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Han L, Zhang Y, Jin X, Ren H, Teng Z, Sun Z, Xu J, Qin T. Changing epidemiologic patterns of typhus group rickettsiosis and scrub typhus in China, 1950-2022. Int J Infect Dis 2024; 140:52-61. [PMID: 38163619 DOI: 10.1016/j.ijid.2023.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/22/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
OBJECTIVES We conducted a systematic analysis of the notifiable rickettsial diseases in humans in China during 1950-2022. METHODS We utilized descriptive statistics to analyze the epidemiological characteristics, clinical manifestations, and diagnostic characteristics of typhus group rickettsiosis (TGR) and scrub typhus (ST) cases. RESULTS Since the 1950s, there have been variations in the incidence rate of TGR and ST in China, with a downtrend for TGR and an uptrend for ST. The South became a high-incidence area of TGR, whereas the North was previously the high-incidence area. ST cases were concentrated in the South and the geographic area of ST spread northward and westward. The seasonality of TGR and ST were similar in the South but distinct in the North. Most TGR and ST cases were reported by county-level medical institutions, whereas primary institutions reported the least. Delayed diagnosis was associated with fatal outcomes of TGR and ST. Cases in low-incidence provinces, confirmed by laboratory tests and reported from county/municipal-level institutions had higher odds of delayed diagnoses. CONCLUSIONS Our study revealed significant changes in the epidemiological characteristics of TGR and ST in China, which can provide useful information to enhance the control and prevention strategies of rickettsial diseases in China.
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Affiliation(s)
- Ling Han
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yunfei Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaojing Jin
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongyu Ren
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhongqiu Teng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaobin Sun
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China
| | - Jianguo Xu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tian Qin
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
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Barbuddhe SS, Thorat YT, Kulkarni P, Shinde SV, Chaudhari SP, Kurkure NV, Sahu R, Rawool DB. Comparative analysis of diagnostic assays for scrub typhus: Unveiling enhanced approaches for accurate detection. J Microbiol Methods 2024; 216:106875. [PMID: 38101580 DOI: 10.1016/j.mimet.2023.106875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/11/2023] [Accepted: 12/11/2023] [Indexed: 12/17/2023]
Abstract
The study comparatively evaluated serological assays, namely, Weil Felix assay, and IgM ELISA with the gold-standard immunofluorescence test (IFAT) for the sensitive and specific serodiagnosis of scrub typhus infection in occupationally exposed groups of humans. A total of 78 serum samples collected from persons affected with various ailments and belonging to different risk groups were screened in the study. Out of the 78 serum samples tested, a total of 17, 26, and 47 samples turned out to be positive by IFAT, IgM ELISA, and Weil Felix test, respectively. The Weil Felix assay could not serve as an ideal test for screening scrub typhus infection owing to its poor sensitivity and specificity in comparison with IFAT. IgM-ELISA could be an initial screening test to detect scrub typhus suspected patient in limited resource settings.
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Affiliation(s)
- Shruti S Barbuddhe
- Maharashtra Animal and Fishery Sciences University, Nagpur 440006, India
| | - Yogesh T Thorat
- Maharashtra Animal and Fishery Sciences University, Nagpur 440006, India
| | - Piyush Kulkarni
- Maharashtra Animal and Fishery Sciences University, Nagpur 440006, India
| | - Shilpshri V Shinde
- Maharashtra Animal and Fishery Sciences University, Nagpur 440006, India
| | | | - Nitin V Kurkure
- Maharashtra Animal and Fishery Sciences University, Nagpur 440006, India
| | - Radhakrishna Sahu
- Odisha University of Agriculture and Technology, Bhubaneswar 751003, India
| | - Deepak B Rawool
- ICAR-National Meat Research Institute, Hyderabad 500092, India.
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Wang YC, Li JH, Qin Y, Qin SY, Chen C, Yang XB, Ma N, Dong MX, Lei CC, Yang X, Sun HT, Sun ZY, Jiang J. The Prevalence of Rodents Orientia tsutsugamushi in China During Two Decades: A Systematic Review and Meta-Analysis. Vector Borne Zoonotic Dis 2023; 23:619-633. [PMID: 37625029 DOI: 10.1089/vbz.2023.0057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2023] Open
Abstract
Background: Orientia tsutsugamushi is a zoonotic intracellular pathogen that requires parasitism in eukaryotic cells to reproduce. In recent years, tsutsugamushi disease reported in many places nationwide has crossed the Yangtze River, continuously, spreading to the North China. Now this phenomenon has aroused people's attention. Materials and Methods: In this study, meta-analysis was used to analyze the infection of rodents (vectors) in China, to clarify the transmission rule of O. tsutsugamushi. Results: This study included literature from six databases (PubMed, Web of Science, Science Direct, Wanfang, CNKI, and VIP). A total of 55 articles were included in the study from 610 retrieved articles. The total infection rate of O. tsutsugamushi in rodents was 5.5% (1206/20,620, 95% confidence interval [CI]: 0.0553-0.0617). The prevalence of O. tsutsugamushi in rodents before 2013 (7.73%, 95% CI: 4.11-12.37) was higher than after 2013 (2.11%, 95% CI: 0.64-4.41). O. tsutsugamushi spread among a variety of rodents, among which Rattus losea (13.3%, 95% CI: 4.33-26.26), Rattus tanezumi (5.69%, 95% CI: 1.37-12.72), and Apodemus agrarius (5.32%, 95% CI: 2.26-9.58) infection rate was higher. Kawasaki (8.32%, 95% CI: 1.42-20.17), Karp (7.36%, 95% CI: 2.62-14.22), Kato (2.54%, 95% CI: 0.08-8.28), and Gilliam (2.13%, 95% CI: 0.42-5.09) were the main prevalent genotypes in China. The prevalence of O. tsutsugamushi in rodents was seasonal, increasing gradually in summer (2.39%, 95% CI: 0.46-5.77), peaking in autumn (4.59%, 95% CI: 1.15-10.16), and then declining. The positive rate of immunofluorescence assay (25.07%, 95% CI: 8.44-46.88) was the highest among the detection methods, and it was statistically significant (p < 0.05). Based on the subgroup of geographical factors and climatic factors, the probability of O. tsutsugamushi infection in rodents was the highest when the temperature >19℃ (8.20%, 95% CI: 1.22-20.52), the altitude <100 millimeters (7.23%, 95% CI: 3.45-12.26), the precipitation >700 millimeters (12.22%, 95% CI: 6.45-19.50), and the humidity 60-70% (7.80%, 95% CI: 4.17-12.44). Conclusions: Studies have shown that rodents carrying O. tsutsugamushi are common. People should prevent and control rodents in life and monitor rodents carrying O. tsutsugamushi for a long time.
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Affiliation(s)
- Yan-Chun Wang
- School of Pharmacy, Qingdao University, Qingdao, PR China
- Changchun Sci-Tech University, Shuangyang, PR China
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Jing-Hao Li
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Ya Qin
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Si-Yuan Qin
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Chao Chen
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Xin-Bo Yang
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Ning Ma
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Ming-Xin Dong
- School of Pharmacy, Qingdao University, Qingdao, PR China
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Cong-Cong Lei
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Xing Yang
- Department of Medical Microbiology and Immunology, School of Basic Medicine, Dali University, Dali, PR China
| | - He-Ting Sun
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Zhi-Yong Sun
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Jing Jiang
- Changchun Sci-Tech University, Shuangyang, PR China
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Ling Y, Hu X, Zheng G, Ye W, Yuan K, Ye L, Huang W, Tian B, Gu B. Metagenomics as New Tool for Diagnosis of Scrub Typhus: Two Case Reports. Int Med Case Rep J 2023; 16:617-622. [PMID: 37789830 PMCID: PMC10544144 DOI: 10.2147/imcrj.s431864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 09/20/2023] [Indexed: 10/05/2023] Open
Abstract
Scrub typhus is a vector-borne infectious disease caused by Orientia tsutsugamushi. Accurate and timely diagnosis at the early infection stage could save the patients' lives. Traditional technologies were limited to rapidly and successfully detecting Orientia tsutsugamushi due to poor specificity, especially in the condition of atypical symptoms. The technology of Metagenomic next-generation sequencing (mNGS) is amenable to finding the real pathogen because it holds potential as a diagnostic platform for unbiased pathogen identification and precision medicine. Herein, we reported two clinical case reports relative to the Orientia tsutsugamushi infection diagnosed by mNGS. We hope these two cases will improve clinical diagnosis.
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Affiliation(s)
- Yong Ling
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Xuejiao Hu
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Guansheng Zheng
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Weitao Ye
- Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Kaixuan Yuan
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Long Ye
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Weiye Huang
- Department of Pathology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Benshun Tian
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
| | - Bing Gu
- Department of Clinical Laboratory Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China
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Huang J, Deng K, Chen J, Zhang M. Epidemiological and clinical characteristics of scrub typhus in northern Fujian, China, from 2015 to 2019. BMC Infect Dis 2023; 23:479. [PMID: 37464324 PMCID: PMC10354924 DOI: 10.1186/s12879-023-08451-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/11/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND This study aimed to analyze the epidemiological and clinical characteristics of scrub typhus in northern Fujian Province on the southeast coast of China. METHODS A retrospective analysis was performed on 303 patients with scrub typhus admitted to the First Hospital of Nanping City, Fujian Province, from January 2015 to December 2019. The epidemic characteristics were analyzed, such as the annual number of cases, age distribution, sex distribution, and seasonal distribution in each region. The patient's clinical manifestations, signs, complications, auxiliary examinations, and prognosis were analyzed. RESULTS From 2015 to 2019, the age distribution of scrub typhus cases was mainly concentrated in 40-49 y (17.16%), 50-59 y (24.09%), and 60-69 y (26.73%). There were no sex differences among the patients. 68.98% of the cases were concentrated in rural areas, with farmers having the highest proportion. However, this study compared prognostic factors in the cured and uncured groups, and found significant differences in non-farmer occupation and diagnosis time ≥ 8 days. Scrub typhus showed two peaks north of Fujian; the prominent peak was from June to July, and the other slight rise was from October to November. The SDE plot showed that the cases were mainly concentrated in Yanping, Shunchang, Zhenghe, and Songxi counties. The number of cases in hilly and mountainous areas was higher than in plain areas. The main diagnostic methods in this area are based on specific eschar and epidemiology, while the positive rate of the Weil-Felix test is low. CONCLUSIONS The results of this study can guide primary care institutions to improve the level of diagnosis and treatment of scrub typhus and take effective public health intervention measures in endemic areas.
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Affiliation(s)
- Jin Huang
- Department of Infectious Diseases, The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine, Wusi Road, Fuzhou, China.
| | - Kaixiang Deng
- Department of Traditional Chinese Medicine, First Hospital of Nanping City, Nanping, China
| | - Jiawei Chen
- Department of Infectious Diseases, The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine, Wusi Road, Fuzhou, China
| | - Meiquan Zhang
- Department of Pulmonary and Critical Care Medicine, Fujian Provincial Geriatric Hospital, Fuzhou, China
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Qian L, Wang Y, Wei X, Liu P, Magalhaes RJS, Qian Q, Peng H, Wen L, Xu Y, Sun H, Yin W, Zhang W. Epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province during 2012–2020. PLoS Negl Trop Dis 2022; 16:e0010278. [PMID: 36174105 PMCID: PMC9553047 DOI: 10.1371/journal.pntd.0010278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/11/2022] [Accepted: 09/13/2022] [Indexed: 12/02/2022] Open
Abstract
Background Scrub typhus has become a serious public health concern in the Asia-Pacific region including China. There were new natural foci continuously recognized and dramatically increased reported cases in mainland China. However, the epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province have yet to be investigated. Objective This study proposes to explore demographic characteristics and spatiotemporal dynamics of scrub typhus cases in Fujian province, and to detect high-risk regions between January 2012 and December 2020 at county/district scale and thereby help in devising public health strategies to improve scrub typhus prevention and control measures. Method Monthly cases of scrub typhus reported at the county level in Fujian province during 2012–2020 were collected from the National Notifiable Disease Surveillance System. Time-series analyses, spatial autocorrelation analyses and space-time scan statistics were applied to identify and visualize the spatiotemporal patterns of scrub typhus cases in Fujian province. The demographic differences of scrub typhus cases from high-risk and low-risk counties in Fujian province were also compared. Results A total of 11,859 scrub typhus cases reported in 87 counties from Fujian province were analyzed and the incidence showed an increasing trend from 2012 (2.31 per 100,000) to 2020 (3.20 per 100,000) with a peak in 2018 (4.59 per 100,000). There existed two seasonal peaks in June-July and September-October every year in Fujian province. A significant positive spatial autocorrelation of scrub typhus incidence in Fujian province was observed with Moran’s I values ranging from 0.258 to 0.471 (P<0.001). Several distinct spatiotemporal clusters mainly concentrated in north and southern parts of Fujian province. Compared to low-risk regions, a greater proportion of cases were female, farmer, and older residents in high-risk counties. Conclusions These results demonstrate a clear spatiotemporal heterogeneity of scrub typhus cases in Fujian province, and provide the evidence in directing future researches on risk factors and effectively assist local health authorities in the refinement of public health interventions against scrub typhus transmission in the high risk regions. Scrub typhus is a vector-borne zoonotic disease caused by Orientia tsutsugamushi and is popular in the Asia-Pacific area. Nowadays scrub typhus has been recognized as a considerable burden on public health in Fujian province. We explored the epidemiological characteristics, spatiotemporal patterns and diffusion characteristics of scrub typhus, and detected high-risk regions at the county level in Fujian province between January 2012 and December 2020. Our results indicated that the majority of cases were reported in June-July and September-October and that that middle aged and elderly people were more prone to infection every year in Fujian province. The spatial autocorrelation analysis revealed clustering in geographic distribution of cases and several distinct spatiotemporal clusters were identified in north and southern parts of Fujian province. Compared with cases from low-risk areas, a higher proportion of cases were female, farmer, and older residents in high-risk counties.
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Affiliation(s)
- Li Qian
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, Chongqing, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Ping Liu
- Department of General Practice, Chinese PLA General Hospital-Sixth Medical Center, Beijing, China
| | - Ricardo J. Soares Magalhaes
- Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia
- Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Quan Qian
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hong Peng
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Liang Wen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hailong Sun
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
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Cao Y, Li M, Haihambo N, Zhu Y, Zeng Y, Jin J, Qiu J, Li Z, Liu J, Teng J, Li S, Zhao Y, Zhao X, Wang X, Li Y, Feng X, Han C. Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021. Front Public Health 2022; 10:903025. [PMID: 36033737 PMCID: PMC9402928 DOI: 10.3389/fpubh.2022.903025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/19/2022] [Indexed: 01/22/2023] Open
Abstract
Background Epidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government. Method In this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis. Results We found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter. Conclusion Our results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.
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Affiliation(s)
- Yanxiang Cao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Meijia Li
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium
| | - Naem Haihambo
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium
| | - Yuyao Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Yimeng Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jianhua Jin
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jinyi Qiu
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Zhirui Li
- Baoding First Central Hospital, Baoding, China
| | - Jiaxin Liu
- Department of Psychology, University of Washington, Washington, SA, United States
| | - Jiayi Teng
- School of Psychology, Philosophy and Language Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Sixiao Li
- Faculty of Arts, Humanities and Cultures, School of Music, University of Leeds, Leeds, United Kingdom
| | - Yanan Zhao
- China Academy of Chinese Medical Sciences, Institute of Acupuncture and Moxibustion, Beijing, China
| | - Xixi Zhao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xuemei Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yaqiong Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiaoyang Feng
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
| | - Chuanliang Han
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, China
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8
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Development of a Scoring System to Differentiate Severe Fever with Thrombocytopenia Syndrome from Scrub Typhus. Viruses 2022; 14:v14051093. [PMID: 35632834 PMCID: PMC9143636 DOI: 10.3390/v14051093] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/07/2022] [Accepted: 05/12/2022] [Indexed: 02/01/2023] Open
Abstract
Severe fever with thrombocytopenia syndrome (SFTS) and scrub typhus are disorders with similar clinical features; therefore, differentiating between them is difficult. We retrospectively collected data from 183 SFTS and 178 scrub typhus patients and validated an existing scoring system to develop a more sensitive, specific, and objective scoring system. We first applied the scoring systems proposed by Kim et al. to differentiate SFTS from scrub typhus. Multivariable logistic regression revealed that altered mental status, leukopenia, prolonged activated partial thromboplastin time (aPTT), and normal C-reactive protein (CRP) level (≤1.0 mg/dL) were significantly associated with SFTS. We changed the normal CRP level from ≤1.0 mg/dL to ≤3.0 mg/dL and replaced altered mental status with the creatine kinase (CK) level. The modified scoring system showed 97% sensitivity and 96% specificity for SFTS (area under the curve (AUC): 0.983) and a higher accuracy than the original scoring system (p = 0.0308). This study’s scoring system had 97% sensitivity and 98% specificity for SFTS (AUC: 0.992) and a higher accuracy than Kim et al.’s original scoring system (p = 0.0308). Our scoring system that incorporated leukopenia, prolonged aPTT, normal CRP level (≤3.0 mg/dL), and elevated CK level (>1000 IU/L) easily differentiated SFTS from scrub typhus in an endemic area.
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Musa TH, Ahmad T, Wana MN, Li W, Musa HH, Sharun K, Tiwari R, Dhama K, Chaicumpa W, Campbell MC, Wei P. The epidemiology, diagnosis and management of scrub typhus disease in China. Hum Vaccin Immunother 2021; 17:3795-3805. [PMID: 34124995 DOI: 10.1080/21645515.2021.1934355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
Thirty-nine years ago, scrub typhus (ST), a disease, was not among the China's notifiable diseases. However, ST has reemerged to become a growing public health issue in the southwest part of China. The major factors contributing to an increased incidence and prevalence of this disease include rapid globalization, urbanization, expansion of humans into previously uninhabited areas, and climate change. The clinical manifestation of ST also consists of high fever, headache, weakness, myalgia, rash, and an eschar. In severe cases, complications (e.g. multi-organ failure, jaundice, acute renal failure, pneumonitis, myocarditis, and even death) can occur. The diagnosis of ST is mainly based on serological identification by indirect immunofluorescence assay and other molecular methods. Furthermore, several groups of antibiotics (e.g. tetracycline, chloramphenicol, macrolides, and rifampicin) are currently effective in treating this disease. This fact suggests the need for robust early diagnostic techniques, increased surveillance, and prompt treatment, and develop future vaccine.
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Affiliation(s)
- Taha Hussein Musa
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.,Biomedical Research Institute (BRI), Darfur College, Nyala, Sudan
| | - Tauseef Ahmad
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Mohammed Nasiru Wana
- Department of Biological Sciences, Faculty of Science, Abubakar Tafawa Balewa University, Bauchi, Nigeria
| | - Wei Li
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Hassan Hussein Musa
- Faculty of Medical Laboratory Sciences, University of Khartoum, Khartoum, Sudan
| | - Khan Sharun
- Division of Surgery, ICAR-Indian Veterinary Research Institute, Bareilly, India
| | - Ruchi Tiwari
- Department of Veterinary Microbiology and Immunology, College of Veterinary Sciences, UP Deen Dayal Upadhayaya Pashu Chikitsa Vigyan Vishwavidyalay Evum Go-Anusandhan Sansthan (DUVASU), Mathura, India
| | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Bareilly, India
| | - Wanpen Chaicumpa
- Center of Research Excellence on Therapeutic Proteins and Antibody Engineering, Department of Parasitology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | - Pingmin Wei
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
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Yang S, Liu X, Gao Y, Chen B, Lu L, Zheng W, Fu R, Yuan C, Liu Q, Li G, Chen H. Spatiotemporal Dynamics of Scrub Typhus in Jiangxi Province, China, from 2006 to 2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094599. [PMID: 33926106 PMCID: PMC8123664 DOI: 10.3390/ijerph18094599] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/15/2021] [Accepted: 04/20/2021] [Indexed: 01/04/2023]
Abstract
Background: Scrub typhus (ST) has become a significant potential threat to public health in Jiangxi. Further investigation is essential for the control and management of the spatiotemporal patterns of the disease. Methods: Time-series analyses, spatial distribution analyses, spatial autocorrelation analysis, and space-time scan statistics were performed to detect spatiotemporal dynamics distribution of the incidence of ST. Results: From 2006 to 2018, a total of 5508 ST cases occurred in Jiangxi, covering 79 counties. The number of ST cases increased continuously from 2006 to 2018, and there was obvious seasonality during the variation process in each year, with a primary peak in autumn (September to October) and a smaller peak in summer (June to August). From 2007 to 2018, the spatial distribution of the ST epidemic was significant heterogeneity, and Nanfeng, Huichang, Xunwu, Anyuan, Longnan, and Xinfeng were hotspots. Seven spatiotemporal clusters were observed using Kulldorff's space-time scan statistic, and the most likely cluster only included one county, Nanfeng county. The high-risk areas of the disease were in the mountainous, hilly region of Wuyi and the southern mountainous region of Jiangxi. Conclusions: Targeted interventions should be executed in high-risk regions for the precise prevention and control of ST.
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Affiliation(s)
- Shu Yang
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China; (S.Y.); (W.Z.); (R.F.); (C.Y.)
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (Y.G.); (L.L.); (Q.L.)
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (Y.G.); (L.L.); (Q.L.)
| | - Baizhou Chen
- School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China;
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (Y.G.); (L.L.); (Q.L.)
| | - Weiqing Zheng
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China; (S.Y.); (W.Z.); (R.F.); (C.Y.)
| | - Renlong Fu
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China; (S.Y.); (W.Z.); (R.F.); (C.Y.)
| | - Chenying Yuan
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China; (S.Y.); (W.Z.); (R.F.); (C.Y.)
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (Y.G.); (L.L.); (Q.L.)
| | - Guichang Li
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (Y.G.); (L.L.); (Q.L.)
- Correspondence: (G.L.); (H.C.)
| | - Haiying Chen
- The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China; (S.Y.); (W.Z.); (R.F.); (C.Y.)
- Correspondence: (G.L.); (H.C.)
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11
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Xin H, Fu P, Sun J, Lai S, Hu W, Clements ACA, Sun J, Cui J, Hay SI, Li X, Li Z. Risk mapping of scrub typhus infections in Qingdao city, China. PLoS Negl Trop Dis 2020; 14:e0008757. [PMID: 33264282 PMCID: PMC7735632 DOI: 10.1371/journal.pntd.0008757] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 12/14/2020] [Accepted: 08/28/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The emergence and re-emergence of scrub typhus has been reported in the past decade in many global regions. In this study, we aim to identify potential scrub typhus infection risk zones with high spatial resolution in Qingdao city, in which scrub typhus is endemic, to guide local prevention and control strategies. METHODOLOGY/PRINCIPAL FINDINGS Scrub typhus cases in Qingdao city during 2006-2018 were retrieved from the Chinese National Infectious Diseases Reporting System. We divided Qingdao city into 1,101 gridded squares and classified them into two categories: areas with and without recorded scrub typhus cases. A boosted regression tree model was used to explore environmental and socioeconomic covariates associated with scrub typhus occurrence and predict the risk of scrub typhus infection across the whole area of Qingdao city. A total of 989 scrub typhus cases were reported in Qingdao from 2006-2018, with most cases located in rural and suburban areas. The predicted risk map generated by the boosted regression tree models indicated that the highest infection risk areas were mainly concentrated in the mid-east and northeast regions of Qingdao, with gross domestic product (20.9%±1.8% standard error) and annual cumulative precipitation (20.3%±1.1%) contributing the most to the variation in the models. By using a threshold environmental suitability value of 0.26, we identified 757 squares (68.7% of the total) with a favourable environment for scrub typhus infection; 66.2% (501/757) of the squares had not yet recorded cases. It is estimated that 6.32 million people (72.5% of the total population) reside in areas with a high risk of scrub typhus infection. CONCLUSIONS/SIGNIFICANCE Many locations in Qingdao city with no recorded scrub typhus cases were identified as being at risk for scrub typhus occurrence. In these at-risk areas, awareness and capacity for case diagnosis and treatment should be enhanced in the local medical service institutes.
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Affiliation(s)
- Hualei Xin
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- World Health Organization (WHO) Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Peng Fu
- Department of Anesthesiology, Qingdao Fuwai Cardiovascular Hospital, Qingdao, Shandong, China
| | - Junling Sun
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shengjie Lai
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Geography and Environmental Science, University of Southampton, Southampton 1BJ, United Kingdom
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Archie C. A. Clements
- Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Jianping Sun
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Jing Cui
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Simon I. Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States of America
| | - Xiaojing Li
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
- * E-mail: (XL); (ZL)
| | - Zhongjie Li
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (XL); (ZL)
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12
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Xin H, Sun J, Yu J, Huang J, Chen Q, Wang L, Lai S, Clements ACA, Hu W, Li Z. Spatiotemporal and demographic characteristics of scrub typhus in Southwest China, 2006–2017: An analysis of population‐based surveillance data. Transbound Emerg Dis 2020; 67:1585-1594. [DOI: 10.1111/tbed.13492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 01/09/2020] [Accepted: 01/13/2020] [Indexed: 01/31/2023]
Affiliation(s)
- Hualei Xin
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Qingdao City Center for Disease Control and Prevention Qingdao China
| | - Junling Sun
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Jianxing Yu
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Ministry of Health Key Laboratory of Systems Biology of Pathogens and Dr. Christophe Mérieux Laboratory CAMS‐Foundation Mérieux Institute of Pathogen Biology Academy of Medical Sciences of China and Peking Union Medical College Beijing China
| | - Jilei Huang
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Chinese Center for Disease Control and Prevention National Institute of Parasitic Diseases Shanghai China
| | - Qiulan Chen
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Liping Wang
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Shengjie Lai
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- WorldPop School of Geography and Environmental Science University of Southampton Southampton UK
- School of Public Health Key Laboratory of Public Health Safety Ministry of Education Fudan University Shanghai China
| | - Archie C. A. Clements
- Faculty of Health Sciences Curtin University Bentley WA Australia
- Telethon Kids Institute Nedlands WA Australia
| | - Wenbiao Hu
- School of Public Health and Social Work Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane Australia
| | - Zhongjie Li
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
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