@chinacdc.cn.

Human brucellosis persists as a criticalpublic health challenge in China. Understanding disease clusters and trends isessential for implementing effective control strategies. This study evaluatesthe epidemiological characteristics and spatiotemporal distribution ofbrucellosis in China from 2011 to 2023. Data were obtained from the NationalNotifiable Disease Reporting System (NNDRS). We conducted descriptiveepidemiological analyses and employed SaTScan10.1 and ArcGIS10.7 software toidentify disease clusters and generate county (district)-level incidence maps.The incidence of human brucellosis in mainland China increased substantiallybetween 2011 and 2023, rising from 38,151 cases (2.8/100,000) across 834counties (25.4%) to 70,439 cases (5.2/100,000) across 2,290 counties (76.9%). Asignificant upward trend in reported incidence emerged during 2018–2023 [averageannual percentage change (AAPC)=14.9%, P=0.01].Most cases (89.3%) occurred in individuals aged 25–69 years, with an increasingproportion among those aged over 60 years. While 96.1% of cases were reportedin northern provincial-level administrative divisions (PLADs), southern regionsdemonstrated escalating incidence rates and expanding geographical spread.Southern PLADs exhibited a notable annual increase of 31.5% in reportedincidence (P<0.01). Counties(districts) with incidence rates exceeding 10 per 100,000 expandedgeographically from northwestern pastoral regions to southern areas and fromrural to urban settings. Primary spatiotemporal clusters were concentrated inInner Mongolia and adjacent PLADs, with emerging clusters identified in Yunnan,Guangdong, and Xizang. The human brucellosis epidemic in China continues tointensify, characterized by rebounding incidence rates and broader geographicaldistribution across counties (districts). While spatiotemporal clusters remainpredominantly centered in Inner Mongolia and neighboring regions, targetedinterventions and increased resource allocation for high-risk areas andpopulations are imperative.

基于县尺度的人间布鲁氏菌病流行特征与时空聚集性变化趋势分析—中国，2011–2023年

周世健¹；覃慧婕²；史青楠 ¹；李思寒¹；陈俊元²；陈秋兰^1,#

1. 传染病溯源预警与智能决策全国重点实验室，中国疾病预防控制中心，北京，中国；

2. 公共卫生学院，广西医科大学，南宁市，广西壮族自治区，中国。

^# 通信作者:陈秋兰，chenql@chinacdc.cn。

人间布鲁氏菌病仍然是中国的一个重要公共卫生问题。了解疫情聚集性与发展趋势对制定有效的疾病控制策略至关重要。本研究评估了 2011 年至 2023 年间中国人间布鲁氏菌病流行病学特征与时空聚集性情况。本研究从中国国家法定传染病报告系统（NNDRS）中获取数据。通过流行病学描述性分析，使用SaTScan10.1和ArcGIS10.7软件探究疫情聚集性，并使用县（区）级地图直观展示年发病率和时空聚集群。2011至2023年间，中国大陆人间布鲁氏菌病的发病率呈大幅上升趋势，从834个县区（25.4%）的38,151例病例（2.8/10万）上升至2,290个县区（76.9%）的70,439例病例（5.2/10万）。2018至 2023 年间，布病报告发病率呈上升趋势（AAPC=14.9%，P=0.01）。大多数病例（89.3%）发生在 25-69 岁的人群中，60 岁以上人群病例占比逐年上升。据报告，96.1%的病例发生在中国大陆北方的省级行政区（PLADs），但南方省份县（区）的发病率和患病人数均呈上升趋势。值得注意的是，南部省级行政区的报告发病率每年上升31.5%（P<0.01）。发病率超过10/10万的县（区）在地域上从西北地区扩展到南部地区，从牧区扩展到城市地区。时空聚集区主要出现在内蒙古及其邻近省份，但云南、广东和西藏也开始出现的时空聚集区。中国人间布鲁氏菌病疫情持续加重，报告发病率反弹，疫情涉及县（区）范围扩大。主要的时空聚集区位于内蒙古及周边地区。加强对疫情热点地区和重点人群的管理与投入势在必行。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.075

Epidemiological Evolution Profile ofHuman Brucellosis and Socio-Economic Factor Correlation Analysis — Southern andNorthern Areas, China, 1950–2021

Zhiguo Liu¹; MiaoWang²; Yue Shi³; Liping Wang³; Xiang Ren³;Zhenjun Li^3,#; Canjun Zheng^3,#

1. National Key Laboratory of Intelligent Tracking andForecasting for Infectious Diseases, National Institute for CommunicableDisease Control and Prevention, Chinese Center for Disease Control andPrevention, Beijing, China;

2. Ulanqab Center for Disease Control and Prevention,Jining City, Inner Mongolia Autonomous Region, China;

3. Chinese Center for Disease Control and Prevention,Beijing, China.

^# Correspondingauthors: Zhenjun Li, lizhenjun@icdc.cn; Canjun Zheng, zhengcj@chinacdc.cn.

Human brucellosis poses a serious public health concernin China, however, epidemiological evolution profileof human brucellosis in southernand northern remain unclear.The number of cases, incidence rate,geographic and temporal distribution, species/biovar pattern, and social factors wereanalyzed to illustrate the epidemiological change. There was 97.6% of casesconsistently located in the northern, is attributed to the tens of thousands oflivestock farming.  This underscores theneed to prioritize strengthening surveillance and control measures in thenorthern.  By contrast, only 2.4% ofcases were in the southern. These data indicate that controlling brucellosis inthe northern will help reduce the incidence in the southern.  There was an apparent shift from historicalmultiple species prevalence to the present dominance of a single species, Brucellamelitensis. Mutton price and production were closely correlated with numberof cases, implying that B. melitensis strains were accompanied by thesefactors co-driving the persistent epidemic of brucellosis and expanding fromthe northern toward the southern. The control and prevention of brucellosis inthe Northern have become extremely complex sociological issues. It is importantto draw attention to the worsening epidemic situation and to mobilize thenation's full strength to curb this trend.

人间布鲁氏菌病流行病学演化特征及社会经济因素相关性分析—南北方地区，中国，1950–2021年

刘志国¹；王妙²；师悦³；王丽萍³；任翔³；李振军^3,#；郑灿军^3,#

1. 传染病溯源预警与智能决策全国重点实验室，传染病预防控制所，中国疾病预防控制中心，北京，中国；

2. 乌兰察布市疾病预防控制中心，集宁市，内蒙古自治区，中国；

3. 中国疾病预防控制中心，北京，中国。

^# 通信作者：李振军，lizhenjun@icdc.cn；郑灿军，zhengcj@chinacdc.cn。

人间布鲁氏菌病已成为我国严峻的公共卫生问题，然而，我国北方地区人间布鲁氏菌病的流行病学演化趋势尚不明确。本文通过报告病例数、发病率、病例的地理、时间分布、布鲁氏菌的种型分布特征及经济社会因素相关性分析揭示我国南北方人间布鲁氏菌病的流行病学变化特征。由于北方地区广袤的草原生态和数以万计的家畜养殖，导致人间布鲁氏菌病发病率居高不下，至少97.60%的病例集中在北方。因此，应优先加强北方地区人间布鲁氏菌病的监测和防控。相反，南方地区的病例仅占2.40%。这些数据表明，控制北方的布病将有助于降低南方地区布病的发病率。随着疫情的演化，流行的布鲁氏菌由历史的多种型驱动转变为当前单一羊种布鲁氏菌主导传播。羊肉价格及其产量与人间布鲁氏菌病的流行程度密切相关。羊种布鲁氏菌协同羊肉价格及其产量等经济社会因素共同驱动我国人间布鲁氏菌病持续流行，并由北向南扩散。人间布鲁氏菌病在我国北方已成为极为复杂的经济社会问题，持续恶化的疫情形势值得高度关注，并呼吁动员全社会的力量共同遏制疫情蔓延。

For more information:https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.076

Epidemic Characteristics ofSchistosomiasis — China, 2016–2023

LijuanZhang¹; Shizhen Li¹, Jing Xu^1,2; Chunli Cao¹;Shizhu Li^1,2,#

1.National Key Laboratory of Intelligent Tracking and Forecasting for InfectiousDiseases, Key Laboratory on Parasite and Vector Biology, Ministry of Health,WHO Centre for Tropical Diseases, National Center for International Research onTropical Diseases, Ministry of Science and Technology, National Institute ofParasitic Diseases, Chinese Center for Disease Control and Prevention (ChineseCenter for Tropical Diseases Research), Shanghai, China;

2.School of Global Health, Chinese Center for TropicalDiseases Research-Shanghai Jiao Tong University School of Medicine,Shanghai, China.

^# Corresponding author:Shizhu Li, lisz@chinacdc.cn.

TheChinese government has established targets for elimination of schistosomiasisin all endemic counties by 2028. This study aimed to analyze theepidemiological characteristics of schistosomiasis in China after transmissioncontrol and provide theoretical basis for achieving the county-levelelimination goal by 2028. Provincial and county-level data on human infection,cattle reservoirs and Oncomelaniahupensis snail vector distribution were collected from 2016 to 2023, toanalyze the trend of schistosomiasis epidemic situation and serologicalpositive rate. And Joinpoint regression analysis was employed to analyzeseropositive rate trends. The number of schistosomiasis cases decreased by49.00%, from 54,454 in 2016 to 27,772 in 2023. The 8-year average seropositiverate across provincial-level administrative divisions (PLADs) was 1.80%, withthe highest rates observed in Yunnan (2.99%), Jiangxi (2.84%), and Hunan(2.67%) PLADs. Joinpoint analysis revealed a consistent decline in seropositiverates since 2016 and a significant inflection point was identified in 2021,indicating an acceleration in the rate of decline. And no positive cattle havebeen detected since 2020. The total area of snail habitats exhibited a slightrebound from 356,835 square hectometers (hm²) in 2016 to 367,702 hm²in 2023, with new habitats emerging annually, totaling 4,080 hm² ofnewly identified habitats. Development of highly sensitive and specificdiagnostic tools is essential, alongside intensified surveillance of wildanimal reservoirs and high-risk snail habitats, to achieve the goal ofeliminating schistosomiasis by 2030.

血吸虫病流行特征— 中国，2016–2023年

张利娟¹；李仕祯¹；许静^1,2；曹淳力¹；李石柱^1,2,#

1. 传染病溯源预警与智能决策全国重点实验室，国家卫生健康委员会寄生虫病原与媒介生物学重点实验室，世界卫生组织热带病合作中心，科技部国家级热带病国际联合研究中心，寄生虫病预防控制所（国家热带病研究中心），中国疾病预防控制中心，上海，中国；

2. 全球健康学院，上海交通大学医学院-国家热带病研究中心，上海，中国。

^# 通信作者：李石柱，lisz@chinacdc.cn。

我国血吸虫病防治工作设定了2028年全国以县为单位达消除标准的目标。本文分析了我国传播控制以来（2016-2023年）血吸虫病流行特征，为实现2028年以县为单位消除目标提供理论依据。通过收集2016-2023年省级及县级人畜血吸虫病查病以及钉螺调查数据，分析疫情变化趋势及血清学阳性率变化趋势，并采用Joinpoint回归分析全国及未消除各省份血清学阳性率变化趋势。结果显示全国血吸虫病病人数由2016年的54,454下降至2023年的27,772,下降49%。8年间全国平均血检阳性率为1.8%，其中排在前三位的省份分别为云南省2.99%，江西省2.84%和湖南省2.67%。Joinpoint分析结果显示2016年以来全国人群血检阳性率呈持续下降趋势，并在2021年出现加速下降。自2020年以来全国未发现阳性耕牛。钉螺面积小幅反弹，由2016年的356,835hm²升至2023年的367,702hm²，8年间新发现钉螺面积4,080hm²。提示需加强敏感有效诊断工具的开发，加强对野生动物在血吸虫病传播中的作用监测以及对高风险有螺区域的监测，以推动2030年全国实现血吸虫病消除目标。

For more information:https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.077

A Novel Matching Pursuit ModelingStrategy Based on Adaptive Fourier Decomposition Theory for PredictingAntigenic Variation of Influenza A (H1N1)

Wei Qu^1,2,&; Ruihan Chen^3,&;Yang Wang^1,3,4; Zhiqi Zeng^5,6,7; Cheng Gao⁸;Weiqi Pan^1,9; Tao Qian^10,#; Chitin Hon^3,9,#;Zifeng Yang^1,4,#

1. State Key Laboratory of RespiratoryDisease, National Clinical Research Center for Respiratory Disease, GuangzhouInstitute of Respiratory Health, The First Affiliated Hospital of Guangzhou MedicalUniversity, Guangzhou City, Guangdong Province, China;

2. College of Sciences, China JiliangUniversity, Hangzhou City, Zhejiang Province, China;

3. Department of Engineering Science,Faculty of Innovation Engineering, Macau University of Science and Technology,Macau Special Administrative Region, China;

4. Guangzhou National Laboratory, GuangzhouCity, Guangdong Province, China;

5. Guangzhou key laboratory for clinicalrapid diagnosis and early warning of infectious diseases, KingMed School of LaboratoryMedicine, Guangzhou Medical University, Guangzhou City, Guangdong Province,China;

6. Engineering Technology Research Centerof Intelligent Diagnosis for Infectious Diseases in Guangdong Province,Guangzhou City Guangdong Province, China;

7. Guangdong Provincial Engineering ResearchCenter for Early Warning and Diagnosis of Respiratory Infectious Diseases,Guangzhou City, Guangdong Province, China;

8. Department of Electrical Engineering& Computer Science, College of Engineering, University of Missouri,Columbia, MO, USA;

9. Respiratory Disease AI Laboratory onEpidemic and Medical Big Data Instrument Applications, Faculty of InnovationEngineering, Macau University of Science and Technology, Macau SpecialAdministrative Region, China;

10. Macau Center for Mathematical Sciences,Macao University of Science and Technology, Macau Special AdministrativeRegion, China.

^&Joint first authors.

^# Corresponding author: Tao Qian, tqian@must.edu.mo; Chitin Hon, cthon@must.edu.mo; Zifeng Yang,yang_zifeng@gzlab.ac.cn.

Seasonal influenza poses a significantpublic health burden, causing substantial morbidity and mortality worldwideeach year. In this context, timely and accurate vaccine strain selection is criticalto mitigating the impact of influenza outbreaks. This article aims to developan adaptive, universal, and convenient method for predicting antigenicvariation in influenza A(H1N1), thereby providing a scientific basis to enhancethe biannual influenza vaccine selection process. The study integrates adaptiveFourier decomposition (AFD) theory with multiple techniques — includingmatching pursuit, the maximum selection principle, and bootstrapping — toinvestigate the complex nonlinear interactions between amino acid substitutionsin hemagglutinin (HA) proteins (the primary antigenic protein of influenzavirus) and their impact on antigenic changes. Through comparative analysis withclassical methods such as Lasso, Ridge, and random forest, we demonstrate thatthe AFD-type method offers superior accuracy and computational efficiency inidentifying antigenic change-associated amino acid substitutions, thuseliminating the need for time-consuming and expensive experimental procedures.In summary, AFD-based methods represent effective mathematical models forpredicting antigenic variations based on HA sequences and serological data,functioning as ensemble algorithms with guaranteed convergence.

一种基于自适应傅里叶分解理论的新型匹配追踪建模策略用于预测甲型流感病毒（H1N1）的抗原变异

曲伟^1,2,&；陈瑞晗^3,&；王洋^1,3,4；曾志奇^5,6,7；高成⁸；潘蔚琦^1,9；钱涛^10,#；韩子天^3,9,#；杨子峰^1,4,#

1. 呼吸疾病国家重点实验室，国家呼吸系统疾病临床医学研究中心，广州呼吸健康研究院，广州医科大学附属第一医院，广州市，广东省，中国；

2. 理学院，中国计量大学，杭州市，浙江省，中国；

3.工程科学系，创新工程学院，澳门科技大学，澳门特别行政区，中国；

4. 广州实验室，广州市，广东省，中国；

5. 广州市传染病临床快速诊断与预警重点实验室，金医检验学院，广州医科大学，广州市，广东省，中国；

6. 广东省感染性疾病智能化诊断技术工程研究中心，广州市，广东省，中国；

7. 广东省呼吸感染疾病预警和诊断工程技术研究中心，广州市，广东省，中国；

8. 工程学院电气工程与计算机科学系，密苏里大学，哥伦比亚市，密苏里州，美国；

9. 大规模呼吸疾病流行病预测预警与医学大数据人工智能应用实验室，创新工程学院，澳门科技大学，澳门特别行政区，中国；

10. 澳门数学研究中心，澳门科技大学，澳门特别行政区，中国。

^&共同第一作者。

^# 通讯作者:钱涛，tqian@must.edu.mo；韩子天，cthon@must.edu.mo；杨子峰，yang_zifeng@gzlab.ac.cn。

季节性流感对公共卫生造成了重大疾病负担，每年在全球范围内的发病率和死亡率居高不下。在此背景下，及时且精准地筛选出每年的疫苗株，对于减轻季节性流感所带来的广泛影响具有至关重要的意义。本文旨在开发一种适应性强、通用性强、更便捷的方法来预测甲型H1N1流感的抗原变异，从而来为流感疫苗选择过程提供科学依据。本研究将自适应傅里叶分解（AFD）理论与多种算法相结合，包括匹配追踪、极大选择原理和自助法，从而来研究流感病毒的主要抗原蛋白（血凝素蛋白，HA）中氨基酸替换之间的复杂非线性关系及其对抗原变化的影响。通过与Lasso、Ridge和随机森林等经典方法的比较分析，本研究证明AFD方法在识别抗原变化相关的氨基酸替换方面具有更高的准确性和计算效率，因此，减少了对耗时且成本高昂的实验流程的需求。综上所述，基于AFD的方法构成了有效的数学模型，能够依据血凝素（HA）序列和血清学数据预测抗原变异，并作为具有保证收敛性的集成算法发挥作用。

For more information:https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.078

Development of A Novel EvaGreen-DyeBased Recombinase Aided Amplification Assay Using Self-Avoiding MolecularRecognition System Primers

Xinxin Shen¹;Shaowei Hua¹; Zijin Zhao¹; Fengyu Tian¹; Lingjun Li^2,#;Xuejun Ma^1,#

1. National Key Laboratory ofIntelligent Tracking and Forecasting for Infectious Diseases, NHC KeyLaboratory of Medical Virology and Viral Diseases, National Institute for ViralDisease Control and Prevention, Chinese Center for Disease Control andPrevention, Beijing, China;

2. State Key Laboratory ofAntiviral Drugs, NMPA Key Laboratory for Research and Evaluation of InnovativeDrug, Pingyuan Laboratory, School of Chemistry and Chemical Engineering, HenanNormal University, Xinxiang City, Henan Province, China.

^# Correspondingauthors: Xuejun Ma, maxj@ivdc.chinacdc.cn; Lingjun Li, lingjunlee@htu.edu.cn.

Fluorescent probe-basedrecombinase aided amplification recombinase-aided amplification(RAA) offers the advantages of rapidity and simplicity but is limited by therequirement for complex and lengthy probe design, restricting its widespreadapplication.A novel EvaGreen dye-based RAA (EvaGreen-RAA) assayutilizing self-avoiding molecular recognition system (SAMRS) primers wasdeveloped for the detection of Pseudomonasfluorescens (PF) and Bacillus cereus(BC) in milk. Conventional RAA was used as a reference method. Sensitivity wasevaluated using nucleic acids from recombinant plasmids and simulated milkspecimens. Additionally, a dual EvaGreen-RAA assay was investigated forsimultaneous detection of mixed BC and PF in simulated milk specimens.TheEvaGreen-RAA demonstrated superior sensitivity compared to conventional RAA,with detection limits of 1 copy/µL versus 10 copies/µL for both BC and PFplasmids, respectively. In simulated milk specimens, EvaGreen-RAA detected BCand PF at concentrations of 100 CFU/mL and 200 CFU/mL, respectively, comparedto 400 CFU/mL and 600 CFU/mL for conventional RAA. The dual EvaGreen-RAA assaysuccessfully detected mixed BC and PF in simulated milk specimens atconcentrations of 200CFU/mL for each pathogen.The EvaGreen-RAAassay demonstrated significant advantages in terms of simplicity and enhancedsensitivity compared to fluorescent probe-based RAA, offering a novel approachfor developing multiplex pathogen detection systems using melting curveanalysis.

一种基于EvaGreen染料和自避免分子识别系统引物的重组酶辅助扩增方法的建立

申辛欣¹；滑少为¹；赵子今¹；田丰雨¹；李凌君^2,#；马学军^1,#

1. 传染病溯源预警与智能决策全国重点实验室，国家卫生健康委员会病毒学与病毒性疾病重点实验室，病毒病预防控制所，中国疾病预防控制中心，北京，中国；

2. 抗病毒药物国家重点实验室，平原实验室，化学和化学工程学院，河南师范大学，新乡市，河南省，中国。

^# 通信作者：马学军，maxj@ivdc.chinacdc.cn；李凌君，lingjunlee@htu.edu.cn。

荧光探针重组酶辅助扩增（RAA）具有快速和简便的优点，但由于其复杂的长探针设计，限制了其广泛应用。研究了一种基于EvaGreen染料的RAA（EvaGreen-RAA）检测方法，该方法使用自避免分子识别系统（SAMRS）引物来检测牛奶中的荧光假单胞菌（PF）和蜡样芽孢杆菌（BC）。作为对照，RAA进行了比较。使用重组质粒和模拟牛奶样本中的核酸来评估两种检测方法的灵敏度。探索了用于检测模拟牛奶样本中混合BC和PF的双重EvaGreen-RAA检测方法。RAA检测BC和PF质粒的灵敏度为10拷贝/µL，而EvaGreen-RAA的灵敏度为1拷贝/µL。RAA检测BC和PF模拟牛奶样本的灵敏度分别为400 CFU/mL和600 CFU/mL，而EvaGreen-RAA的灵敏度分别为100 CFU/mL和200 CFU/mL。双重EvaGreen-RAA检测BC和PF混合模拟牛奶样本的病原体浓度均为200 CFU/mL。EvaGreen-RAA检测方法展示了比荧光探针RAA更简单且灵敏度更高的优势，为开发基于熔解曲线的RAA检测多种病原体提供了新策略。

For more information:https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.079