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Zhang X, Yao X, Chen H, Han D, Yang M. Meta-genomic next-generation sequencing in the diagnosis of brucellosis: Five cases from a non-endemic area. Future Microbiol 2024; 19:1111-1117. [PMID: 39109822 DOI: 10.1080/17460913.2024.2363632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Accepted: 05/31/2024] [Indexed: 08/17/2024] Open
Abstract
Metagenomic next-generation sequencing (mNGS) in diagnosis of human brucellosis is comparatively unexplored. This report details five human brucellosis cases diagnosed using mNGS based on Illumina sequencing platform, comprising three females and two males, four with epidemiological exposure. In cases 1 and 2, plasma mNGS results showed one positive and one negative for Brucella melitensis, and subsequent blood cultures were both positive. Cases 3, 4 and 5 involved spinal brucellosis, some with paravertebral abscesses. mNGS from infectious tissue samples successfully detected Brucella, with read counts ranging between 30 and 1314, yet cultures were negative in cases 4 and 5. Following antibiotic and surgical treatments, all patients showed clinical improvement. This report shows mNGS testing enhances the detection sensitivity of brucellosis diagnosis.
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Affiliation(s)
- Xuan Zhang
- State Key Laboratory for Diagnosis & Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis & Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xinfei Yao
- State Key Laboratory for Diagnosis & Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis & Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Huixin Chen
- State Key Laboratory for Diagnosis & Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis & Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Dongsheng Han
- Department of Laboratory Medicine, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, Zhejiang, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Meifang Yang
- State Key Laboratory for Diagnosis & Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis & Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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2
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Wen X, Wang Y, Shao Z. The spatiotemporal trend of human brucellosis in China and driving factors using interpretability analysis. Sci Rep 2024; 14:4880. [PMID: 38418566 PMCID: PMC10901783 DOI: 10.1038/s41598-024-55034-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/19/2024] [Indexed: 03/01/2024] Open
Abstract
Human brucellosis has reemerged in China, with a distinct change in its geographical distribution. The incidence of human brucellosis has significantly risen in inland regions of China. To gain insights into epidemic characteristics and identify factors influencing the geographic spread of human brucellosis, our study utilized the Extreme Gradient Boosting (XGBoost) algorithm and interpretable machine learning techniques. The results showed a consistent upward trend in the incidence of human brucellosis, with a significant increase of 8.20% from 2004 to 2021 (95% CI: 1.70, 15.10). The northern region continued to face a serious human situation, with a gradual upward trend. Meanwhile, the western and southern regions have experienced a gradual spread of human brucellosis, encompassing all regions of China over the past decade. Further analysis using Shapley Additive Explanations (SHAP) demonstrated that higher Gross Domestic Product (GDP) per capita and increased funding for education have the potential to reduce the spread. Conversely, the expansion of human brucellosis showed a positive correlation with bed availability per 1000 individuals, humidity, railway mileage, and GDP. These findings strongly suggest that socioeconomic factors play a more significant role in the spread of human brucellosis than other factors.
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Affiliation(s)
- Xiaohui Wen
- Department of Epidemiology, Air Force Medical University, Xi'an, 710000, China
| | - Yun Wang
- Central Sterile Services Department, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710000, China
| | - Zhongjun Shao
- Department of Epidemiology, Air Force Medical University, Xi'an, 710000, China.
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3
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Gao S, Peng R, Zeng Z, Zhai J, Yang M, Liu X, Sharav T, Chen Z. Risk transboundary transmission areas and driving factors of brucellosis along the borders between China and Mongolia. Travel Med Infect Dis 2023; 56:102648. [PMID: 37813322 DOI: 10.1016/j.tmaid.2023.102648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/26/2023] [Accepted: 10/01/2023] [Indexed: 10/11/2023]
Abstract
OBJECTIVE Brucellosis is a common and neglected zoonotic infectious disease worldwide caused by Brucella. However, transboundary transmissions among countries, particularly those with high incidences, are seldom investigated. In the present study, by taking China and Mongolia as examples, we aim to identify transboundary transmission risk and driving factors of brucellosis along borders. METHODS 167 brucellosis outbreak locations along the border between China and Mongolia were collected. Wildlife distribution and cross-border activities were mapped. Maximum entropy approach modeling was conducted to predict the potential risk of prevalence of brucellosis with meteorological factors, geographical environment, economic development, living habits et al. The accuracy of the models was assessed by the area under the receiver operating characteristic (ROC) curve (AUC), Kappa test, and correctly classified instances (CCI). RESULTS The spatial model performed excellent predictive performance with the predictor variables of soils, pastures, goat density, mean precipitation of the wettest month, temperature seasonality, and population density, which with the contribution and permutation important in 27.2 %, 31.9; 23.3 %, 6.8; 18.0 %, 17.2; 11.2 %, 18.1; 10. 3 %, 15.2; 10.0 %, 10.8. The calculated AUC, SD, Kappa, and CCI are 0.870, 0.001, 0.882, and 0.883, respectively. The distribution map of brucellosis showed high-risk areas along the borders. CONCLUSIONS Our study identified high-risk areas and the driving effect of brucellosis along the borders between China and Mongolia. Moreover, there is the possibility of cross-border wildlife activities in high-risk areas, which increases the risk of cross-border brucellosis transmission. The funding provides clues for cooperative prevention and control of brucellosis by reducing transboundary transmission.
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Affiliation(s)
- Shan Gao
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, PR China
| | - Ruihao Peng
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, PR China
| | - Zan Zeng
- Department of Vascular Surgery, the First Affiliated Hospital of the Navy Medical University, Shanghai, 200433, PR China
| | - Jingbo Zhai
- Key Laboratory of Zoonose Prevention and Control at Universities of Inner Mongolia Autonomous Region, Innovative Institute of Zoonoses, Inner Mongolia Minzu University, Tongliao, 028000, PR China
| | - Mingwei Yang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, PR China
| | - Xinrui Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, PR China
| | - Tumenjargal Sharav
- Department of Infectious Diseases and Public Health, School of Veterinary Medicine, Mongolian University of Life Science, Khan-Uul District, Zaisan, 17042, Ulaanbaatar, Mongolia.
| | - Zeliang Chen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, PR China; Key Laboratory of Zoonose Prevention and Control at Universities of Inner Mongolia Autonomous Region, Innovative Institute of Zoonoses, Inner Mongolia Minzu University, Tongliao, 028000, PR China.
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Phang WK, Hamid MHBA, Jelip J, Mudin RNB, Chuang TW, Lau YL, Fong MY. Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches. Front Microbiol 2023; 14:1126418. [PMID: 36876062 PMCID: PMC9977793 DOI: 10.3389/fmicb.2023.1126418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
The emergence of potentially life-threatening zoonotic malaria caused by Plasmodium knowlesi nearly two decades ago has continued to challenge Malaysia healthcare. With a total of 376 P. knowlesi infections notified in 2008, the number increased to 2,609 cases in 2020 nationwide. Numerous studies have been conducted in Malaysian Borneo to determine the association between environmental factors and knowlesi malaria transmission. However, there is still a lack of understanding of the environmental influence on knowlesi malaria transmission in Peninsular Malaysia. Therefore, our study aimed to investigate the ecological distribution of human P. knowlesi malaria in relation to environmental factors in Peninsular Malaysia. A total of 2,873 records of human P. knowlesi infections in Peninsular Malaysia from 1st January 2011 to 31st December 2019 were collated from the Ministry of Health Malaysia and geolocated. Three machine learning-based models, maximum entropy (MaxEnt), extreme gradient boosting (XGBoost), and ensemble modeling approach, were applied to predict the spatial variation of P. knowlesi disease risk. Multiple environmental parameters including climate factors, landscape characteristics, and anthropogenic factors were included as predictors in both predictive models. Subsequently, an ensemble model was developed based on the output of both MaxEnt and XGBoost. Comparison between models indicated that the XGBoost has higher performance as compared to MaxEnt and ensemble model, with AUCROC values of 0.933 ± 0.002 and 0.854 ± 0.007 for train and test datasets, respectively. Key environmental covariates affecting human P. knowlesi occurrence were distance to the coastline, elevation, tree cover, annual precipitation, tree loss, and distance to the forest. Our models indicated that the disease risk areas were mainly distributed in low elevation (75-345 m above mean sea level) areas along the Titiwangsa mountain range and inland central-northern region of Peninsular Malaysia. The high-resolution risk map of human knowlesi malaria constructed in this study can be further utilized for multi-pronged interventions targeting community at-risk, macaque populations, and mosquito vectors.
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Affiliation(s)
- Wei Kit Phang
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | | | - Jenarun Jelip
- Disease Control Division, Ministry of Health Malaysia, Putrajaya, Malaysia
| | - Rose Nani Binti Mudin
- Sabah State Health Department, Ministry of Health Malaysia, Kota Kinabalu, Sabah, Malaysia
| | - Ting-Wu Chuang
- Department of Molecular Parasitology and Tropical Diseases, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yee Ling Lau
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Mun Yik Fong
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
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Driving effect of multiplex factors on human brucellosis in high incidence region, implication for brucellosis based on one health concept. One Health 2022; 15:100449. [DOI: 10.1016/j.onehlt.2022.100449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/16/2022] [Accepted: 10/16/2022] [Indexed: 11/06/2022] Open
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Dong W, Zhang P, Xu QL, Ren ZD, Wang J. A Study on a Neural Network Risk Simulation Model Construction for Avian Influenza A (H7N9) Outbreaks in Humans in China during 2013-2017. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10877. [PMID: 36078588 PMCID: PMC9518328 DOI: 10.3390/ijerph191710877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
The main purposes of this study were to explore the spatial distribution characteristics of H7N9 human infections during 2013-2017, and to construct a neural network risk simulation model of H7N9 outbreaks in China and evaluate their effects. First, ArcGIS 10.6 was used for spatial autocorrelation analysis, and cluster patterns ofH7N9 outbreaks were analyzed in China during 2013-2017 to detect outbreaks' hotspots. During the study period, the incidence of H7N9 outbreaks in China was high in the eastern and southeastern coastal areas of China, with a tendency to spread to the central region. Moran's I values of global spatial autocorrelation of H7N9 outbreaks in China from 2013 to 2017 were 0.080128, 0.073792, 0.138015, 0.139221 and 0.050739, respectively (p < 0.05) indicating a statistically significant positive correlation of the epidemic. Then, SPSS 20.0 was used to analyze the correlation between H7N9 outbreaks in China and population, livestock production, the distance between the case and rivers, poultry farming, poultry market, vegetation index, etc. Statistically significant influencing factors screened out by correlation analysis were population of the city, average vegetation of the city, and the distance between the case and rivers (p < 0.05), which were included in the neural network risk simulation model of H7N9 outbreaks in China. The simulation accuracy of the neural network risk simulation model of H7N9 outbreaks in China from 2013 to 2017 were 85.71%, 91.25%, 91.54%, 90.49% and 92.74%, and the AUC were 0.903, 0.976, 0.967, 0.963 and 0.970, respectively, showing a good simulation effect of H7N9 epidemics in China. The innovation of this study lies in the epidemiological study of H7N9 outbreaks by using a variety of technical means, and the construction of a neural network risk simulation model of H7N9 outbreaks in China. This study could provide valuable references for the prevention and control of H7N9 outbreaks in China.
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Affiliation(s)
- Wen Dong
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China
- GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming 650500, China
| | - Peng Zhang
- College of Intelligent Information Engineering, Chongqing Aerospace Polytechnic College, Chongqing 400021, China
| | - Quan-Li Xu
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China
- GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming 650500, China
| | - Zhong-Da Ren
- GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming 650500, China
- State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
| | - Jie Wang
- Chongqing City Management College, Chongqing 401331, China
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Zhu Y, Shi L, Zeng Y, Piao D, Xie Y, Du J, Gao M, Gao W, Tian J, Yue J, Li M, Guo X, Yao Y, Kang Y. Key immunity characteristics of diverse stages of brucellosis in rural population from Inner Mongolia, China. Infect Dis Poverty 2022; 11:63. [PMID: 35659087 PMCID: PMC9167523 DOI: 10.1186/s40249-022-00989-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 05/16/2022] [Indexed: 01/18/2023] Open
Abstract
Background Brucellosis poses a serious threat to human and animal health, particularly in developing countries such as China. The Inner Mongolia Autonomous Region is one of the most severely brucellosis-endemic provinces in China. Currently, the host immune responses functioning to control Brucella infection and development remain poorly understood. The aim of this study is to further clarify the key immunity characteristics of diverse stages of brucellosis in Inner Mongolia.
Methods We collected a total of 733 blood samples from acute (n = 137), chronic (n = 316), inapparent (n = 35), recovery (n = 99), and healthy (n = 146) groups from the rural community of Inner Mongolia between 2014 and 2015. The proportions of CD4+, CD8+, Th1, Th2, and Th17 T cells in peripheral blood and the expression of TLR2 and TLR4 in lymphocytes, monocytes and granulocytes were examined using flow cytometry analysis. The differences among the five groups were compared using one-way ANOVA and the Kruskal–Wallis method, respectively.
Results Our results revealed that the proportions of CD4+ and CD8+ T cells were significantly different among the acute, chronic, recovery, and healthy control groups (P < 0.05), with lower proportions of CD4+ T cells and a higher proportion of CD8+ T cells in the acute, chronic, and recovery groups. The proportion of Th1 cells in the acute, chronic, and inapparent groups was higher than that in the healthy and recovery groups; however, there was no significant difference between patients and healthy individuals (P > 0.05). The proportion of Th2 lymphocytes was significantly higher in the acute and healthy groups than in the inapparent group (P < 0.05). The proportion of Th17 cells in the acute group was significantly higher than that in the healthy control, chronic, and inapparent groups (P < 0.05). Finally, the highest expression of TLR4 in lymphocytes, monocytes and granulocytes was observed in the recovery group, and this was followed by the acute, chronic, healthy control, and inapparent groups. There was a significant difference between the recovery group and the other groups, except for the acute group (P < 0.05). Moreover, a correlation in TLR4 expression was observed in lymphocytes, monocytes and granulocytes among the five groups (r > 0.5), except for the inapparent group between lymphocytes and granulocytes (r = 0.34). Conclusions Two key factors (CD8+ T cells and TLR4) in human immune profiles may closely correlate with the progression of brucellosis. The detailed function of TLR4 in the context of a greater number of cell types or tissues in human or animal brucellosis and in larger samples should be further explored in the future. Graphical Abstract ![]()
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Affiliation(s)
- Yongzhang Zhu
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China
| | - Li Shi
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Yige Zeng
- Department of Biological Science, Xi'an Jiaotong-Liverpool University, Suzhou, China
| | - Dongri Piao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yingbo Xie
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Juan Du
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Meng Gao
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Wei Gao
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Junli Tian
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Jun Yue
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
| | - Min Li
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China
| | - XiaoKui Guo
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China.
| | - Yufeng Yao
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China.
| | - YaoXia Kang
- Baotou Municipal Center for Disease Control and Prevention, Baotou, Inner Mongolia, China. .,Inner Mongolia Autonomous Region Comprehensive Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China.
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8
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Liang D, Liu D, Yang M, Wang X, Li Y, Guo W, Du M, Wang W, Xue M, Wu J, Cui B, Yin S, Wang R, Li S. Spatiotemporal distribution of human brucellosis in Inner Mongolia, China, in 2010-2015, and influencing factors. Sci Rep 2021; 11:24213. [PMID: 34930982 PMCID: PMC8688419 DOI: 10.1038/s41598-021-03723-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 09/16/2020] [Indexed: 12/03/2022] Open
Abstract
Human brucellosis is caused by Brucella species and remains a major burden in both human and domesticated animal populations, especially in Inner Mongolia, China. The aims of this study were to analyze the spatiotemporal trends in human brucellosis in Inner Mongolia during 2010 to 2015, to explore the factors affecting the incidence of brucellosis. The results showed that the annual incidence was 29.68–77.67 per 100,000, and peaked from March to June. The majority of human brucellosis was male farmers and herdsmen, aged 40–59 years. The high-risk areas were mainly Xilin Gol League and Hulunbeier City. The incidence of human brucellosis in Inner Mongolia decreased during 2010 to 2015, although the middle and eastern regions were still high-risk areas. The regions with larger number of sheep and cattle, lower GDP per capita, less number of hospital beds, higher wind speed, lower mean temperature more likely to become high-risk areas of human brucellosis.
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Affiliation(s)
- Danyan Liang
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.,Inner Mongolia People's Hospital, Hohhot, China
| | - Dan Liu
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.,Department of Medicine, Hetao College, Bayan Nur, China
| | - Min Yang
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Xuemei Wang
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
| | - Yunpeng Li
- Inner Mongolia Ecology and Agrometeorology Center, Hohhot, China
| | - Weidong Guo
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, China
| | - Maolin Du
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Wenrui Wang
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, China
| | - Mingming Xue
- School of Basic Medicine, Inner Mongolia Medical University, Hohhot, China
| | - Jing Wu
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Buyun Cui
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shaohua Yin
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Ruiqi Wang
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Shiyuan Li
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
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9
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Zhao B, Gong QL, Feng HF, Wang Q, Shi JF, Song YH, Liu F, Shi K, Zong Y, Du R, Li JM. Brucellosis prevalence in yaks in China in 1980-2019: A systematic review and meta-analysis. Prev Vet Med 2021; 198:105532. [PMID: 34844124 DOI: 10.1016/j.prevetmed.2021.105532] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 11/01/2021] [Accepted: 11/02/2021] [Indexed: 11/24/2022]
Abstract
In the Qinghai-Tibet Plateau of China, the yak is an animal of particular economic interest, which provides protein and income for herders in daily life. Brucellosis is a bacterial disease that can infect humans and animals, including yaks. It can damage the yak reproductive system, causing miscarriage and orchitis. At the same time, brucellosis threatens the health of herders. We performed this meta-analysis using R software to explore the combined prevalence and risk factors of brucellosis in yak in China. Variability was assessed by the I2 statistic and Cochran Q statistic. We identified 52 publications of related research from four databases (Wanfang Data, VIP Chinese Journal Database, China National Knowledge Infrastructure, and of PubMed). The pooled prevalence of yak brucellosis was 8.39 %. Prevalence was highest in Southwestern China (11.1 %). The point estimate of brucellosis in yak from 2012 to 2016 was the highest (11.47 %). The point estimate of age ≤ 12 months (1.44 %) was lower than that of age > 12 months (15.6 %). This study shows that yak brucellosis is serious, and its incidence is higher than before 2012. We recommend carrying out large-scale yak brucellosis investigations in Western China and conducting comprehensive testing planning. The detection of brucellosis in adult animals should be strengthened to reduce the economic loss caused by brucellosis to herders and to improve public health.
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Affiliation(s)
- Bo Zhao
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China; College of Chinese Medicine Materials, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Qing-Long Gong
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Hai-Feng Feng
- Animal Health Supervision Institute of Jilin Province, Changchun, Jilin Province 130061, PR China
| | - Qi Wang
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Jun-Feng Shi
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Yu-Hao Song
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Fei Liu
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Kun Shi
- College of Chinese Medicine Materials, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Ying Zong
- College of Chinese Medicine Materials, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China
| | - Rui Du
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China.
| | - Jian-Ming Li
- College of Chinese Medicine Materials, Jilin Agricultural University, Changchun, Jilin Province 130118, PR China.
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10
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Babaie E, Alesheikh AA, Tabasi M. Spatial prediction of human brucellosis (HB) using a GIS-based adaptive neuro-fuzzy inference system (ANFIS). Acta Trop 2021; 220:105951. [PMID: 33979640 DOI: 10.1016/j.actatropica.2021.105951] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 04/18/2021] [Accepted: 05/04/2021] [Indexed: 01/23/2023]
Abstract
OBJECTIVE This study pursues three main objectives: 1) exploring the spatial distribution patterns of human brucellosis (HB); 2) identifying parameters affecting the disease spread; and 3) modeling and predicting the spatial distribution of HB cases in 2012-2016 and 2017-2018, respectively, in rural districts of Mazandaran province, Iran. METHODS We collected data on the disease incidence, demography, ecology, climate, topography, and vegetation. Using the Global Moran's I statistic, we measured spatial autocorrelation between log (number of HB cases). We applied the Getis-Ord Gi* statistic to identify areas with high and low risk of the disease. To investigate the relationships between the factors affecting the incidence of HB as input variables together and the factors with the log (number of HB cases) as an output variable, we used the statistical linear regression model and the Pearson correlation coefficient. Then, we implemented a GIS-based adaptive neuro-fuzzy inference system (ANFIS) with two subtractive clustering and fuzzy c-means (FCM) clustering methods to model and predict the spatial distribution of HB. RESULTS Global Moran's I spatial autocorrelation analysis indicated that the type of HB distribution is clustered in all years except 2014 and 2017, which are random. According to the Getis-Ord Gi* analysis, the location of the hot spots varied during 2012-2018. In 2012 and 2013, most of the hot spots were seen in the west of the province. While in 2018, they were mostly concentrated in the eastern regions of the province. The linear regression model indicated that the parameters affecting the incidence of HB are independent of each other and can explain only 25.3% of the total changes in the log (number of HB cases). The results of the Pearson correlation coefficient showed that there were positive relationships between vegetation, log (population), and the number of sheep and cattle (p-value < 0.05). The above-mentioned factors had the strongest positive correlation with the log (number of HB cases) (p-value < 0.01). These results may be due to the fact that vegetation regions are suitable for livestock grazing, attracting large crowds of people. Therefore, this will increase HB cases. We compared the results of subtractive clustering and FCM clustering methods by evaluation criteria (e.g., linear correlation coefficient (LCC) and mean absolute error (MAE)) in two phases of development and assessment of the ANFIS model. In the assessment phase, we predicted the spatial distribution of log (number of HB cases) in 2017 and 2018 by subtractive clustering (R2 = 0.699, LCC or R = 0.692, MAE = 0.509, MSE = 0.455) and by FCM clustering (R2 = 0.704, LCC or R = 0.697, MAE = 0.512, MSE = 0.448) that showed FCM clustering outperformed the subtractive clustering. CONCLUSION The findings may have important implications for public health. The emergence of the hot spots in the east of the province can be a warning to the health system. Health authorities can use the findings of this study to predict the spread of HB and perform HB prevention programs. They can also investigate the factors affecting the prevalence of the disease, identify high-risk areas, and ultimately allocate resources to high-risk regions.
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Zhai M, Li W, Tie P, Wang X, Xie T, Ren H, Zhang Z, Song W, Quan D, Li M, Chen L, Qiu L. Research on the predictive effect of a combined model of ARIMA and neural networks on human brucellosis in Shanxi Province, China: a time series predictive analysis. BMC Infect Dis 2021; 21:280. [PMID: 33740904 PMCID: PMC7980350 DOI: 10.1186/s12879-021-05973-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 03/09/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Brucellosis is a major public health problem that seriously affects developing countries and could cause significant economic losses to the livestock industry and great harm to human health. Reasonable prediction of the incidence is of great significance in controlling brucellosis and taking preventive measures. METHODS Our human brucellosis incidence data were extracted from Shanxi Provincial Center for Disease Control and Prevention. We used seasonal-trend decomposition using Loess (STL) and monthplot to analyse the seasonal characteristics of human brucellosis in Shanxi Province from 2007 to 2017. The autoregressive integrated moving average (ARIMA) model, a combined model of ARIMA and the back propagation neural network (ARIMA-BPNN), and a combined model of ARIMA and the Elman recurrent neural network (ARIMA-ERNN) were established separately to make predictions and identify the best model. Additionally, the mean squared error (MAE), mean absolute error (MSE) and mean absolute percentage error (MAPE) were used to evaluate the performance of the model. RESULTS We observed that the time series of human brucellosis in Shanxi Province increased from 2007 to 2014 but decreased from 2015 to 2017. It had obvious seasonal characteristics, with the peak lasting from March to July every year. The best fitting and prediction effect was the ARIMA-ERNN model. Compared with those of the ARIMA model, the MAE, MSE and MAPE of the ARIMA-ERNN model decreased by 18.65, 31.48 and 64.35%, respectively, in fitting performance; in terms of prediction performance, the MAE, MSE and MAPE decreased by 60.19, 75.30 and 64.35%, respectively. Second, compared with those of ARIMA-BPNN, the MAE, MSE and MAPE of ARIMA-ERNN decreased by 9.60, 15.73 and 11.58%, respectively, in fitting performance; in terms of prediction performance, the MAE, MSE and MAPE decreased by 31.63, 45.79 and 29.59%, respectively. CONCLUSIONS The time series of human brucellosis in Shanxi Province from 2007 to 2017 showed obvious seasonal characteristics. The fitting and prediction performances of the ARIMA-ERNN model were better than those of the ARIMA-BPNN and ARIMA models. This will provide some theoretical support for the prediction of infectious diseases and will be beneficial to public health decision making.
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Affiliation(s)
- Mengmeng Zhai
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Wenhan Li
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Ping Tie
- Endemic Disease Prevention and Control Section, Shanxi Center for Disease Control and Prevention, Taiyuan City, Shanxi Province China
| | - Xuchun Wang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Tao Xie
- Department of Mathematical Statistics, School of Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi Province China
| | - Hao Ren
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Zhuang Zhang
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Weimei Song
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Dichen Quan
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Meichen Li
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
| | - Limin Chen
- Shanxi Provincial Peoples Hospital, Taiyuan City, Shanxi Province China
| | - Lixia Qiu
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan City, Shanxi Province China
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Sun JM, Wu HX, Lu L, Liu Y, Mao ZY, Ren JP, Yao WW, Qu HH, Liu QY. Factors associated with spatial distribution of severe fever with thrombocytopenia syndrome. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 750:141522. [PMID: 32846249 DOI: 10.1016/j.scitotenv.2020.141522] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 08/03/2020] [Accepted: 08/04/2020] [Indexed: 06/11/2023]
Abstract
Severe fever with thrombocytopenia syndrome (SFTS) was firstly identified in mainland China in 2009 and the geographic distribution has expanded in recent years. In this study, we constructed ecological niche models (ENM) of SFTS with meteorological factors, environmental factor, and density of domestic animals using MaxEnt. We found four significant associated factors including altitude, yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity which accounted for 94.1% percent contribution. SFTS occurrence probability was high when altitude was between -100 m and 100 m, and the probability was nearly 0 when altitude was beyond 3000 m. Response curves of SFTS to the yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity were all reversed V-shape. SFTS occurrence probability was high where the yearly average temperature, yearly accumulated precipitation, and yearly relative humidity were 12.5-17.5 °C, 700-2250 mm and 63-82%, respectively. ENMs predicted that the potential high-risk areas were mainly distributed in eastern areas and central areas of China. But there were some predicted potential high-risk areas where no SFTS case was reported up to date. More researches should be done to make clear whether SFTS case had occurred in these areas.
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Affiliation(s)
- Ji-Min Sun
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, China
| | - Hai-Xia Wu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, China
| | - Ying Liu
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, China
| | | | - Jiang-Ping Ren
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, China
| | - Wen-Wu Yao
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, China
| | - Hong-Hua Qu
- Qilu Hospital of Shandong University, China.
| | - Qi-Yong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, China.
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Alim M, Ye GH, Guan P, Huang DS, Zhou BS, Wu W. Comparison of ARIMA model and XGBoost model for prediction of human brucellosis in mainland China: a time-series study. BMJ Open 2020; 10:e039676. [PMID: 33293308 PMCID: PMC7722837 DOI: 10.1136/bmjopen-2020-039676] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVES Human brucellosis is a public health problem endangering health and property in China. Predicting the trend and the seasonality of human brucellosis is of great significance for its prevention. In this study, a comparison between the autoregressive integrated moving average (ARIMA) model and the eXtreme Gradient Boosting (XGBoost) model was conducted to determine which was more suitable for predicting the occurrence of brucellosis in mainland China. DESIGN Time-series study. SETTING Mainland China. METHODS Data on human brucellosis in mainland China were provided by the National Health and Family Planning Commission of China. The data were divided into a training set and a test set. The training set was composed of the monthly incidence of human brucellosis in mainland China from January 2008 to June 2018, and the test set was composed of the monthly incidence from July 2018 to June 2019. The mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to evaluate the effects of model fitting and prediction. RESULTS The number of human brucellosis patients in mainland China increased from 30 002 in 2008 to 40 328 in 2018. There was an increasing trend and obvious seasonal distribution in the original time series. For the training set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)12 model were 338.867, 450.223 and 10.323, respectively, and the MAE, RSME and MAPE of the XGBoost model were 189.332, 262.458 and 4.475, respectively. For the test set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)12 model were 529.406, 586.059 and 17.676, respectively, and the MAE, RSME and MAPE of the XGBoost model were 249.307, 280.645 and 7.643, respectively. CONCLUSIONS The performance of the XGBoost model was better than that of the ARIMA model. The XGBoost model is more suitable for prediction cases of human brucellosis in mainland China.
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Affiliation(s)
- Mirxat Alim
- Department of Epidemiology, China Medical University, Shenyang, China
| | - Guo-Hua Ye
- Department of Epidemiology, China Medical University, Shenyang, China
| | - Peng Guan
- Department of Epidemiology, China Medical University, Shenyang, China
| | - De-Sheng Huang
- Department of Mathematics, China Medical University, Shenyang, China
| | - Bao-Sen Zhou
- Department of Epidemiology, China Medical University, Shenyang, China
| | - Wei Wu
- Department of Epidemiology, China Medical University, Shenyang, China
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Zhou K, Wu B, Pan H, Paudyal N, Jiang J, Zhang L, Li Y, Yue M. ONE Health Approach to Address Zoonotic Brucellosis: A Spatiotemporal Associations Study Between Animals and Humans. Front Vet Sci 2020; 7:521. [PMID: 32984409 PMCID: PMC7492289 DOI: 10.3389/fvets.2020.00521] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 07/07/2020] [Indexed: 12/21/2022] Open
Abstract
Background: Brucellosis is one of the most significant zoonosis over the world, threatening both veterinary and human public health. However, few studies were focused on nationwide animal brucellosis and made association with human brucellosis. Methodology and Principal Findings: We conducted a bilingual literature search on Brucella or brucellosis in China on the two largest databases (China National Knowledge Infrastructure and PubMed) and conducted a systematic review. A total of 1,383 Chinese and 81 English publications, published between 1958 and 2018 were identified. From them, 357 publications presenting 692 datasets were subjected to the meta-analysis. The overall prevalence rate is 1.70% (95% CI: 1.66-1.74), with a declining (until the late 1990s) and rising trend (starting the early 2000s). Interestingly, the animal with highest prevalence rate is canine (8.35%, 95% CI: 7.21-9.50), and lowest in cattle (1.22%, 95% CI: 1.17-1.28). The prevalence of Brucella in animals was unequally distributed among the 24 examined regions in China. Conclusions: Brucellosis is a reemerging disease for both humans and animals in China. The observed data suggests that dogs and yaks are the leading reservoirs for Brucella, and the provinces with highest prevalence rates in animals are Hubei, Sichuan, Inner Mongolia, Fujian, and Guizhou. Accordingly targeted intervention policy should be implemented to break the Brucella transmission chain between animals and humans in China.
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Affiliation(s)
- Kun Zhou
- Department of Veterinary Medicine & Institute of Veterinary Sciences, Zhejiang University College of Animal Sciences, Hangzhou, China
| | - Beibei Wu
- Zhejiang Province Center for Disease Control and Prevention, Hangzhou, China
| | - Hang Pan
- Department of Veterinary Medicine & Institute of Veterinary Sciences, Zhejiang University College of Animal Sciences, Hangzhou, China
| | - Narayan Paudyal
- Animal Health Research Division, Nepal Agricultural Research Council, Kathmandu, Nepal
| | - Jize Jiang
- College of Computer Science, Sichuan University, Chengdu, China
| | - Le Zhang
- College of Computer Science, Sichuan University, Chengdu, China
| | - Yan Li
- Department of Veterinary Medicine & Institute of Veterinary Sciences, Zhejiang University College of Animal Sciences, Hangzhou, China
- Zhejiang Provincial Laboratory of Preventive Veterinary Medicine, Hangzhou, China
| | - Min Yue
- Department of Veterinary Medicine & Institute of Veterinary Sciences, Zhejiang University College of Animal Sciences, Hangzhou, China
- Zhejiang Provincial Laboratory of Preventive Veterinary Medicine, Hangzhou, China
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Zhang Q, Li C, Wang Y, Li Y, Han X, Zhang H, Wang D, Liao Y, Chen Z. Temporal and spatial distribution trends of human brucellosis in Liaoning Province, China. Transbound Emerg Dis 2020; 68:747-757. [PMID: 32696554 DOI: 10.1111/tbed.13739] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 07/11/2020] [Accepted: 07/11/2020] [Indexed: 10/23/2022]
Abstract
Brucellosis is a natural epidemic zoonotic disease. Liaoning province, north-east of China, has been among the top 10 provinces with highest brucellosis incidence. In this study, the spatial and temporal distribution of brucellosis in Liaoning Province from 2006 through 2017 was analysed using the Bayesian theory of space-time modelling. The study found that in Liaoning Province, (a) all regions of the entire study area were stable counties; (b) the risk of brucellosis declined slowly with time without an obvious trend; (c) the declining trend of disease risk in three sub-hot-spot counties was faster than the overall trend, whereas in other counties, the trend was similar to the overall trend. Furthermore, the time and spatial trends of brucellosis incidence in Liaoning Province were calculated and analysed. These results may provide a theoretical and scientific basis for the public health department to develop targeted effective prevention and control measures for the disease.
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Affiliation(s)
- Qi Zhang
- Key Laboratory of Zoonotic of Liaoning Province, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, Liaoning Province, P. R. China
| | - Chunlin Li
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, P. R. China
| | - Ying Wang
- Plague and Brucellosis Prevention and Control Base, Chinese Center for Disease Control and Prevention, Baicheng, P. R. China
| | - Ye Li
- Plague and Brucellosis Prevention and Control Base, Chinese Center for Disease Control and Prevention, Baicheng, P. R. China
| | - Xiaohu Han
- Key Laboratory of Zoonotic of Liaoning Province, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, Liaoning Province, P. R. China
| | - Huan Zhang
- Key Laboratory of Zoonotic of Liaoning Province, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, Liaoning Province, P. R. China
| | - Dali Wang
- Plague and Brucellosis Prevention and Control Base, Chinese Center for Disease Control and Prevention, Baicheng, P. R. China
| | - Yilan Liao
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, P. R. China
| | - Zeliang Chen
- Key Laboratory of Zoonotic of Liaoning Province, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, Liaoning Province, P. R. China.,School of Public Health, Sun Yat-sen University, Guangzhou, P. R. China
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Yang H, Zhang S, Wang T, Zhao C, Zhang X, Hu J, Han C, Hu F, Luo J, Li B, Zhao W, Li K, Wang Y, Zhen Q. Epidemiological Characteristics and Spatiotemporal Trend Analysis of Human Brucellosis in China, 1950-2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E2382. [PMID: 32244493 PMCID: PMC7178157 DOI: 10.3390/ijerph17072382] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 03/25/2020] [Accepted: 03/28/2020] [Indexed: 12/14/2022]
Abstract
The rate of brucellosis, a zoonotic disease, has rapidly increased in humans brucellosis(HB) in recent years. In 1950-2018, a total of 684,380 HB cases (median 2274/year (interquartile range (IQR) 966-8325)) were reported to the National Infectious Disease Surveillance System in mainland China. The incidence of HB peaked in 2014 (4.32/100,000), and then showed a downward trend; we predict that it will maintain a steady downward trend in 2019-2020. Since 2015, the incidence of HB has shown opposite trends in the north and south of China; rates in the north have fallen and rates in the south have increased. In 2004-2018, the most significant increases in incidence of HB were in Yunnan (IQR 0.002-0.463/100,000), Hubei (IQR 0.000-0.338/100,000), and Guangdong (IQR 0.015-0.350/100,000). The areas where HB occurs have little overlap with areas with high per capita GDP in China. The "high-high" clusters of HB are located in northeastern China (Inner Mongolia, Heilongjiang, Jilin, Liaoning, Ningxia, Shanxi, and Gansu), and the "low-low" clusters of HB are located in southern China (Yunnan, Jiangxi, Shanghai, Guangxi, Guangdong, Zhejiang, Guizhou, and Hunan). In recent years, the incidence of HB in China has been controlled to some extent, but the incidence of HB has increased in southern China, and the disease has spread geographically in China from north to south. Further research is needed to address this change and to continue to explore the relationship between the incidence of HB and relevant factors.
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Affiliation(s)
- Huixin Yang
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Siwen Zhang
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Taijun Wang
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Chenhao Zhao
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Xiangyi Zhang
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Jing Hu
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Chenyu Han
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Fangfang Hu
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Jingjing Luo
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Biao Li
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
| | - Wei Zhao
- Jilin Provincial Center for Disease Control and Prevention, Microbiological laboratory, Changchun 130000, China; (W.Z.); (K.L.)
| | - Kewei Li
- Jilin Provincial Center for Disease Control and Prevention, Microbiological laboratory, Changchun 130000, China; (W.Z.); (K.L.)
| | - Ying Wang
- Jilin Province First Institute of Endemic Disease Control, Brucellosis Research Laboratory, Changchun 130000, China;
| | - Qing Zhen
- Jilin University School of Public Health, Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis Research, Ministry of Education, Changchun 130000, China; (H.Y.); (S.Z.); (T.W.); (C.Z.); (X.Z.); (J.H.); (C.H.); (F.H.); (J.L.); (B.L.)
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Li D, Li L, Zhai J, Wang L, Zhang B. Epidemiological features of human brucellosis in Tongliao City, Inner Mongolia province, China: a cross-sectional study over an 11-year period (2007-2017). BMJ Open 2020; 10:e031206. [PMID: 31900267 PMCID: PMC6955466 DOI: 10.1136/bmjopen-2019-031206] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES To describe the epidemiology of human brucellosis in the past decade and provide evidence of disease control in Tongliao city, which is one of the highest-risk areas of human brucellosis in Inner Mongolia province, China. DESIGN Cross-sectional study. PARTICIPANTS Clinically and bacteriologically confirmed human brucellosis cases. PRIMARY AND SECONDARY OUTCOME MEASURES An analysis of the reported cases of human brucellosis during 2007-2017 was carried out to describe the age, sex and occupational distributions of the cases. The time series analysis model and the geographical information system were explored to describe the seasonality and spatiotemporal distribution, respectively, at the county level. RESULTS A total of 13 938 cases of human brucellosis was collected in Tongliao from 2007 to 2017; the majority was aged 25 years to 59 years (85.4%) and the male-to-female ratio was 2.64:1; most of them were agriculturalists (81.9%) and pastoralists (12.4%). The incidence rates increased dramatically from 9.22/100 000 in 2007 to 69.16/100 000 in 2011 with an annual increase of 14.99%. They decreased during 2012-2016 (annual decrease of 8.37%) and rose again in 2017 (44.32/100 000). The disease peaked during March-July, with a clear periodicity and trend of monthly anterior displacement since 2012. Jarud Banner, the region located in the north-west of Tongliao, had the highest accumulated incidence rate (130.1/100 000) compared with other counties. The high-risk regions were spread from the north-west to the south and east of Tongliao during the past decade. CONCLUSIONS The prevalence of human brucellosis in Tongliao was aggravated during the past decade and peaked during March-July. High-risk areas were mainly concentrated in the counties with extensive prairies and livestock.
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Affiliation(s)
- Di Li
- Department of Anatomy, The Medical College of Inner Mongolia University for the Nationalities, Tongliao, Inner Mongolia, China
| | - Lifei Li
- Department of Respiratory Medicine, Affiliated Hospital of Inner Mongolia University for The Nationalities, Tongliao, Inner Mongolia, China
| | - Jingbo Zhai
- Brucellosis Prevention and Treatment Engineering, Technology Research Center of Mongolia Autonomous region, Tongliao, Inner Mongolia, China
| | - Lingzhan Wang
- Institute of Applied Anatomy, The Medical College of Inner Mongolia University for the Nationalities, Tongliao, Inner Mongolia, China
| | - Bin Zhang
- Department of Thoracic Surgery, Affiliated Hospital of Inner Mongolia University for The Nationalities, Tongliao, Inner Mongolia, China
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Prediction of Human Brucellosis in China Based on Temperature and NDVI. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16214289. [PMID: 31694212 PMCID: PMC6862670 DOI: 10.3390/ijerph16214289] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 10/27/2019] [Accepted: 10/29/2019] [Indexed: 11/19/2022]
Abstract
Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.
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Faramarzi H, Nasiri M, Khosravi M, Keshavarzi A, Rezaei Ardakani AR. Potential Effects of Climatic Parameters on Human Brucellosis in Fars Province, Iran, during 2009-2015. IRANIAN JOURNAL OF MEDICAL SCIENCES 2019; 44:465-473. [PMID: 31875081 PMCID: PMC6885718 DOI: 10.30476/ijms.2019.44968] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Revised: 03/03/2018] [Accepted: 05/13/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND Human brucellosis is widespread in Fars province. The present study aimed to investigate the effect of climate on its incidence and determine the areas prone to the infection. METHODS Monthly meteorological data and the incidence rate of human brucellosis during 2009-2015 were collected and their correlation was studied using Pearson's correlation coefficient. Additionally, the multiple regression method and multi-layer perceptron neural network model were used to predict the incidence of human brucellosis. In order to analyze the data SPSS software (version 16.0), MATLAB software (version 8.1), and GIS software (version 10.4) were used. RESULTS Pearson's regression analysis, on a monthly basis, showed a significant indirect correlation between the incidence of human brucellosis (with a time lag of up to 5 months) and climatic parameters (minimum temperature: -0.72 and evaporation: -0.73) in Abadeh (Fars, Iran). Moreover, there was a significant direct correlation (P<0.001) between the incidence of human brucellosis and the maximum relative humidity (+0.67) and rainfall (+0.48). The incidence of human brucellosis in Abadeh was predicted by using artificial neural network models (4 layers, 4 neurons in each layer), the Levenberg-Marquardt training algorithm, and Sigmoid transfer function. It was determined that a correlation rate of 0.89 in the training level and 0.8 in the test level (with the lowest error rate) were the best values in multi-layer perceptron modeling. CONCLUSION Climatic parameters are important factors in determining the incidence rate of human brucellosis in Fars province. Climate conditions provide a favorable environment for the spread of human brucellosis in this area.
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Affiliation(s)
- Hossein Faramarzi
- Department of Community Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Maryam Nasiri
- Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, Iran
| | - Mahmood Khosravi
- Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, Iran
| | - Abouzar Keshavarzi
- Department of Health Education and Promotion, Shiraz University of Medical Sciences, Shiraz, Iran
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Yespembetov BA, Syrym NS, Syzdykov MS, Kuznetsov AN, Koshemetov ZK, Mussayeva AK, Basybekov SZ, Kanatbayev SG, Mankibaev AT, Romashev CM. Impact of geographical factors on the spread of animal brucellosis in the Republic of Kazakhstan. Comp Immunol Microbiol Infect Dis 2019; 67:101349. [PMID: 31525572 DOI: 10.1016/j.cimid.2019.101349] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 08/09/2019] [Accepted: 08/30/2019] [Indexed: 11/24/2022]
Abstract
In Latin and Central America and in most Asian countries, brucellosis remains an insufficiently studied disease. This study aims to determine the national and regional incidence of brucellosis among cattle (cows) and small ruminants (sheep, goats) in the Republic of Kazakhstan, as well as to identify the effect of climatic and geographical factors on the incidence rates. Thematic maps were created in an open geographic information system QGIS version 2.8. in order to identify the natural and socio-economic factors that influence the spread of the disease overlay method was used. Local cluster analysis was used in order to identify additional causes of the disease. Findings show the following values of Pearson correlation between the overall population and the number of animals infected: 0.68 for cows, p ≤ 0.005, and 0.56 for sheep and goats, p ≤ 0.03. Thus, the larger the heard in a given area, the greater likelihood of having brucellosis. Data processing reveals that Kazakhstan has almost twice as many regions good for cattle breeding as regions that are good for the small ruminants farming. The correlation variables for cattle and small ruminants are approximately the same. On the basis of the performed research the author proposes to amend the accepted methodology of epidemiology surveillance by the methods based on spatial (geographical) analysis. It is also proposed to adjust the process of breeding cattle and small ruminants considering the additional health recommendations that take into account the geographical aspects of the spread of the disease.
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Affiliation(s)
| | - Nazym S Syrym
- Research Institute for Biological Safety Problems, Kazakhstan.
| | - Marat S Syzdykov
- M. Aikimbayev Kazakh Scientific Centre for Quarantine and Zoonotic Diseases, Kazakhstan
| | - Andrey N Kuznetsov
- M. Aikimbayev Kazakh Scientific Centre for Quarantine and Zoonotic Diseases, Kazakhstan
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21
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Jara M, Escobar LE, Rodriges RO, Frias-De-Diego A, Sanhueza J, Machado G. Spatial distribution and spread potential of sixteen Leptospira serovars in a subtropical region of Brazil. Transbound Emerg Dis 2019; 66:2482-2495. [PMID: 31342664 DOI: 10.1111/tbed.13306] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 07/11/2019] [Accepted: 07/17/2019] [Indexed: 12/14/2022]
Abstract
Leptospirosis is a bacterial disease that represents a major problem in animal and public health due to its high prevalence and widespread distribution. This zoonotic disease is most prevalent in tropical environments where conditions favour pathogen survival. The ecological preferences of Leptospira serovars are poorly understood, limiting our knowledge of where and when outbreaks can occur, which may result in misinformed prevention and control plans. While the disease can occur consistently in time and space in tropical regions, research on the ecology of leptospirosis remains limited in subtropical regions. This research gap regarding Leptospira ecology brings public and veterinary health problems, impacting local economies. To fill this gap of knowledge, we suggest to assess geographic and ecological features among Leptospira serovars in a subtropical area of Brazil where leptospirosis is endemic to (a) highlight environmental conditions that facilitate or limit Leptospira spread and survival and (b) reconstruct its geographic distribution. An ecological niche modelling framework was used to characterize and compare Leptospira serovars in both geographic and environmental space. Our results show that despite the geographic overlap exhibited by the different serovars assessed, we found ecological divergence among their occupied ecological niches. Ecological divergences were expressed as ranges of potential distributions and environmental conditions found suitably by serovar, Sejroe being the most asymmetric (<0.15). Most important predictors for the potential distribution of most serovars were soil pH (31.7%) and landscape temperature (24.2%). Identification of environmental preferences will allow epidemiologists to better infer the presence of a serovar based on the environmental characteristics of regions rather than inferences based solely on historical epidemiological records. Including geographic and ecological ranges of serovars also may help to forecast transmission potential of Leptospira in public health and the food animal practice.
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Affiliation(s)
- Manuel Jara
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, USA
| | - Luis E Escobar
- Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia, USA
| | - Rogério O Rodriges
- Desidério Finamor Veterinary Research Institute, Diagnostic and Agricultural Research Department of Agriculture, Livestock and Irrigation (DDPA/SEAPI), Porto Alegre, Brazil
| | - Alba Frias-De-Diego
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, USA
| | - Juan Sanhueza
- Veterinary Population Medicine Department, College of Veterinary Medicine, University of Minnesota, St Paul, Minnesota, USA
| | - Gustavo Machado
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, USA
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22
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Lin Y, Xu M, Zhang X, Zhang T. An exploratory study of factors associated with human brucellosis in mainland China based on time-series-cross-section data from 2005 to 2016. PLoS One 2019; 14:e0208292. [PMID: 31199806 PMCID: PMC6568380 DOI: 10.1371/journal.pone.0208292] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 05/28/2019] [Indexed: 11/28/2022] Open
Abstract
Objective Many studies focused on reasons behind the increasing incidence and the spread of human brucellosis in mainland China, yet most of them lacked comprehensive consideration with quantitative evidence. Hence, this study aimed to further investigate the epidemic mechanism and associated factors of human brucellosis so as to provide thoughts for future countermeasures in China and the rest of the world. Methods Data of human brucellosis incidence and some associated factors in economy, animal husbandry, transportation as well as health and hygiene were collected at provincial level from 2005–2016. Time series plots were first used to visualize the annual incidence and annual rate of change of human brucellosis for each province, then cluster analysis categorized all the 31 provinces of mainland China based on their incidence time series during the study period. In addition, according to the characteristics of data, the dynamic panel data model in combination with supervised principal component analysis was proposed to explore effects of associated factors on human brucellosis. Results 1. The incidence rate of human brucellosis in mainland China increased three-fold from 1.41 per 100,000 people in 2005 to 4.22 per 100,000 people in 2014, though it went down a little in 2015 and 2016. Incidence rates in the north have always been higher than those in the south, but the latter also experienced an upward trend especially between 2012 and 2016. 2. The 31 provinces of mainland China were categorized into three clusters, and each cluster had its own characteristics of incidence time series. 3. The impact of health and hygiene situations on the prevention and control work of human brucellosis was still very limited and trivial (regression coefficient = -0.02). Therefore, it was plausible to presume that improving the personal average number of medical institutes and the proportion of rural medical expenditure might be helpful in preventing and controlling human brucellosis. Conclusions The epidemic status of human brucellosis has changed in both spatial and temporal dimensions in recent years in mainland China. Apart from traditional control measures, more attention should be paid to the improvement of medical healthcare especially in rural areas in the hope of enhancing the control effect.
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Affiliation(s)
- Yun Lin
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Minghan Xu
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xingyu Zhang
- Applied Biostatistics Laboratory, University of Michigan School of Nursing, Ann Arbor, Michigan, United States of America
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- * E-mail:
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23
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Zhao M, Huang F, Zhang A, Zhang B, Zeng L, Xu J, Wang J. Congenital brucellosis in a Chinese preterm neonate: A case report. J Int Med Res 2019; 47:2296-2301. [PMID: 30971153 PMCID: PMC6567740 DOI: 10.1177/0300060519838921] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Although extremely rare, congenital brucellosis can occur via perinatal transmission. We report a case of an infant born prematurely at 34–36 weeks' gestation who had pyrexia, shortness of breath, hepatosplenomegaly and thrombocytopenia. Blood cultures were positive for Gram-negative coccobacilli and Brucella infection was suspected. While, serological tests were negative for Brucella antibodies, B. melitensis infection was confirmed by polymerase chain reaction (PCR). Serology of the parents’ blood confirmed the presence of Brucella. The family did not live in an endemic area but had ridden a camel 12 months before the pregnancy. The bacteria may have been sexually transmitted from father to mother and then to foetus via an intrauterine infection. In endemic areas or where the family has been in close contact with infected animals, brucellosis should be suspected in a severely ill neonate with an unknown infection. Thorough medical histories from the family are essential as early diagnosis and prompt therapy will almost certainly improve neonatal outcome.
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Affiliation(s)
- Menghua Zhao
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Furong Huang
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Aimin Zhang
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Bing Zhang
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Ling Zeng
- 2 Department of Clinical Laboratory, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Jun Xu
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Juanmei Wang
- 1 Children's Medical Centre, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
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24
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Blackburn JK, Ganz HH, Ponciano JM, Turner WC, Ryan SJ, Kamath P, Cizauskas C, Kausrud K, Holt RD, Stenseth NC, Getz WM. Modeling R₀ for Pathogens with Environmental Transmission: Animal Movements, Pathogen Populations, and Local Infectious Zones. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E954. [PMID: 30884913 PMCID: PMC6466347 DOI: 10.3390/ijerph16060954] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2018] [Revised: 03/04/2019] [Accepted: 03/07/2019] [Indexed: 01/24/2023]
Abstract
How a disease is transmitted affects our ability to determine R₀, the average number of new cases caused by an infectious host at the onset of an epidemic. R₀ becomes progressively more difficult to compute as transmission varies from directly transmitted diseases to diseases that are vector-borne to environmentally transmitted diseases. Pathogens responsible for diseases with environmental transmission are typically maintained in environmental reservoirs that exhibit a complex spatial distribution of local infectious zones (LIZs). Understanding host encounters with LIZs and pathogen persistence within LIZs is required for an accurate R₀ and modeling these contacts requires an integrated geospatial and dynamical systems approach. Here we review how interactions between host and pathogen populations and environmental reservoirs are driven by landscape-level variables, and synthesize the quantitative framework needed to formulate outbreak response and disease control.
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Affiliation(s)
- Jason K Blackburn
- Spatial Epidemiology and Ecology Research Laboratory, Department of Geography, University of Florida, 3141 Turlington Hall, Gainesville, FL 32611, USA.
- Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, Gainesville, FL 32611, USA.
| | - Holly H Ganz
- Davis Genome Center, University of California, 451 Health Sciences Dr., Davis, CA 95616, USA.
| | | | - Wendy C Turner
- Department of Biological Sciences, State University of New York, 1400 Washington Avenue, Albany, NY 12222, USA.
| | - Sadie J Ryan
- Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, Gainesville, FL 32611, USA.
- Quantitative Disease Ecology & Conservation Lab, Department of Geography, University of Florida, 3141 Turlington Hall, Gainesville, FL 32611, USA.
- School of Life Sciences, University of KwaZulu-Natal, Durban 4041, South Africa.
| | - Pauline Kamath
- School of Food and Agriculture, University of Maine, 5763 Rogers Hall, Room 210, Orono, ME 04469, USA.
| | - Carrie Cizauskas
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, 130 Mulford Hall, Berkeley, CA 94720, USA.
| | - Kyrre Kausrud
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, P.O. Box 1066 Blindern, 0361 Oslo, Norway.
| | - Robert D Holt
- Department of Biology, University of Florida, Gainesville, FL 32611, USA.
| | - Nils Chr Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, P.O. Box 1066 Blindern, 0361 Oslo, Norway.
| | - Wayne M Getz
- School of Food and Agriculture, University of Maine, 5763 Rogers Hall, Room 210, Orono, ME 04469, USA.
- School of Mathematical Sciences, University of KwaZulu-Natal, Durban 4041, South Africa.
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25
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Jia P, Xue H, Yin L, Stein A, Wang M, Wang Y. Spatial Technologies in Obesity Research: Current Applications and Future Promise. Trends Endocrinol Metab 2019; 30:211-223. [PMID: 30712979 DOI: 10.1016/j.tem.2018.12.003] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 12/09/2018] [Accepted: 12/16/2018] [Indexed: 11/25/2022]
Abstract
Geographic Information Systems (GIS), Global Positioning Systems (GPS), and remote sensing (RS) are revolutionizing obesity-related research. The primary applications of GIS have included visualizing obesity outcomes and risk factors, constructing obesogenic environmental indicators, and detecting geographical patterns of obesity prevalence and obesogenic environmental features. GPS was mainly used to delineate individual activity space and combined with other devices to measure obesogenic behaviors. RS has been understated for its role as important sources of data about natural and built environments. These spatial technologies, collectively called the 3S technologies, will be useful in measuring more facets of obesogenic environments and individual environmental exposure at finer levels and studying obesity etiology and interventions.
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Affiliation(s)
- Peng Jia
- Department of Earth Observation Science, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, 7500, The Netherlands; International Initiative on Spatial Lifecourse Epidemiology (ISLE), Enschede, 7500, The Netherlands.
| | - Hong Xue
- Department of Health Behavior and Policy, School of Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Li Yin
- Department of Urban and Regional Planning, University at Buffalo, The State University of New York, Buffalo, NY 14214, USA
| | - Alfred Stein
- Department of Earth Observation Science, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, 7500, The Netherlands
| | - Minqi Wang
- Department of Behavioral and Community Health, University of Maryland at College Park, College Park, MD 20742, USA
| | - Youfa Wang
- Global Health Institute, Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, China.
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26
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Jia P, Stein A, James P, Brownson RC, Wu T, Xiao Q, Wang L, Sabel CE, Wang Y. Earth Observation: Investigating Noncommunicable Diseases from Space. Annu Rev Public Health 2019; 40:85-104. [PMID: 30633713 DOI: 10.1146/annurev-publhealth-040218-043807] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The United Nations has called on all nations to take immediate actions to fight noncommunicable diseases (NCDs), which have become an increasingly significant burden to public health systems around the world. NCDs tend to be more common in developed countries but are also becoming of growing concern in low- and middle-income countries. Earth observation (EO) technologies have been used in many infectious disease studies but have been less commonly employed in NCD studies. This review discusses the roles that EO data and technologies can play in NCD research, including ( a) integrating natural and built environment factors into NCD research, ( b) explaining individual-environment interactions, ( c) scaling up local studies and interventions, ( d) providing repeated measurements for longitudinal studies including cohorts, and ( e) advancing methodologies in NCD research. Such extensions hold great potential for overcoming the challenges of inaccurate and infrequent measurements of environmental exposure at the level of both the individual and the population, which is of great importance to NCD research, practice, and policy.
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Affiliation(s)
- Peng Jia
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands; .,International Initiative on Spatial Lifecourse Epidemiology (ISLE), 7500 AE Enschede, The Netherlands
| | - Alfred Stein
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands;
| | - Peter James
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts 02215, USA
| | - Ross C Brownson
- Prevention Research Center in St. Louis, Brown School; Department of Surgery and Alvin J. Siteman Cancer Center, Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Tong Wu
- School of Life Sciences, Arizona State University, Tempe, Arizona 85287-4701, USA
| | - Qian Xiao
- Department of Health and Human Physiology, University of Iowa, Iowa City, Iowa 52242-1111, USA
| | - Limin Wang
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Clive E Sabel
- Department of Environmental Science, Aarhus University, DK-4000 Roskilde, Denmark.,Danish Big Data Centre for Environment and Health (BERTHA), DK-4000 Roskilde, Denmark
| | - Youfa Wang
- Global Health Institute; and Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710049, China
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Ran X, Cheng J, Wang M, Chen X, Wang H, Ge Y, Ni H, Zhang XX, Wen X. Brucellosis seroprevalence in dairy cattle in China during 2008-2018: A systematic review and meta-analysis. Acta Trop 2019; 189:117-123. [PMID: 30308207 DOI: 10.1016/j.actatropica.2018.10.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 10/03/2018] [Accepted: 10/05/2018] [Indexed: 02/08/2023]
Abstract
Brucellosis remains one of the most common zoonotic diseases globally with more than a half million human cases reported annually. The Brucella reservoir associated with livestock brucellosis poses a significant threat to public health, and awareness of the seroprevalence and spatial distribution of livestock brucellosis is valuable for the prevention and control of diseases caused by Brucella, especially human brucellosis. Therefore, we conducted a systematic review and meta-analysis to evaluate the seroprevalence of brucellosis in dairy cattle in China. We retrieved 88 studies related to the seroprevalence of brucellosis in dairy cattle in China in which samples were harvested between 2008 and 2018. The results of our systematic review and meta-analysis reveal that the overall seroprevalence of brucellosis in dairy cattle herds in China was 1.9% during the selected period, rising from 1.6% in 2008-2012 to 2.6% in 2013-2018. In Northern China, where the traditional agropastoral areas with more developed animal breeding industry are located, the brucellosis seroprevalence was >10%. In contrast, the seroprevalence of brucellosis in Southern China reached only 5.5%. At the provincial level, the highest brucellosis seroprevalence in dairy cattle was estimated at >30% in Jilin province, followed by Shanxi, Ningxia, Inner Mongolia, and Guizhou, each with a prevalence of 10-20%. Additionally, the seroprevalence of brucellosis in some local areas was >30% or even >50%, indicating that Brucella infection was highly endemic in dairy herds in China. Our data may facilitate the prevention and control of brucellosis in domestic animals in China. Further epidemiological surveillance and the administration of a comprehensive monitoring program to determine the risk factors associated with brucellosis incidence in humans and domestic animals are recommended to refine brucellosis control strategies.
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28
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Shi Y, Gao H, Pappas G, Chen Q, Li M, Xu J, Lai S, Liao Q, Yang W, Yi Z, Rouzi Z, Yu H. Clinical features of 2041 human brucellosis cases in China. PLoS One 2018; 13:e0205500. [PMID: 30476930 PMCID: PMC6258468 DOI: 10.1371/journal.pone.0205500] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 09/26/2018] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Human brucellosis has become a major public health problem in China. However, the available clinical data on brucellosis cases are limited. METHODS We retrospectively reviewed medical charts of 2041 patients with confirmed human brucellosis and prospectively recorded their outcomes by telephone interview. These patients were admitted to the Sixth People's Hospital of the Xinjiang Uygur Autonomous region between 1st January and 31st December 2014. Data on these patients were collected from hospital medical records. RESULTS Many patients presented with fatigue (67%), fever (64%), arthralgia (63%) and sweating (54%). High erythrocyte sedimentation rate (ESR) (69%), high C-reactive protein (CRP) (39%), high alanine aminotransferase (ALT) (33%) and high aspartate aminotransferase (AST) (20%) were the most common laboratory findings, especially in acute patients. There was evidence of focal involvement in 90% of patients. A total of 61.5% of brucellosis patients recovered. Multivariate logistic regression analyses suggested that the risk factors key to unfavorable prognosis were: age≥45 years (OR = 1.75, 95% CI 1.36-2.24), back pain (OR = 1.50, 95% CI 1.16-1.94) and joint tenderness (OR = 1.73, 95% CI 1.13-2.65). The increasing duration of the illness increased the risk of poor prognosis. CONCLUSION Patients with brucellosis showed different characteristics in different clinical stages. In China, the chronicity rate of human brucellosis is high. The risk of poor prognosis is increased in patients aged 45 years or older, patients who have had brucellosis for a substantial period of time, and patients with back pain or joint tenderness. The clinical management of brucellosis should be improved to include sensitive diagnostic methods for subacute and chronic brucellosis.
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Affiliation(s)
- Yujing Shi
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early–warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hui Gao
- The Sixth People's Hospital of the Xinjiang Uygur Autonomous Region, Urumqi, China
| | | | - Qiulan Chen
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early–warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mei Li
- The Sixth People's Hospital of the Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Jun Xu
- The Sixth People's Hospital of the Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Shengjie Lai
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early–warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
| | - Qiaohong Liao
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early–warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenwen Yang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
| | - Zhongtao Yi
- The Sixth People's Hospital of the Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Zulaguli Rouzi
- The Sixth People's Hospital of the Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Hongjie Yu
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early–warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
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Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018. Sci Rep 2018; 8:15901. [PMID: 30367079 PMCID: PMC6203822 DOI: 10.1038/s41598-018-33165-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 09/20/2018] [Indexed: 01/07/2023] Open
Abstract
With the re-emergence of brucellosis in mainland China since the mid-1990s, an increasing threat to public health tends to become even more violent, advanced warning plays a pivotal role in the control of brucellosis. However, a model integrating the autoregressive integrated moving average (ARIMA) with Error-Trend-Seasonal (ETS) methods remains unexplored in the epidemiological prediction. The hybrid ARIMA-ETS model based on discrete wavelet transform was hence constructed to assess the epidemics of human brucellosis from January 2004 to February 2018 in mainland China. The preferred hybrid model including the best-performing ARIMA method for approximation-forecasting and the best-fitting ETS approach for detail-forecasting is evidently superior to the standard ARIMA and ETS techniques in both three in-sample simulating and out-of-sample forecasting horizons in terms of the minimum performance indices of the root mean square error, mean absolute error, mean error rate and mean absolute percentage error. Whereafter, an ahead prediction from March to December in 2018 displays a dropping trend compared to the preceding years. But being still present, in various trends, in the present or future. This hybrid model can be highlighted in predicting the temporal trends of human brucellosis, which may act as the potential for far-reaching implications for prevention and control of this disease.
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Dietrich D, Dekova R, Davy S, Fahrni G, Geissbühler A. Applications of Space Technologies to Global Health: Scoping Review. J Med Internet Res 2018; 20:e230. [PMID: 29950289 PMCID: PMC6041558 DOI: 10.2196/jmir.9458] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/21/2018] [Accepted: 04/22/2018] [Indexed: 12/27/2022] Open
Abstract
Background Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health. Objective The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges. Methods We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified. Results A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use. Conclusions Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.
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Affiliation(s)
- Damien Dietrich
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Ralitza Dekova
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Stephan Davy
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Guillaume Fahrni
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Antoine Geissbühler
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
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31
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Guan P, Wu W, Huang D. Trends of reported human brucellosis cases in mainland China from 2007 to 2017: an exponential smoothing time series analysis. Environ Health Prev Med 2018; 23:23. [PMID: 29921215 PMCID: PMC6010161 DOI: 10.1186/s12199-018-0712-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 05/29/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The main objective of this study was to describe the temporal distribution of monthly reported human brucellosis cases in mainland China and develop an appropriate time series model for short-term extrapolation forecast. METHODS Surveillance data of the monthly reported human brucellosis cases occurring from April 1, 2007, to March 31, 2017, in mainland China were obtained. The spectrum analysis was first adopted to find the cyclic and seasonal features, the existence of the seasonality and trend was determined by exponential smoothing method and the seasonal-trend decomposition. The candidate models of exponential smoothing included the additive model and multiplicative model; R2 was selected as the indicator for the selection of candidate model, and the stability of the model was verified by adjusting the training data and test data set. Finally, the extrapolations of monthly incident human brucellosis cases in 2017 were made. RESULTS From April 1, 2007, to March 31, 2017, a total of 435,108 cases of Brucellosis occurred in mainland China were reported, with an average of 3626 cases per month and a standard deviation of 1834 cases. The R2 of the exponential smoothing method that based on additive model increased steadily from 0.927 to 0.949 with the increase of the data volume. Ten of 12 actual values fell in the confidence interval of predicted value. CONCLUSIONS Human brucellosis cases peaked during the months from March to August in mainland China, with clear seasonality. The exponential smoothing based on the additive model method could be effectively used in the time series analysis of human brucellosis in China. Control methods, such as vaccination, quarantine, elimination of infected animals, and good hygiene within the production cycle, should be strengthened with paying more attention to the seasonality. Further research is warranted to explore the drivers behind the seasonality.
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Affiliation(s)
- Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Wei Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Desheng Huang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China. .,Department of Mathematics, School of Fundamental Sciences, China Medical University, Shenyang, 110122, China.
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32
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A Systematic Review and Meta-Analysis of Epidemiology and Clinical Manifestations of Human Brucellosis in China. BIOMED RESEARCH INTERNATIONAL 2018; 2018:5712920. [PMID: 29850535 PMCID: PMC5937618 DOI: 10.1155/2018/5712920] [Citation(s) in RCA: 104] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 03/01/2018] [Indexed: 12/22/2022]
Abstract
Background. Brucellosis has a wide spectrum of clinical manifestations and it may last several days or even several years; however, it is often misdiagnosed and therefore may cause inadequate therapy and prolonged illness. Previous studies about meta-analysis of manifestations of brucellosis reported in English lacked the data published in Chinese, which did not provide details about the contact history, laboratory tests, and misdiagnosis. We undertake a meta-analysis of clinical manifestations of human brucellosis in China to identify those gaps in the literature. We have searched published articles in electronic databases up to December 2016 identified as relating to clinical features of human brucellosis in China. 68 studies were included in the analysis. The main clinical manifestations were fever, fatigue, arthralgia, and muscle pain (87%, 63%, 62%, and 56%, resp.). There are significant differences between adults and children. Rash, respiratory and cardiac complications, and orchitis/epididymitis were more prevalent in children patients. The common complications of brucellosis were hepatitis, followed by osteoarthritis, respiratory diseases, cardiovascular diseases, central nervous system dysfunction, hemophagocytic syndrome, and orchitis/epididymitis in male. In the nonpastoral areas, brucellosis has a high ratio of misdiagnosis. Our analysis provides further evidence for the accurate diagnosis, particularly in assessing severe, debilitating sequelae of this infection.
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Lai S, Zhou H, Xiong W, Gilbert M, Huang Z, Yu J, Yin W, Wang L, Chen Q, Li Y, Mu D, Zeng L, Ren X, Geng M, Zhang Z, Cui B, Li T, Wang D, Li Z, Wardrop NA, Tatem AJ, Yu H. Changing Epidemiology of Human Brucellosis, China, 1955-2014. Emerg Infect Dis 2018; 23:184-194. [PMID: 28098531 PMCID: PMC5324817 DOI: 10.3201/eid2302.151710] [Citation(s) in RCA: 150] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Brucellosis, a zoonotic disease, was made statutorily notifiable in China in 1955. We analyzed the incidence and spatial–temporal distribution of human brucellosis during 1955–2014 in China using notifiable surveillance data: aggregated data for 1955–2003 and individual case data for 2004–2014. A total of 513,034 brucellosis cases were recorded, of which 99.3% were reported in northern China during 1955–2014, and 69.1% (258, 462/374, 141) occurred during February–July in 1990–2014. Incidence remained high during 1955–1978 (interquartile range 0.42–1.0 cases/100,000 residents), then decreased dramatically in 1979–1994. However, brucellosis has reemerged since 1995 (interquartile range 0.11–0.23 in 1995–2003 and 1.48–2.89 in 2004–2014); the historical high occurred in 2014, and the affected area expanded from northern pastureland provinces to the adjacent grassland and agricultural areas, then to southern coastal and southwestern areas. Control strategies in China should be adjusted to account for these changes by adopting a One Health approach.
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34
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A Remote Sensing Data Based Artificial Neural Network Approach for Predicting Climate-Sensitive Infectious Disease Outbreaks: A Case Study of Human Brucellosis. REMOTE SENSING 2017. [DOI: 10.3390/rs9101018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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He M, Wang J, Chen L, Liu J, Zeng P. The Impact of Emerging Infectious Diseases on Chinese Blood Safety. Transfus Med Rev 2017; 31:94-101. [PMID: 27923518 PMCID: PMC7126663 DOI: 10.1016/j.tmrv.2016.10.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 09/19/2016] [Accepted: 10/24/2016] [Indexed: 12/16/2022]
Abstract
Emerging infectious diseases (EIDs) have always been one of the major threats to public health. Although the implementation of mandatory testing for 4 classical transfusion-transmitted infectious-human immunodeficiency virus, hepatitis B virus, hepatitis C virus, and syphilis-has reduced the transfusion risk of these pathogens, the potential threat of various EID agents and their constantly evolving variants to blood safety in China is not fully understood. This review presents 9 representative EID agents that are autochthonous and epidemic nationally or regionally in China. The epidemiologic status and distribution of these EID agents among donors and/or healthy populations are summarized. The potential risks of these EID agents to blood safety are discussed. The review also explores strategies to strengthen hemovigilance systems and studies to further evaluate the impact of EID agents on blood safety.
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Affiliation(s)
- Miao He
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Jingxing Wang
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Limin Chen
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Jing Liu
- Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Peibin Zeng
- West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
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36
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Ning C, Shuyi G, Tao Y, Hao Z, Zhang X. Epidemiological survey of human brucellosis in Inner Mongolia, China, 2010-2014: A high risk groups-based survey. J Infect Public Health 2017; 11:24-29. [PMID: 28320594 DOI: 10.1016/j.jiph.2017.02.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 02/07/2017] [Accepted: 02/22/2017] [Indexed: 11/16/2022] Open
Abstract
Brucellosis, a zoonosis which can seriously harm public health. Inner Mongolia is known as an endemic region of human brucellosis in China. The aim of this study is to present the epidemic of human brucellosis in Inner Mongolia from 2010 to 2014, and to provide the evidence of preventing from brucellosis in endemic areas. The study included 838,956 participants by cluster random sampling from 2010 to 2014. The contents of this study included questionnaire survey and serological testing. The seropositive rate was calculated based on the serological testing results, tested to determine whether the participants were infected by brucellosis. The new brucellosis cases were diagnosed using the questionnaire data and serological testing results then and the incidence rate was obtained. We also plotted spatial distribution maps based on the seropositive and incidence rate of human brucellosis. The total seropositive and incidence rate of human brucellosis among the high risk groups in Inner Mongolia from 2010 to 2014 was 35.91‰ and 18.25‰, respectively. The epidemic of the mid-eastern Inner Mongolia was decreased, however, the epidemic has worsened in western Inner Mongolia. Despite the epidemic of human brucellosis among the high risk groups of Inner Mongolia decreased significantly from 2010 to 2014, increased prevention and control measures are urgently needed.
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Affiliation(s)
- Cao Ning
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia 010110, China
| | - Guo Shuyi
- People's Hospital of Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia 010110, China
| | - Yan Tao
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia 010110, China
| | - Zhu Hao
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia 010110, China
| | - Xingguang Zhang
- School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia 010110, China.
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Reyes AWB, Hop HT, Arayan LT, Huy TXN, Park SJ, Kim KD, Min W, Lee HJ, Rhee MH, Kwak YS, Kim S. The host immune enhancing agent Korean red ginseng oil successfully attenuates Brucella abortus infection in a murine model. JOURNAL OF ETHNOPHARMACOLOGY 2017; 198:5-14. [PMID: 28012988 DOI: 10.1016/j.jep.2016.12.026] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 12/09/2016] [Accepted: 12/14/2016] [Indexed: 06/06/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Panax ginseng Meyer (Araliaceae), is one of the most valuable traditional Chinese medicines and is used for the treatment of various human diseases. In this study, we elucidated the protective mechanism of the essential oil from Korean red ginseng (RGO) against Brucella infection. MATERIALS AND METHODS The effects of RGO on Brucella abortus viability, NO production, uptake and intracellular growth in macrophages were investigated. Mice were intraperitoneally infected with B. abortus and orally treated with RGO for 14 days. The weights and bacterial numbers from each spleen were monitored, and the sera were evaluated for cytokine production. RESULTS B. abortus viability was not affected, whereas NO production, internalization and intracellular replication were inhibited in RGO-treated macrophages. Bacterial adherence, F-actin polymerization and MAPK signaling protein phosphorylation (ERK1/2, JNK and p38α) were reduced and the co-localization of B. abortus-containing phagosomes with LAMP-1 was augmented in RGO-treated cells compared to untreated cells. RGO displayed protective effects against cell damage by inhibiting nitrite production during B. abortus infection in macrophages. Moreover, the spleen weight and bacterial burden were lower in the RGO-treated group than in the control group. The uninfected RGO-treated mice displayed increased TNF-α and IFN-γ production, whereas the B. abortus-infected RGO-treated mice showed reduced IL-10 production compared to the control. CONCLUSION RGO exhibits protective effects against B. abortus infection in vitro and in vivo, which emphasize the beneficial effects of RGO in the prevention and treatment of brucellosis.
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Affiliation(s)
- Alisha Wehdnesday Bernardo Reyes
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea; Department of Veterinary Paraclinical Sciences, College of Veterinary Medicine, University of the Philippines Los Baños, College, Laguna 4031, Philippines.
| | - Huynh Tan Hop
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Lauren Togonon Arayan
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Tran Xuan Ngoc Huy
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Soo Jong Park
- Division of Applied Life Science (BK21 Plus) and Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Kwang Dong Kim
- Division of Applied Life Science (BK21 Plus) and Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - WonGi Min
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Hu Jang Lee
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
| | - Man Hee Rhee
- College of Veterinary Medicine, Kyungpook National University, Daegu 702-701, Republic of Korea.
| | - Yi-Seong Kwak
- Research Institute of Technology, Korea Ginseng Corporation, Taejon 305-805, Republic of Korea
| | - Suk Kim
- Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Republic of Korea.
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Chen Q, Lai S, Yin W, Zhou H, Li Y, Mu D, Li Z, Yu H, Yang W. Epidemic characteristics, high-risk townships and space-time clusters of human brucellosis in Shanxi Province of China, 2005-2014. BMC Infect Dis 2016; 16:760. [PMID: 27993134 PMCID: PMC5165709 DOI: 10.1186/s12879-016-2086-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2016] [Accepted: 12/02/2016] [Indexed: 01/04/2023] Open
Abstract
Background Brucellosis, one of the world’s most important zoonosis, has been re-emerging in China. Shanxi Province, located in northern China, where husbandry development has been accelerated in recent years, has a rather high incidence of human brucellosis but drew little attention from the researchers. This study aimed to describe the changing epidemiology of human brucellosis in Shanxi Province from 2005 to 2014 and explore high-risk towns and space-time clusters for elucidating the necessity of decentralizing disease control resource to township level in epidemic regions, particularly in hotspot areas. Methods We extracted data from the Chinese National Notifiable Infectious Disease Reporting System to describe the incidence and spatiotemporal distribution of human brucellosis in Shanxi Province. Geographic information system was used to identify townships at high risk for the disease. Space-Time Scan Statistic was applied to detect the space-time clusters of human brucellosis during the past decade. Results From 2005 to 2014, a total of 50,002 cases of human brucellosis were recorded in Shanxi, with a male-to-female ratio of 3.9:1. The reported incidence rate increased dramatically from 7.0/100,000 in 2005 to 23.5/100,000 in 2014, with an average annual increase of 14.5%. There were still 33.8% cases delaying diagnosis in 2014. The proportion of the affected towns increased from 31.5% in 2005 to 82.5% in 2014. High-risk towns spread from the north to the center and then south of Shanxi Province, which were basins and adjacent highlands suitable for livestock cultivation. During the past decade, there were 55 space-time clusters of human brucellosis detected in high risk towns; the clusters could happen in any season. Some clusters’ location maintained stable over time. Conclusions During the last decade, Shanxi province’s human brucellosis epidemic had been aggravated and high-risk areas concentrated in some towns located in basins and adjacent highlands. Space-time clusters existed and some located steadily over time. Quite a few cases still missed timely diagnosis. Greater resources should be allocated and decentralized to mitigate the momentum of rise and improve the accessibility of prompt diagnosis treatment in the high-risk townships. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-2086-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Qiulan Chen
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Shengjie Lai
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,Worldpop Project, Department of Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK
| | - Wenwu Yin
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hang Zhou
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Yu Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Di Mu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hongjie Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Weizhong Yang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
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Zhan BD, Wang SQ, Lai SM, Lu Y, Shi XG, Cao GP, Hu XL, Zheng CJ, Yu ZY, Zhang JM, Fang CF, Gong ZY. Outbreak of Occupational Brucellosis at a Pharmaceutical Factory in Southeast China. Zoonoses Public Health 2016; 64:431-437. [PMID: 27863096 DOI: 10.1111/zph.12322] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Indexed: 01/30/2023]
Abstract
Brucellosis is an occupational disease affecting workers in butcher shops, the milking and dairy product industry, causing more than 500 000 new cases around the world. As a national statutory B infectious disease in China, morbidity of brucellosis is rapidly increasing in recent years. We report an occupational outbreak of brucellosis infection in a pharmaceutical factory. Exposure was a result of manual operation in the process line, close contact with sheep placentas, insufficient disinfection and repeated using of protective suits and infected by aerosol dissemination. Improved preventive methods, appropriate public health measures and spread of health education would be helpful to prevent the occupational outbreak of brucellosis in future.
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Affiliation(s)
- B D Zhan
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - S Q Wang
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - S M Lai
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Y Lu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - X G Shi
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - G P Cao
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - X L Hu
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - C J Zheng
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Z Y Yu
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - J M Zhang
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - C F Fang
- Quzhou Center for Disease Control and Prevention, Quzhou, China
| | - Z Y Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
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40
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Xu M, Cao C, Li Q, Jia P, Zhao J. Ecological Niche Modeling of Risk Factors for H7N9 Human Infection in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:E600. [PMID: 27322296 PMCID: PMC4924057 DOI: 10.3390/ijerph13060600] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Revised: 06/07/2016] [Accepted: 06/07/2016] [Indexed: 01/27/2023]
Abstract
China was attacked by a serious influenza A (H7N9) virus in 2013. The first human infection case was confirmed in Shanghai City and soon spread across most of eastern China. Using the methods of Geographic Information Systems (GIS) and ecological niche modeling (ENM), this research quantitatively analyzed the relationships between the H7N9 occurrence and the main environmental factors, including meteorological variables, human population density, bird migratory routes, wetland distribution, and live poultry farms, markets, and processing factories. Based on these relationships the probability of the presence of H7N9 was predicted. Results indicated that the distribution of live poultry processing factories, farms, and human population density were the top three most important determinants of the H7N9 human infection. The relative contributions to the model of live poultry processing factories, farms and human population density were 39.9%, 17.7% and 17.7%, respectively, while the maximum temperature of the warmest month and mean relative humidity had nearly no contribution to the model. The paper has developed an ecological niche model (ENM) that predicts the spatial distribution of H7N9 cases in China using environmental variables. The area under the curve (AUC) values of the model were greater than 0.9 (0.992 for the training samples and 0.961 for the test data). The findings indicated that most of the high risk areas were distributed in the Yangtze River Delta. These findings have important significance for the Chinese government to enhance the environmental surveillance at multiple human poultry interfaces in the high risk area.
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Affiliation(s)
- Min Xu
- State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
| | - Chunxiang Cao
- State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
| | - Qun Li
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| | - Peng Jia
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500, The Netherlands.
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY 14214, USA.
| | - Jian Zhao
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
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41
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Lu L, Ren Z, Yue Y, Yu X, Lu S, Li G, Li H, Wei J, Liu J, Mu Y, Hai R, Yang Y, Wei R, Kan B, Wang H, Wang J, Wang Z, Liu Q, Xu J. Niche modeling predictions of the potential distribution of Marmota himalayana, the host animal of plague in Yushu County of Qinghai. BMC Public Health 2016; 16:183. [PMID: 26912171 PMCID: PMC4765042 DOI: 10.1186/s12889-016-2697-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Accepted: 01/07/2016] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND After the earthquake on 14, April 2010 at Yushu in China, a plague epidemic hosted by Himalayan marmot (Marmota himalayana) became a major public health concern during the reconstruction period. A rapid assessment of the distribution of Himalayan marmot in the area was urgent. The aims of this study were to analyze the relationship between environmental factors and the distribution of burrow systems of the marmot and to predict the distribution of marmots. METHODS Two types of marmot burrows (hibernation and temporary) in Yushu County were investigated from June to September in 2011. The location of every burrow was recorded with a global positioning system receiver. An ecological niche model was used to determine the relationship between the burrow occurrence data and environmental variables, such as land surface temperature (LST) in winter and summer, normalized difference vegetation index (NDVI) in winter and summer, elevation, and soil type. The predictive accuracies of the models were assessed by the area under the curve of the receiving operator curve. RESULTS The models for hibernation and temporary burrows both performed well. The contribution orders of the variables were LST in winter and soil type, NDVI in winter and elevation for the hibernation burrow model, and LST in summer, NDVI in summer, soil type and elevation in the temporary burrow model. There were non-linear relationships between the probability of burrow presence and LST, NDVI and elevation. LST of 14 and 23 °C, NDVI of 0.22 and 0.60, and 4100 m were inflection points. A substantially higher probability of burrow presence was observed in swamp soil and dark felty soil than in other soil types. The potential area for hibernation burrows was 5696 km(2) (37.7% of Yushu County), and the area for temporary burrows was 7711 km(2) (51.0% of Yushu County). CONCLUSIONS The results suggested that marmots preferred warm areas with relatively low altitudes and good vegetation conditions in Yushu County. Based on these results, the present research is useful in understanding the niche selection and distribution pattern of marmots in this region.
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Affiliation(s)
- Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. .,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, 100101, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China. .,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Yujuan Yue
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Xiaotao Yu
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Shan Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Guichang Li
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Hailong Li
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Jianchun Wei
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Jingli Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - You Mu
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Rong Hai
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Yonghai Yang
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Rongjie Wei
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Biao Kan
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Hu Wang
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, 100101, China. .,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Zuyun Wang
- Qinghai Institute for Endemic Disease Prevention and Control, Qinghai, 811602, China.
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. .,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Jianguo Xu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
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Hasanjani Roushan MR, Moulana Z, Mohseni Afshar Z, Ebrahimpour S. Risk Factors for Relapse of Human Brucellosis. Glob J Health Sci 2015; 8:77-82. [PMID: 26925907 PMCID: PMC4965643 DOI: 10.5539/gjhs.v8n7p77] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Revised: 10/19/2015] [Accepted: 10/18/2015] [Indexed: 12/04/2022] Open
Abstract
Background & Propose: Brucellosis is serious disease around the world, especially in underdeveloped countries. Relapse is major problem in therapy of brucellosis. This study aimed to evaluate risk factors of relapse after treatment in patients. Methods: It is a descriptive-analytic study from 1990 to 2014, in Ayatolla Rohani hospital in Babol, Iran. We studied 980 patients with brucellosis. The studied community included patients infected with brucellosis and the required information was gathered based on their hospital files. The base for recognizing Malta fever were clinical symptoms and Para-clinical sign congruent with infection like as, titer SAT>1:320 and 2-ME>1:160. Patients with relapse and patients without relapse were placed separately in two groups. The data were statistically compared with Spss 16, by Chi-square and Cox–regression tests. Results: Based on this study, treatment regimen is a preventive factor (P=0.000). Moreover, Based on some statistical methods, regimens no. 3 and 4 were introduce preventive factors (P=0.001) and (P=0.004). It should also be noted that findings the same statistical model, factors like gender, age, residence, professional contacts, complications and delay in treatment were also analyzed but none of them are considered as preventive factors. Conclusion: Based our finding, we suggest aminoglycosides (gentamicin or streptomycin with doxycycline) are associated with lower rate of relapse in brucellosis.
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