Surveillance and Analysis of Plague Epidemic — China, 2010–2024

Qi Bing^1,&, Shaoxian Zhang^1,&, Zhao Wang¹, Cheng Ju¹, Shiwen Zhang¹, Na Ma¹, Bin Zhao¹, Xiaoheng Yao¹, Cheng Xu¹, Kuidong Shao^1,#

1. Plague and Brucellosis Prevention and Control Base, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Baicheng City, Jilin Province, China.

^& Joint first authors.

^# Corresponding author: Kuidong Shao, shaokuidong001@163.com.

To analyze the national plague surveillance data from 2010 to 2024 and provide evidence for plague prevention and control. Data on human and animal plague epidemics were collected from the National Plague Prevention and Control Management Information System and analyzed using descriptive epidemiological methods. As of 2024, 12 types of natural plague foci have been identified in China. Between 2010 and 2024, 33 human plague cases and 14 deaths were reported nationwide. Geographically, cases were concentrated in Inner Mongolia (15, 45.5%), Xizang (8, 24.2%), and Gansu (6, 18.2%). By focus type, cases originated primarily from Marmota himalayana (16, 48.5%), Meriones unguiculatus (15, 45.5%), and Rattus flavipectus (2, 6.1%). Pneumonic plague was most common (15, 45.5%), followed by bubonic (10,30.3%), septicemic (7, 21.2%), and intestinal plague (1, 3.0%). Animal plague epidemics persisted nationwide, with active outbreaks in foci of M. himalayana, Marmota baibacina, Spermophilus undulatus, and Meriones unguiculatus. Bacterial isolation positivity rates in animals and insects were 0.05%–0.13% and 0.04%–0.11%, respectively, while Indirect Hemagglutination Assay (IHA) and Reverse Indirect Hemagglutination Assay (RIHA) positivity rates were 0.08%–0.25% and 0.09%–2.18%, respectively. Currently, Polymerase Chain Reaction (PCR) testing has been implemented in some regions, with positivity rates of 0.80% in animals and 1.59% in insects in 2024. The current plague epidemic situation in China is characterized by "sporadic human cases, active animal epidemics in some foci." It is recommended to strengthen targeted surveillance, promote PCR-based screening, and enhance cross-provincial coordination.

鼠疫疫情监测与分析 — 中国，2010–2024年

邴琪^1,&，张少先^1,&, 王照¹，鞠成¹，张诗文¹，马娜¹，赵斌¹，姚晓恒¹，徐成¹，邵奎东^1,#

1. 鼠疫布氏菌病预防控制基地，中国疾病预防控制中心（中国预防医学科学院），白城市，吉林省，中国。

^& 共同第一作者

^# 通信作者: 邵奎东, shaokuidong001@163.com。

文章通过分析2010–2024年全国鼠疫监测数据，为防控提供依据。研究从“鼠疫防治管理信息系统”中收集人间及动物间疫情监测数据，采用描述性流行病学方法进行分析。截至2024年，我国现有12类鼠疫自然疫源地。期间累计报告人间病例33例，死亡14例。病例集中于内蒙古（15例，45.5%）、西藏（8例，24.2%）、甘肃（6例，18.2%），主要分布于喜马拉雅旱獭（16例，48.5%）、长爪沙鼠（15例，45.5%）及黄胸鼠（2例，6.1%）疫源地。临床分型以肺鼠疫为主（15例，45.5%），其次为腺鼠疫（10例，30.3%）、败血型（7例，21.2%）和肠型（1例，3.0%）。动物疫情在喜马拉雅旱獭、灰旱獭-长尾黄鼠及长爪沙鼠疫源地持续活跃。病原学阳性率动物0.05%–0.13%、昆虫0.04%–0.11%，免疫学阳性率IHA 0.08%–0.25%、RIHA 0.09%–2.18%。2024年动物与昆虫PCR阳性率分别为0.80%和1.59%。鼠疫疫情呈“人间散发、部分疫源地动物疫情活跃”态势。建议强化精准监测、推进PCR筛查、提升跨省协同能力。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.074

Genetic Analysis of Coxsackievirus A4 Among Healthy Children — Xizang Autonomous Region, 1996–2024

Kaitao Xiao^1,2,&; Mei Hong^3,&; Mengyi Xiao^1,2; Fan Li⁴; Kexin Shao^1,2; Chenglin Zhu^1,2; Lan Yang²; Jie Lin²; Qin Wang³; Cidan Zhuoga³; Shuangli Zhu²; Dongmei Yan²; Yong Zhang²; Xiaomei Li^1,#; Jinbo Xiao^2,#

1. School of Public Health and Health Management, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan City, Shandong Province, China;

2. National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Laboratory for Poliomyelitis, WHO WPRO Regional Polio Reference Laboratory, National Health Commission Key Laboratory of Microbial Genomics, National Health Commission Key Laboratory for Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

3. Department of Microbiological Testing, Xizang Autonomous Region Center for Disease Control and Prevention, Lhasa City, Xizang Autonomous Region, China;

4. National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.

^& Joint first authors.

^# Corresponding author: Jinbo Xiao, xiaojb@ivdc.chinacdc.cn; Xiaomei Li, xmli@sdfmu.edu.cn.

Coxsackievirus A4 (CVA4) causes several diseases, including hand, foot, and mouth disease (HFMD) and herpangina. This study analyzed CVA4 isolates collected between 1996 and 2024 from the Xizang Autonomous Region to elucidate the phylogenetic characteristics and epidemiological patterns of this virus in high-altitude regions. VP1 coding region sequences of CVA4 were obtained through virus isolation and Sanger sequencing. MEGA software was used to construct a maximum likelihood phylogenetic tree based on the VP1 region. The BEAST toolkit was used to generate a maximum clade credibility tree and perform phylogeographic analysis. From 2018 onwards, the prevalence of CVA4 among healthy carriers increased significantly, accounting for 62.12% of all detections. Genotyping revealed that most isolates belonged to genotype C, while the remainder were classified as D2. As the dominant genotype, genotype C has spread outward from Xigaze and Lhasa since 2011, leading to multiple asymptomatic infections in Shannan (2020), Xigaze and Lhasa (2023), and Ngari Prefecture (2024). Transmission of CVA4 genotype C among healthy children in high-altitude areas suggests strong environmental adaptability, highlighting the need to strengthen enterovirus surveillance and control, including targeted monitoring of CVA4, in these regions.

健康儿童中柯萨奇病毒A组4型的基因特征分析 — 西藏自治区，中国，1996–2024年

肖凯涛^1,2,&，红梅^3,&，肖梦怡^1,2，栗凡⁴，邵珂欣^1,2，朱成林^1,2，杨澜²，林婕²，王琴³，次旦卓嘎³，祝双利²，严冬梅²，张勇²，李晓梅^1,#，肖金波^2,#

1. 公共卫生与健康管理学院，山东第一医科大学（山东省医学科学院），济南市，山东省，中国;

2.传染病溯源预警与智能决策全国重点实验室（NITFID），国家脊髓灰质炎实验室、世界卫生组织西太平洋地区脊髓灰质炎参比实验室，国家卫生健康委员会微生物基因组重点实验室、国家卫生健康委员会实验室生物安全重点实验室，病毒病预防控制所，中国疾病预防控制中心（中国预防医学科学院），北京，中国;

3. 微生物检验所，西藏自治区疾病预防控制中心，拉萨市，西藏自治区，中国;

4. 传染病预防控制所，中国疾病预防控制中心（中国预防医学科学院），北京，中国。

^& 共同第一作者。

^# 通信作者：肖金波, xiaojb@ivdc.chinacdc.cn; 李晓梅, xmli@sdfmu.edu.cn。

柯萨奇病毒A组4型（CVA4）可引起手足口病（HFMD）、疱疹性咽峡炎等多种疾病。本研究对1996—2024年西藏自治区分离的CVA4毒株进行分析，以阐明该病毒在高海拔地区的系统进化特征及流行病学流行情况。通过病毒分离与Sanger测序获得CVA4的VP1编码区序列。使用MEGA软件基于VP1区构建CVA4最大似然树，进行系统发育分析。使用BEAST软件包构建CVA4最大类群置信树并进行系统地理分析。自2018年起，CVA4在健康携带者中的流行率显著上升，占总检出数的62.12%。基因分型结果显示，绝大多数分离株属于C基因型，其余为D2型。C基因型作为优势基因型自2011年起从日喀则、拉萨向外扩散，并在山南市（2020年）、日喀则市与拉萨市（2023年）及阿里地区（2024年）出现多起无症状感染病例。高海拔地区中C基因型的CVA4在健康儿童中的传播表明该病毒具有较强的环境适应性，这提示需加强该地区包括CVA4在内的肠道病毒监测与防控工作。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.076

Epidemiological Characteristics and Transmissibility of Human Immunodeficiency Virus — Fujian Province, China, 1987–2024

Mingya Zhang^1,&; Yanshu Ke^2,&; Yue He^3,&; Qiaoling Lian¹; Chunyang Zhang¹; Shaobin Wu¹; Zhenghua Wang¹; Xiaoli Lu¹; Meirong Xie¹; Shouli Wu¹; Jianfeng Xie¹; Zeyu Zhao²; Jia Rui⁴; Tianmu Chen²; Yuefeng Qiu^1,#
1. Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fujian Provincial Academy of Preventive Medicine Fuzhou City, Fujian Province, China;

2. State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen City, Fujian Province, China;

3. State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen City, Fujian Province, China;

4. Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha City, Hunan Province, China.

^& Joint first authors.

^# Corresponding authors: Yuefeng Qiu, qiuyuefeng@fjcdc.com.cn.

Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) remains a global public health threat, with distinct regional patterns across China. In this study, we examined the unique epidemic characteristics of Fujian Province to assess HIV transmission dynamics, evaluate progress toward the "95-95-95" targets, and optimize local prevention strategies. HIV/AIDS surveillance data from Fujian Province spanning 1987-2024 were collected to analyze epidemiological characteristics and develop a comprehensive transmission dynamics model. Using the next-generation matrix method, we estimated the effective reproduction number (R_eff) to assess transmissibility. By integrating spatiotemporal distribution analysis with evaluation of progress toward the 95-95-95 targets, we assessed epidemic trends and intervention effectiveness. The HIV/AIDS epidemic in Fujian Province showed an initial increase followed by gradual stabilization, with notable spatiotemporal heterogeneity. High-risk populations included males (81.86%) and individuals aged 20–70 years (89.21%). Although treatment coverage and viral suppression achieved the 95% targets, diagnostic coverage (86.30%) remained suboptimal. Model estimates revealed that R_eff declined from 2–5 during 2009–2019 to below 1 after 2020, but rebounded to 1.03 by 2024. Although HIV transmission in Fujian Province has stabilized, the persistent diagnostic gap and rebound in transmissibility in 2024 indicate potential resurgence risks. Future interventions should prioritize middle-aged and older adults, and enhanced case identification strategies are essential to support achievement of the 2030 HIV elimination targets.

HIV/AIDS疫情流行特征与传播能力研究 — 福建省，中国，1987–2024年

张明雅^1,&，柯妍姝^2,&，和越^3,&，连巧龄¹，张春阳¹，吴韶彬¹，王征桦¹，卢晓丽¹，谢美榕¹，吴守丽¹，谢剑锋¹，赵泽宇²，芮佳⁴，陈田木²，邱月锋^1,#

1. 福建省疾病预防控制中心，福建省人畜共患病重点实验室，福建省预防医学科学院，福州市，福建省，中国；

2. 分子疫苗学和分子诊断学国家重点实验室,国家医学攻关产教融合创新平台，厦门大学，厦门市，福建省，中国；

3. 传染病疫苗研发全国重点实验室,翔安创新实验室，厦门大学公共卫生学院，厦门市，福建省，中国；

4. 中南大学湘雅公共卫生学院流行病与卫生统计学系，长沙市，湖南省，中国。

^& 共同第一作者。

^# 通信作者：邱月锋, qiuyuefeng@fjcdc.com.cn。

人类免疫缺陷病毒（HIV）/获得性免疫缺陷综合征（AIDS）仍是全球重大公共卫生威胁，中国各地区流行模式存在显著差异。本研究旨在分析福建省HIV/AIDS流行特征，评估传播动力学变化，评价"95-95-95"目标进展，并为优化本地防控策略提供依据。收集福建省1987–2024年HIV/AIDS监测数据，分析流行病学特征并构建综合传播动力学模型。采用下一代矩阵法估算有效再生数（R^eff）以评估传播能力。结合时空分布分析与95-95-95目标进展评价，综合研判疫情趋势及干预措施效果。福建省HIV/AIDS疫情呈先上升后逐步平稳态势，存在显著时空异质性。高危人群以男性（81.86%）和20-70岁年龄组（89.21%）为主。尽管治疗覆盖率及病毒抑制率已达95%目标，诊断覆盖率（86.30%）仍存差距。模型估算显示，R^eff由2009–2019年的2-5降至2020年后的低于1，但2024年回升至1.03。福建省HIV传播虽总体趋稳，但诊断覆盖不足及2024年传播力反弹提示疫情复燃风险。未来防控应重点关注中老年人群，强化病例发现策略，以助力实现2030年HIV消除目标。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.077

Time to Antiretroviral Therapy Initiation After HIV Diagnosis in the Integrase Strand Transfer Inhibitor Era — Nanjing City, Jiangsu Province, China, 2021–2024

Chenyu Ma¹, Jinjin Yang¹, Anni Liu², Zheng Qian², Ziyao Liu¹, You Ge², Yuanyuan Xu³, Zhengping Zhu³, Hongxia Wei², Zhihang Peng^4,#, Guoping Yin^1,#, Zhiliang Hu^2,5,#

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

2. Department of Infectious Diseases, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing City, Jiangsu Province, China；

3. Department of AIDS/STD Control and Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China;

4. National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

5. Center for Global Health, School of Public Health, Nanjing Medical Univrsity, Nanjing City, Jiangsu Province, China.

^# Corresponding authors: Zhiliang Hu, huzhiliang@njucm.edu.cn; Guoping Yin, yinguoping0304@163.com; Zhihang Peng, pengzh@chinacdc.cn.

In China, newly diagnosed people living with HIV are referred from CDC confirmation to designated hospitals for antiretroviral therapy (ART), and treatment delays may occur across this referral pathway. Using a real-world cohort of 1,456 adults diagnosed between 2021 and 2024 in Nanjing, this study disentangled and quantified the contributions of the pre-hospital interval (from diagnosis to the first hospital visit; T_PreHOS) and the post-hospital interval (from the first hospital visit to ART initiation; T_PostHOS) to overall treatment delay (from diagnosis to ART initiation; T_total). Among the 1,456 patients analyzed, all three intervals showed substantial year-to-year reductions. The median T_total decreased from 20 to 9 days, driven by reductions in T_PreHOS (12 to 7 days) and T_PostHOS (7 to 0 days). In 2024, 37% initiated ART within 7 days of diagnosis, 49.8% attended the hospital within 7 days of HIV confirmation, and 87.9% initiated ART within 7 days of their first hospital visit. Notably, 56.3% started ART at their initial visit. However, T_PreHOS remains the principal bottleneck, with over half of patients not attending care within 7 days of diagnosis. Younger age was associated with delayed hospital attendance. INSTI-based regimens were independently associated with faster ART initiation. These findings highlight that strengthening linkage from CDC confirmation to hospital care is now the critical step for achieving rapid ART initiation and accelerating progress toward the 95–95–95 targets.

整合酶链转移抑制剂时代 HIV 确诊后启动抗反转录病毒治疗的时间 — 南京市，江苏省，中国，2021–2024年

马晨雨¹；杨金金¹；刘安妮²；钱正²；刘子瑶¹；葛尤²；徐园园³；朱正平³；魏洪霞²；彭志行^4,#；殷国平^1,#；胡志亮^2,5,#

1. 公共卫生学院，南京医科大学，南京市，江苏省，中国；

2. 传染病部，南京中医药大学附属南京市第二医院，南京市，江苏省，中国；

3. 艾滋病性病防制科，南京市疾病预防控制中心，南京市，江苏省，中国；

4. 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（中国预防医学科学院），北京，中国；

5. 全球健康中心，公共卫生学院，南京医科大学，南京市，江苏省，中国。

^# 通信作者：胡志亮，huzhiliang@njucm.edu.cn；殷国平，yinguoping0304@163.com;彭志行，pengzh@chinacdc.cn。

在我国，HIV感染者确诊后需经疾控机构转介至定点医院接受抗反转录病毒治疗，诊断至治疗启动的延迟仍然存在。本研究基于南京市2021–2024年1456例新诊断的成人HIV感染者队列，系统分解并量化了院前间隔（从确诊至首次医院就诊; T_PreHOS）与院后间隔（从首次医院就诊至ART启动; T_PostHOS）两个阶段对总体治疗延迟（从确诊至ART启动；T_total）的贡献。在纳入分析的 1456 例患者中，三个时间间隔均呈逐年显著缩短。总间隔时间（T_total）的中位数从20天降至9天，主要由院前间隔（12天降至7天）和院后间隔（7天降至0天）的缩短所驱动。2024年，37%的患者在确诊后7天内启动 ART，49.8%在HIV确诊后7天内到院就诊，87.9%在首次医院就诊后7天内启动治疗。值得关注的是，56.3%的患者在首次就诊时即启动 ART。然而，院前间隔（T_PreHOS）仍是主要瓶颈，仍有超过半数患者未能在确诊后7天内就诊。年龄较小与就诊延迟相关；基于整合酶链转移抑制剂（INSTI）的治疗方案与更快启动 ART 独立相关。研究提示，在整合酶抑制剂时代，进一步缩短治疗延迟的关键在于强化疾控中心与定点医院之间的衔接机制，优化转诊流程与患者支持服务，从而实现快速治疗目标，加速推进95–95–95防控进程。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.078

Development of a Subsequence Correlation Coefficient Feature Vector Method for High-Resolution HIV-1 Subtype Classification — China, 2004–2022

Shuyan Han^1.&, Lily He^1,&, Yihang Tang², Kun Peter Li³, Yuhua Ruan⁴, Hengjian Cui ^5,#

1. School of Science, Beijing University of Civil Engineering and Architecture, Beijing, China;

2. School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China;

3. Department of Mathematical Sciences, Tsinghua University, Beijing, China;

4. National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

5. School of Mathematical Sciences, Capital Normal University, Beijing, China.

^& Joint first authors.

^# Corresponding author: Hengjian Cui, hjcui@bnu.edu.cn.

Current HIV-1 subtyping tools are predominantly trained on Western B‑subtype data, limiting their accuracy for non‑B strains prevalent in China. This study developed an alignment‑free method—the Subsequence Correlation Coefficient Feature Vector (SCCFV)—that captures nucleotide spatial distribution and correlation within sequences. Combined with Regularized Discriminant Analysis (RDA), the model was tailored specifically for Chinese HIV‑1 strains using 55,261 pol sequences from the China CDC (2004–2022). On an independent test set of 13,816 sequences, SCCFV‑RDA achieved 99.7% overall accuracy. For China’s dominant CRF07_BC and CRF08_BC strains, recall rates reached 99.82% and 99.91%, respectively—dramatically outperforming HIVdb (60.0%, 78.7%) and COMET (54.6%, 95.5%). Validation on 821 Chinese full‑genome sequences yielded 100% accuracy across all subtypes. The method also demonstrated strong generalizability on international datasets covering 10 gene regions, with accuracy exceeding 99.85%. This work provides China with a rapid, locally adapted subtyping tool that supports large‑scale molecular surveillance and enables construction of a reusable feature vector database for all circulating strains.

HIV-1 高分辨率亚型分类的子序列相关系数特征向量（SCCFV）方法建立 — 中国，2004–2022年

韩书岩^1,&，何黎黎^1,&，汤一航²，Kun Peter Li ³，阮玉华⁴，崔恒建^5,#
1. 理学院，北京建筑工程学院，北京，中国；
2. 智能科学与技术学院，北京建筑工程学院，北京，中国；
3. 数学科学系，清华大学，北京，中国；
4. 传染病预防控制国家重点实验室，性病艾滋病预防控制中心，中国疾病预防控制中心（中国预防医学科学院），北京，中国；
5. 数学科学学院，首都师范大学，北京，中国。

^& 共同第一作者。

^# 通信作者：崔恒建，hjcui@bnu.edu.cn。

当前HIV-1亚型分型工具多基于欧美B亚型数据训练，对中国广泛流行的非B亚型毒株识别能力有限。本研究建立了一种无需序列比对的新方法——子序列相关系数特征向量，该技术可有效捕获核苷酸在序列中的空间分布及相关性特征。联合正则化判别分析分类器，本研究利用中国疾控中心2004–2022年采集的55,261条pol序列，构建了针对中国HIV-1流行株的专用分型模型。在13,816条序列的独立测试集中，SCCFV-RDA模型总体准确率达99.7%。对于我国主要流行株CRF07_BC和CRF08_BC，模型召回率分别高达99.82%和99.91%，显著优于HIVdb（60.0%、78.7%）及COMET（54.6%、95.5%）。在821条中国全基因组序列的验证中，模型对所有亚型分类准确率均达100%。此外，在覆盖10个基因区域的国际数据集上，该模型准确率均超过99.85%，展现出强大的泛化能力。本研究为中国HIV分子流行病学监测提供了快速、本土化的分型工具，并为构建全国流行毒株特征向量数据库奠定了技术基础。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.080