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Tian JW, Kong YC, Han PY, Xu FH, Yang WH, Zhang YZ. Molecular epidemiological study of Scrub Typhus in residence, farm and forest habitats from Yunnan Province, China. PLoS One 2024; 19:e0301841. [PMID: 38626103 PMCID: PMC11020965 DOI: 10.1371/journal.pone.0301841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 03/23/2024] [Indexed: 04/18/2024] Open
Abstract
The number of people suffering from scrub typhus, which is not of concern, is increasing year by year, especially in Yunnan Province, China. From June 1, 2021 to August 15, 2022, a total of 505 mammalian samples were collected from farm, forest, and residential habitats with high incidence of scrub typhus in Yunnan, China, for nPCR (nested PCR) and qPCR (quantitative real-time PCR) detection of Orientia tsutsugamushi. A total of 4 orders of murine-like animals, Rodentia (87.52%, n = 442), Insectivora (10.29%, n = 52), Lagomorpha (1.79%, n = 9) and Scandentia (0.40%, n = 2) were trapped. Comparing the qPCR infection rates in the three habitats, it was no significant difference that the infection rate of residential habitat (44.44%) and that of the farm habitat (45.05%, P>0.05), which is much larger than that of the forest habitat (3.08%) (P<0.001). Three genotypes (Karp-like, Kato-like and TA763-like) of O. tsutsugamushi were found from Yunnan, China in this study.
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Affiliation(s)
- Jia-Wei Tian
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from Western Yunnan, Yunnan Key Laboratory of Zoonotic Disease Cross-border Prevention and Quarantine, Institute of Preventive Medicine, School of Public Health, Dali University, Dali, Yunnan, China
| | - Yi-Chen Kong
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from Western Yunnan, Yunnan Key Laboratory of Zoonotic Disease Cross-border Prevention and Quarantine, Institute of Preventive Medicine, School of Public Health, Dali University, Dali, Yunnan, China
| | - Pei-Yu Han
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from Western Yunnan, Yunnan Key Laboratory of Zoonotic Disease Cross-border Prevention and Quarantine, Institute of Preventive Medicine, School of Public Health, Dali University, Dali, Yunnan, China
| | - Fen-Hui Xu
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from Western Yunnan, Yunnan Key Laboratory of Zoonotic Disease Cross-border Prevention and Quarantine, Institute of Preventive Medicine, School of Public Health, Dali University, Dali, Yunnan, China
| | - Wei-Hong Yang
- Yunnan Institute of Endemic Diseases Control and Prevention, Dali, Yunnan, China
| | - Yun-Zhi Zhang
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from Western Yunnan, Yunnan Key Laboratory of Zoonotic Disease Cross-border Prevention and Quarantine, Institute of Preventive Medicine, School of Public Health, Dali University, Dali, Yunnan, China
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Qian J, Wu Y, Zhu C, Chen Q, Chu H, Liu L, Wang C, Luo Y, Yue N, Li W, Yang X, Yi J, Ye F, He J, Qi Y, Lu F, Wang C, Tan W. Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018. BMC Public Health 2024; 24:538. [PMID: 38383355 PMCID: PMC10880311 DOI: 10.1186/s12889-023-17233-y] [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: 04/20/2023] [Accepted: 11/15/2023] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Large-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control. METHODS This study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions. RESULTS Scrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882. CONCLUSIONS These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.
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Affiliation(s)
- Jiaojiao Qian
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Yifan Wu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Changqiang Zhu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Qiong Chen
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Hongliang Chu
- Center for Disease Prevention and Control of Jiangsu Province, Nanjing, Jiangsu, China
| | - Licheng Liu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Chongcai Wang
- Hainan International Travel Healthcare Center, Haikou, Hainan, China
| | - Yizhe Luo
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Na Yue
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Wenhao Li
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Xiaohong Yang
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Jing Yi
- Department of Transfusion Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fuqiang Ye
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Ji He
- Xiamen International Travel Health Care Center (Xiamen Customs Port Outpatient Department), Xiamen, China
| | - Yong Qi
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Fei Lu
- College of Information Engineering, Zhejiang University of Technology, Liuhe Rd. 288, Hangzhou, 310023, China.
| | - Chunhui Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
| | - Weilong Tan
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
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Pan K, Huang R, Xu L, Lin F. Exploring the effects and interactions of meteorological factors on the incidence of scrub typhus in Ganzhou City, 2008-2021. BMC Public Health 2024; 24:36. [PMID: 38167033 PMCID: PMC10763082 DOI: 10.1186/s12889-023-17423-8] [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: 08/22/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Scrub typhus poses a substantial risk to human life and wellbeing as it is transmitted by vectors. Although the correlation between climate and vector-borne diseases has been investigated, the impact of climate on scrub typhus remains inadequately comprehended. The objective of this study is to investigate the influence of meteorological conditions on the occurrence of scrub typhus in Ganzhou City, Jiangxi Province. METHODS: From January 1, 2008 to December 31, 2021, we gathered weekly records of scrub typhus prevalence alongside meteorological data in Ganzhou city. In order to investigate the correlation between meteorological factors and scrub typhus incidence, we utilized distributional lag nonlinear models and generalized additive models for our analysis. RESULTS Between 2008 and 2021, a total of 5942 cases of scrub typhus were recorded in Ganzhou City. The number of females affected exceeded that of males, with a male-to-female ratio of 1:1.86. Based on the median values of these meteorological factors, the highest relative risk for scrub typhus occurrence was observed when the weekly average temperature reached 26 °C, the weekly average relative humidity was 75%, the weekly average sunshine duration lasted for 2 h, and the weekly mean wind speed measured 2 m/s. The respective relative risks for these factors were calculated as 3.816 (95% CI: 1.395-10.438), 1.107 (95% CI: 1.008-1.217), 2.063 (95% CI: 1.022-4.165), and 1.284 (95% CI: 1.01-1.632). Interaction analyses showed that the risk of scrub typhus infection in Ganzhou city escalates with higher weekly average temperature and sunshine duration. CONCLUSION The findings of our investigation provide evidence of a correlation between environmental factors and the occurrence of scrub typhus. As a suggestion, utilizing environmental factors as early indicators could be recommended for initiating control measures and response strategies.
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Affiliation(s)
- Kailun Pan
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, China
| | - Renfa Huang
- Ganzhou Municipal Center for Disease Control and Prevention, Jiangxi Province, Ganzhou, 341000, China.
| | - Lingui Xu
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, China
| | - Fen Lin
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, China.
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Zhao J, Pang B, Liu C, Wang X, Chen S, Feng H, Kou Z, Wu T, Xu C, Yang L. Infections and Influencing Factors of Pathogens in Rattus norvegicus along the Zengjiang River in Guangzhou, China. Vector Borne Zoonotic Dis 2024; 24:46-54. [PMID: 38193886 DOI: 10.1089/vbz.2023.0045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024] Open
Abstract
Background: Rattus norvegicus can carry and transmit various zoonotic pathogens. Some studies were conducted to investigate a few zoonotic pathogens in Guangzhou, China, but no coinfections were investigated or specifically mentioned. Studies on the infections and the influencing factors of various zoonotic pathogens in R. norvegicus along the Zengjiang River in Guangzhou have not been carried out. Materials and Methods: In this study, R. norvegicus was captured in November 2020 and September 2021 along the Zengjiang River, and was tested for Bartonella spp., Leptospira spp., Orientia tsutsugamushi, Borrelia burgdorferi, Hantavirus (HV), Ehrlichia spp., and severe fever with thrombocytopenia syndrome virus (SFTSV) by the RT-PCR. Logistic regression analysis was used to determine the impact of habitat and demographic factors on the infections and coinfections of the surveyed pathogens. Results: In 119 R. norvegicus, the detection rates of Bartonella spp., Leptospira spp., O. tsutsugamushi, B. burgdorferi, and HV were 46.2%, 31.9%, 5%, 0.8%, and 18.5%, respectively. Ehrlichia spp. and SFTSV were negative. The triple coinfection rate of Bartonella spp., Leptospira spp., and HV was 11.8%. In addition, the coinfection of Bartonella spp., Leptospira spp., and B. burgdorferi was 0.8%. Dual coinfection of Bartonella spp. and Leptospira spp., Leptospira spp. and HV, Bartonella spp. and O. tsutsugamushi, Leptospira spp. and O. tsutsugamushi, and HV and O. tsutsugamushi was 9.2%, 3.4%, 1.7%, 1.7%, and 0.8%, respectively. Infections of these pathogens in R. norvegicus were found in habitats of banana plantation, grassland, and bush. Weight affected the infection of Bartonella spp., Leptospira spp., or HV in R. norvegicus. Conclusions: R. norvegicus along the Zengjiang River not only carried various potentially zoonotic pathogens but also had a variety of coinfections. Surveillance of the density and pathogens in R. norvegicus should be strengthened to reduce the incidence of relevant zoonotic diseases.
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Affiliation(s)
- Jiaqi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Bo Pang
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Chao Liu
- Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Xiaodong Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shouyi Chen
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Haiyan Feng
- Zengcheng District Center for Disease Control and Prevention, Guangzhou, China
| | - Zengqiang Kou
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Taoyu Wu
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Conghui Xu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Liping Yang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
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Liu L, Xiao Y, Wei X, Li X, Duan C, Jia X, Jia R, Guo J, Chen Y, Zhang X, Zhang W, Wang Y. Spatiotemporal epidemiology and risk factors of scrub typhus in Hainan Province, China, 2011-2020. One Health 2023; 17:100645. [PMID: 38024283 PMCID: PMC10665174 DOI: 10.1016/j.onehlt.2023.100645] [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: 05/19/2023] [Revised: 10/09/2023] [Accepted: 10/11/2023] [Indexed: 12/01/2023] Open
Abstract
Background The re-emergence of scrub typhus in the southern provinces of China in recent decades has been validated, thereby attracting the attention of public health authorities. There has been a spatial and temporal expansion of scrub typhus in Hainan Province, but the epidemiological characteristics, environmental drivers, and potential high-risk areas for scrub typhus have not yet been investigated. Objective The aims of this study were to characterize the spatiotemporal epidemiology of scrub typhus, identify dominant environmental risk factors, and map potential risk areas in Hainan Province from 2011 to 2020. Methods The spatiotemporal dynamics of scrub typhus in Hainan Province between 2011 and 2020 were analyzed using spatial analyses and seasonal-trend decomposition using regression (STR). The maximum entropy (MaxEnt) model was applied to determine the key environmental predictors and environmentally suitable areas for scrub typhus, and the demographic diversity of the predicted suitable zones was evaluated. Results During 2011-2020, 3260 scrub typhus cases were recorded in Hainan Province. The number of scrub typhus cases increased continuously each year, particularly among farmers (67.61%) and individuals aged 50-59 years (23.25%) who were identified as high-risk groups. A dual epidemic peak was detected, emerging annually from April to June and from July to October. The MaxEnt-based risk map illustrated that highly suitable areas, accounting for 25.36% of the total area, were mainly distributed in the northeastern part of Hainan Province, where 75.43% of the total population lived. Jackknife tests revealed that ground surface temperature, elevation, cumulative precipitation, evaporation, land cover, population density, and ratio of dependents were the most significant environmental factors. Conclusion In this study, we gained insights into the spatiotemporal epidemiological dynamics, pivotal environmental drivers, and potential risk map of scrub typhus in Hainan Province. These results have important implications for researchers and public health officials in guiding future prevention and control strategies for scrub typhus.
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Affiliation(s)
- Lisha Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yang Xiao
- Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Xianyu Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Chunyuan Duan
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Xinjing Jia
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Ruizhong Jia
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Jinpeng Guo
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Yong Chen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Xiushan Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenyi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Yong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
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Wang YC, Li JH, Qin Y, Qin SY, Chen C, Yang XB, Ma N, Dong MX, Lei CC, Yang X, Sun HT, Sun ZY, Jiang J. The Prevalence of Rodents Orientia tsutsugamushi in China During Two Decades: A Systematic Review and Meta-Analysis. Vector Borne Zoonotic Dis 2023; 23:619-633. [PMID: 37625029 DOI: 10.1089/vbz.2023.0057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2023] Open
Abstract
Background: Orientia tsutsugamushi is a zoonotic intracellular pathogen that requires parasitism in eukaryotic cells to reproduce. In recent years, tsutsugamushi disease reported in many places nationwide has crossed the Yangtze River, continuously, spreading to the North China. Now this phenomenon has aroused people's attention. Materials and Methods: In this study, meta-analysis was used to analyze the infection of rodents (vectors) in China, to clarify the transmission rule of O. tsutsugamushi. Results: This study included literature from six databases (PubMed, Web of Science, Science Direct, Wanfang, CNKI, and VIP). A total of 55 articles were included in the study from 610 retrieved articles. The total infection rate of O. tsutsugamushi in rodents was 5.5% (1206/20,620, 95% confidence interval [CI]: 0.0553-0.0617). The prevalence of O. tsutsugamushi in rodents before 2013 (7.73%, 95% CI: 4.11-12.37) was higher than after 2013 (2.11%, 95% CI: 0.64-4.41). O. tsutsugamushi spread among a variety of rodents, among which Rattus losea (13.3%, 95% CI: 4.33-26.26), Rattus tanezumi (5.69%, 95% CI: 1.37-12.72), and Apodemus agrarius (5.32%, 95% CI: 2.26-9.58) infection rate was higher. Kawasaki (8.32%, 95% CI: 1.42-20.17), Karp (7.36%, 95% CI: 2.62-14.22), Kato (2.54%, 95% CI: 0.08-8.28), and Gilliam (2.13%, 95% CI: 0.42-5.09) were the main prevalent genotypes in China. The prevalence of O. tsutsugamushi in rodents was seasonal, increasing gradually in summer (2.39%, 95% CI: 0.46-5.77), peaking in autumn (4.59%, 95% CI: 1.15-10.16), and then declining. The positive rate of immunofluorescence assay (25.07%, 95% CI: 8.44-46.88) was the highest among the detection methods, and it was statistically significant (p < 0.05). Based on the subgroup of geographical factors and climatic factors, the probability of O. tsutsugamushi infection in rodents was the highest when the temperature >19℃ (8.20%, 95% CI: 1.22-20.52), the altitude <100 millimeters (7.23%, 95% CI: 3.45-12.26), the precipitation >700 millimeters (12.22%, 95% CI: 6.45-19.50), and the humidity 60-70% (7.80%, 95% CI: 4.17-12.44). Conclusions: Studies have shown that rodents carrying O. tsutsugamushi are common. People should prevent and control rodents in life and monitor rodents carrying O. tsutsugamushi for a long time.
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Affiliation(s)
- Yan-Chun Wang
- School of Pharmacy, Qingdao University, Qingdao, PR China
- Changchun Sci-Tech University, Shuangyang, PR China
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Jing-Hao Li
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Ya Qin
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Si-Yuan Qin
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Chao Chen
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Xin-Bo Yang
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Ning Ma
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, PR China
| | - Ming-Xin Dong
- School of Pharmacy, Qingdao University, Qingdao, PR China
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Cong-Cong Lei
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Xing Yang
- Department of Medical Microbiology and Immunology, School of Basic Medicine, Dali University, Dali, PR China
| | - He-Ting Sun
- Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang, PR China
| | - Zhi-Yong Sun
- Department of Technology, Ningbo Sansheng Biotechnology Co., Ltd, Ningbo, PR China
| | - Jing Jiang
- Changchun Sci-Tech University, Shuangyang, PR China
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Xie X, Jiang D, Hao M, Ding F. Modeling analysis of armed conflict risk in sub-Saharan Africa, 2000-2019. PLoS One 2023; 18:e0286404. [PMID: 37782655 PMCID: PMC10545108 DOI: 10.1371/journal.pone.0286404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 05/10/2023] [Indexed: 10/04/2023] Open
Abstract
Sub-Saharan Africa has suffered frequent outbreaks of armed conflict since the end of the Cold War. Although several efforts have been made to understand the underlying causes of armed conflict and establish an early warning mechanism, there is still a lack of a comprehensive assessment approach to model the incidence risk of armed conflict well. Based on a large database of armed conflict events and related spatial datasets covering the period 2000-2019, this study uses a boosted regression tree (BRT) approach to model the spatiotemporal distribution of armed conflict risk in sub-Saharan Africa. Evaluation of accuracy indicates that the simulated models obtain high performance with an area under the receiver operator characteristic curve (ROC-AUC) mean value of 0.937 and an area under the precision recall curves (PR-AUC) mean value of 0.891. The result of the relative contribution indicates that the background context factors (i.e., social welfare and the political system) are the main driving factors of armed conflict risk, with a mean relative contribution of 92.599%. By comparison, the climate change-related variables have relatively little effect on armed conflict risk, accounting for only 7.401% of the total. These results provide novel insight into modelling the incidence risk of armed conflict, which may help implement interventions to prevent and minimize the harm of armed conflict.
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Affiliation(s)
- Xiaolan Xie
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land & Resources, Beijing, China
| | - Mengmeng Hao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
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Li Y, Ding F, Hao M, Chen S, Jiang D, Fan P, Qian Y, Zhuo J, Wu J. The implications for potential marginal land resources of cassava across worldwide under climate change challenges. Sci Rep 2023; 13:15177. [PMID: 37704718 PMCID: PMC10499798 DOI: 10.1038/s41598-023-42132-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 09/05/2023] [Indexed: 09/15/2023] Open
Abstract
The demand for energy plants is foreseen to grow as worldwide energy and climate policies promote the use of bioenergy for climate change mitigation. To avoid competing with food production, it's critical to assess future changes in marginal land availability for energy plant development. Using a machine learning method, boosted regression tree, this study modeled potential marginal land resources suitable for cassava under current and different climate change scenarios, based on cassava occurrence records and environmental covariates. The findings revealed that, currently, over 80% of the 1357.24 Mha of available marginal land for cassava cultivation is distributed in Africa and South America. Under three climate change scenarios, by 2030, worldwide suitable marginal land resources were predicted to grow by 39.71Mha, 66.21 Mha, and 39.31Mha for the RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively; by 2050, the potential marginal land suitable for cassava will increase by 38.98Mha, 83.02 Mha, and 55.43Mha, respectively; by 2080, the global marginal land resources were estimated to rise by 40.82 Mha, 99.74 Mha, and 21.87 Mha from now, respectively. Our results highlight the impacts of climate change on potential marginal land resources of cassava across worldwide, which provide the basis for assessing bioenergy potential in the future.
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Affiliation(s)
- Yongping Li
- Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, 650093, China
- Yunnan Institute of Land Resources Planning and Design, Kunming, 650216, China
| | - Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Mengmeng Hao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shuai Chen
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Peiwei Fan
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China
| | - Yushu Qian
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China.
| | - Jun Zhuo
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jiajie Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
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9
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Huang X, Xie B, Long J, Chen H, Zhang H, Fan L, Chen S, Chen K, Wei Y. Prediction of risk factors for scrub typhus from 2006 to 2019 based on random forest model in Guangzhou, China. Trop Med Int Health 2023. [PMID: 37230481 DOI: 10.1111/tmi.13896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
OBJECTIVES Scrub typhus is an increasingly serious public health problem, which is becoming the most common vector-borne disease in Guangzhou. This study aimed to analyse the correlation between scrub typhus incidence and potential factors and rank the importance of influential factors. METHODS We collected monthly scrub typhus cases, meteorological variables, rodent density (RD), Normalised Difference Vegetation Index (NDVI), and land use type in Guangzhou from 2006 to 2019. Correlation analysis and a random forest model were used to identify the risk factors for scrub typhus and predict the importance rank of influencing factors related to scrub typhus incidence. RESULTS The epidemiological results of the scrub typhus cases in Guangzhou between 2006 and 2019 showed that the incidence rate was on the rise. The results of correlation analysis revealed that a positive relationship between scrub typhus incidence and meteorological factors of mean temperature (Tmean ), accumulative rainfall (RF), relative humidity (RH), sunshine hours (SH), and NDVI, RD, population density, and green land coverage area (all p < 0.001). Additionally, we tested the relationship between the incidence of scrub typhus and the lagging meteorological factors through cross-correlation function, and found that incidence was positively correlated with 1-month lag Tmean , 2-month lag RF, 2-month lag RH, and 6-month lag SH (all p < 0.001). Based on the random forest model, we found that the Tmean was the most important predictor among the influential factors, followed by NDVI. CONCLUSIONS Meteorological factors, NDVI, RD, and land use type jointly affect the incidence of scrub typhus in Guangzhou. Our results provide a better understanding of the influential factors correlated with scrub typus, which can improve our capacity for biological monitoring and help public health authorities to formulate disease control strategies.
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Affiliation(s)
- Xiaobin Huang
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Binbin Xie
- Department of Surveillance and Control, Hainan Tropical Diseases Research Center, Haikou, China
| | - Jiali Long
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Haiyan Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Hao Zhang
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Lirui Fan
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Shouyi Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Kuncai Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yuehong Wei
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
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10
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Wei X, He J, Yin W, Soares Magalhaes RJ, Wang Y, Xu Y, Wen L, Sun Y, Zhang W, Sun H. Spatiotemporal dynamics and environmental determinants of scrub typhus in Anhui Province, China, 2010-2020. Sci Rep 2023; 13:2131. [PMID: 36747027 PMCID: PMC9902522 DOI: 10.1038/s41598-023-29373-7] [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: 09/13/2022] [Accepted: 02/03/2023] [Indexed: 02/08/2023] Open
Abstract
This study aims to describe the epidemiological characteristics of scrub typhus, detect the spatio-temporal patterns of scrub typhus at county level, and explore the associations between the environmental variables and scrub typhus cases in Anhui Province. Time-series analysis, spatial autocorrelation analysis, and space-time scan statistics were used to explore the characteristics and spatiotemporal patterns of the scrub typhus in Anhui Province. Negative binomial regression analysis was used to explore the association between scrub typhus and environmental variables. A total of 16,568 clinically diagnosed and laboratory-confirmed cases were reported from 104 counties of 16 prefecture-level cities. The number of female cases was higher than male cases, with a proportion of 1.32:1. And the proportion of cases over 65 years old was the highest, accounting for 33.8% of the total cases. Two primary and five secondary high-risk clusters were detected in the northwestern, northeastern, and central-eastern parts of Anhui Province. The number of cases in primary and secondary high-risk clusters accounted for 60.27% and 3.00%, respectively. Scrub typhus incidence in Anhui Province was positively correlated with the population density, normalized difference vegetation index, and several meteorological variables. The mean monthly sunshine duration with 3 lags (SSD_lag3), mean monthly ground surface temperature with 1 lag (GST_lag1), and mean monthly relative humidity with 3 lags (RHU_lag3) had the most significant association with increased cases of scrub typhus. Our findings indicate that public health interventions need to be focused on the elderly farmers in north of the Huai River in Anhui Province.
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Affiliation(s)
- Xianyu Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.,Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Junyu He
- Ocean College, Zhejiang University, Zhoushan, China.,Ocean Academy, Zhejiang University, Zhoushan, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ricardo J Soares Magalhaes
- Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia.,Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Yanding Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Liang Wen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yehuan Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China.
| | - Hailong Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China. .,Chinese PLA Center for Disease Control and Prevention, Beijing, China.
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11
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Li X, Wei X, Yin W, Soares Magalhaes RJ, Xu Y, Wen L, Peng H, Qian Q, Sun H, Zhang W. Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China. Parasit Vectors 2023; 16:44. [PMID: 36721181 PMCID: PMC9887782 DOI: 10.1186/s13071-023-05668-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/13/2023] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Despite the increasing number of cases of scrub typhus and its expanding geographical distribution in China, its potential distribution in Fujian Province, which is endemic for the disease, has yet to be investigated. METHODS A negative binomial regression model for panel data mainly comprising meteorological, socioeconomic and land cover variables was used to determine the risk factors for the occurrence of scrub typhus. Maximum entropy modeling was used to identify the key predictive variables of scrub typhus and their ranges, map the suitability of different environments for the disease, and estimate the proportion of the population at different levels of infection risk. RESULTS The final multivariate negative binomial regression model for panel data showed that the annual mean normalized difference vegetation index had the strongest correlation with the number of scrub typhus cases. With each 0.1% rise in shrubland and 1% rise in barren land there was a 75.0% and 37.0% increase in monthly scrub typhus cases, respectively. In contrast, each unit rise in mean wind speed in the previous 2 months and each 1% increase in water bodies corresponded to a decrease of 40.0% and 4.0% in monthly scrub typhus cases, respectively. The predictions of the maximum entropy model were robust, and the average area under the curve value was as high as 0.864. The best predictive variables for scrub typhus occurrence were population density, annual mean normalized difference vegetation index, and land cover types. The projected potentially most suitable areas for scrub typhus were widely distributed across the eastern coastal area of Fujian Province, with highly suitable and moderately suitable areas accounting for 16.14% and 9.42%, respectively. Of the total human population of the province, 81.63% reside in highly suitable areas for scrub typhus. CONCLUSIONS These findings could help deepen our understanding of the risk factors of scrub typhus, and provide information for public health authorities in Fujian Province to develop more effective surveillance and control strategies in identified high risk areas in Fujian Province.
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Affiliation(s)
- Xuan Li
- grid.186775.a0000 0000 9490 772XDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China ,grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- grid.186775.a0000 0000 9490 772XDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China ,grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- grid.198530.60000 0000 8803 2373Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ricardo J. Soares Magalhaes
- grid.1003.20000 0000 9320 7537Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia ,grid.1003.20000 0000 9320 7537Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Yuanyong Xu
- grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Liang Wen
- grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hong Peng
- grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Quan Qian
- grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hailong Sun
- grid.186775.a0000 0000 9490 772XDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China ,grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenyi Zhang
- grid.186775.a0000 0000 9490 772XDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China ,grid.488137.10000 0001 2267 2324Chinese PLA Center for Disease Control and Prevention, Beijing, China
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12
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Pautu L, Lalmalsawma P, Vanramliana, Balasubramani K, Balabaskaran Nina P, Rosangkima G, Sarma DK, Malvi Y, Hunropuia. Seroprevalence of scrub typhus and other rickettsial diseases among the household rodents of Mizoram, North-East India. Zoonoses Public Health 2023; 70:269-275. [PMID: 36694961 DOI: 10.1111/zph.13025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/26/2023]
Abstract
In the last decade, scrub typhus, a zoonotic disease has emerged as a major health concern in Mizoram, a North-East Indian state that shares international borders with Myanmar and Bangladesh. Mizoram is a biodiversity hotspot and >85% of the state is under forest cover, which provides an ideal ecological niche for the rodents and mites to transmit scrub typhus and other rickettsial infections. Using the Weil-Felix test, a serosurvey of household rodents from 41 villages spread across all the 11 districts in Mizoram was undertaken to gather important insights on their role in disease transmission. Furthermore, the chigger and flea indexes were calculated from the captured rodents. The 163 rodents captured belonged to five species; the highest numbers were from Rattus tanezumi (87), followed by Rattus rattus (41), Mus musculus (17), Suncus murinus (16), and Bandicota bengalensis (2). The rickettsial seropositivity of the captured rodents was 66.26% (108 out of 163 were positive). Among the 163 rodents, sera of 75 (46.01%), 61 (37.42%), and 73 (44.78%) were reactive to OXK, OX19, and OX2 antigens, respectively. The chigger and flea index were 17.92 and 0.16, respectively. Overall, the study has given important insights into the risk of multiple rickettsial infections that household rodents could transmit in Mizoram. These findings indicate the need for the urgent implementation of effective rodent control strategies in Mizoram.
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Affiliation(s)
- Lalfakzuala Pautu
- Integrated Disease Surveillance Programme, Health & Family Welfare Department, Aizawl, Mizoram, India.,Department of Life Sciences, Pachhunga University College, Mizoram University, Aizawl, Mizoram, India
| | - Pachuau Lalmalsawma
- Integrated Disease Surveillance Programme, Health & Family Welfare Department, Aizawl, Mizoram, India
| | - Vanramliana
- Department of Life Sciences, Pachhunga University College, Mizoram University, Aizawl, Mizoram, India
| | - Karuppusamy Balasubramani
- Department of Geography, School of Earth Sciences, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India
| | - Praveen Balabaskaran Nina
- Department of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala, India.,Department of Epidemiology and Public Health, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India
| | - Gabriel Rosangkima
- Department of Life Sciences, Pachhunga University College, Mizoram University, Aizawl, Mizoram, India
| | - Devojit Kumar Sarma
- ICMR- National Institute for Research in Environmental Health, Bhopal, Madhya Pradesh, India
| | - Yogesh Malvi
- Integrated Disease Surveillance Programme, Health & Family Welfare Department, Aizawl, Mizoram, India
| | - Hunropuia
- Department of Life Sciences, Pachhunga University College, Mizoram University, Aizawl, Mizoram, India
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13
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Han L, Sun Z, Li Z, Zhang Y, Tong S, Qin T. Impacts of meteorological factors on the risk of scrub typhus in China, from 2006 to 2020: A multicenter retrospective study. Front Microbiol 2023; 14:1118001. [PMID: 36910234 PMCID: PMC9996048 DOI: 10.3389/fmicb.2023.1118001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/08/2023] [Indexed: 02/25/2023] Open
Abstract
Scrub typhus is emerging as a global public health threat owing to its increased prevalence and remarkable geographic expansion. However, it remains a neglected disease, and possible influences of meteorological factors on its risk are poorly understood. We conducted the largest-scale research to assess the impact of meteorological factors on scrub typhus in China. Weekly data on scrub typhus cases and meteorological factors were collected across 59 prefecture-level administrative regions from 2006 to 2020. First, we divided these regions into 3 regions and analyzed the epidemiological characteristics of scrub typhus. We then applied the distributed lag nonlinear model, combined with multivariate meta-analysis, to examine the associations between meteorological factors and scrub typhus incidence at the total and regional levels. Subsequently, we identified the critical meteorological predictors of scrub typhus incidence and extracted climate risk windows. We observed distinct epidemiological characteristics across regions, featuring obvious clustering in the East and Southwest with more even distribution and longer epidemic duration in the South. The mean temperature and relative humidity had profound effects on scrub typhus with initial-elevated-descendent patterns. Weather conditions of weekly mean temperatures of 25-33°C and weekly relative humidity of 60-95% were risk windows for scrub typhus. Additionally, the heavy rainfall was associated with sharp increase in scrub typhus incidence. We identified specific climatic signals to detect the epidemic of scrub typhus, which were easily monitored to generalize. Regional heterogeneity should be considered for targeted monitoring and disease control strategies.
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Affiliation(s)
- Ling Han
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, China.,China Meteorological Administration Urban Meteorology Key Laboratory, Beijing, China
| | - Ziming Li
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
| | - Yunfei Zhang
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China.,Center for Global Health, Nanjing Medical University, Nanjing, China.,School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia
| | - Tian Qin
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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14
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Xie X, Hao M, Ding F, Helman D, Scheffran J, Wang Q, Ge Q, Jiang D. Exploring the direct and indirect impacts of climate variability on armed conflict in South Asia. iScience 2022; 25:105258. [PMID: 36439983 PMCID: PMC9684034 DOI: 10.1016/j.isci.2022.105258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 09/03/2022] [Accepted: 09/28/2022] [Indexed: 11/19/2022] Open
Abstract
Although numerous studies have examined the effects of climate variability on armed conflict, the complexity of these linkages requires deeper understanding to assess the causes and effects. Here, we assembled an extensive database of armed conflict, climate, and non-climate data for South Asia. We used structural equation modeling to quantify both the direct and indirect impacts of climate variability on armed conflict. We found that precipitation impacts armed conflict via direct and indirect effects which are contradictory in sign. Temperature affects armed conflict only through a direct path, while indirect effects were insignificant. Yet, an in-depth analysis of indirect effects showed that the net impact is weak due to two strong contradictory effects offsetting each other. Our findings illustrate the complex link between climate variability and armed conflict, highlighting the importance of a detailed analysis of South Asia's underlying mechanisms at the regional scale.
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Affiliation(s)
- Xiaolan Xie
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mengmeng Hao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - David Helman
- Institute of Environmental Sciences (Soil & Water), The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University, Rehovot 7610001, Israel
- Advanced School for Environmental Studies, The Hebrew University of Jerusalem, Jerusalem 91905, Israel
| | - Jürgen Scheffran
- Institute of Geography, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg 20144, Germany
| | - Qian Wang
- Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX13QR, UK
| | - Quansheng Ge
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land & Resources, Beijing 100101, China
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15
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Ding F, Wang Q, Hao M, Maude RJ, John Day NP, Lai S, Chen S, Fang L, Ma T, Zheng C, Jiang D. Climate drives the spatiotemporal dynamics of scrub typhus in China. GLOBAL CHANGE BIOLOGY 2022; 28:6618-6628. [PMID: 36056457 PMCID: PMC9825873 DOI: 10.1111/gcb.16395] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/12/2022] [Indexed: 06/15/2023]
Abstract
Scrub typhus is a climate-sensitive and life-threatening vector-borne disease that poses a growing public health threat. Although the climate-epidemic associations of many vector-borne diseases have been studied for decades, the impacts of climate on scrub typhus remain poorly understood, especially in the context of global warming. Here we incorporate Chinese national surveillance data on scrub typhus from 2010 to 2019 into a climate-driven generalized additive mixed model to explain the spatiotemporal dynamics of this disease and predict how it may be affected by climate change under various representative concentration pathways (RCPs) for three future time periods (the 2030s, 2050s, and 2080s). Our results demonstrate that temperature, precipitation, and relative humidity play key roles in driving the seasonal epidemic of scrub typhus in mainland China with a 2-month lag. Our findings show that the change of projected spatiotemporal dynamics of scrub typhus will be heterogeneous and will depend on specific combinations of regional climate conditions in future climate scenarios. Our results contribute to a better understanding of spatiotemporal dynamics of scrub typhus, which can help public health authorities refine their prevention and control measures to reduce the risks resulting from climate change.
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Affiliation(s)
- Fangyu Ding
- Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
| | - Qian Wang
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global HealthUniversity of OxfordOxfordUK
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical MedicineMahidol UniversityBangkokThailand
| | - Mengmeng Hao
- Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
| | - Richard James Maude
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global HealthUniversity of OxfordOxfordUK
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical MedicineMahidol UniversityBangkokThailand
- Harvard TH Chan School of Public HealthHarvard UniversityBostonMassachusettsUSA
| | - Nicholas Philip John Day
- Nuffield Department of Medicine, Centre for Tropical Medicine and Global HealthUniversity of OxfordOxfordUK
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical MedicineMahidol UniversityBangkokThailand
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK
| | - Shuai Chen
- Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
| | - Liqun Fang
- State Key Laboratory of Pathogen and BiosecurityBeijing Institute of Microbiology and EpidemiologyBeijingChina
| | - Tian Ma
- Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
| | - Canjun Zheng
- Chinese Center for Disease Control and PreventionBeijingChina
| | - Dong Jiang
- Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
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16
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Determining the potential distribution of Oryctes monoceros and Oryctes rhinoceros by combining machine-learning with high-dimensional multidisciplinary environmental variables. Sci Rep 2022; 12:17439. [PMID: 36261485 PMCID: PMC9581929 DOI: 10.1038/s41598-022-21367-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 09/26/2022] [Indexed: 01/12/2023] Open
Abstract
The African coconut beetle Oryctes monoceros and Asiatic rhinoceros beetle O. rhinoceros have been associated with economic losses to plantations worldwide. Despite the amount of effort put in determining the potential geographic extent of these pests, their environmental suitability maps have not yet been well established. Using MaxEnt model, the potential distribution of the pests has been defined on a global scale. The results show that large areas of the globe, important for production of palms, are suitable for and potentially susceptible to these pests. The main determinants for O. monoceros distribution were; temperature annual range, followed by land cover, and precipitation seasonality. The major determinants for O. rhinoceros were; temperature annual range, followed by precipitation of wettest month, and elevation. The area under the curve values of 0.976 and 0.975, and True skill statistic values of 0.90 and 0.88, were obtained for O. monoceros and O. rhinoceros, respectively. The global simulated areas for O. rhinoceros (1279.00 × 104 km2) were more than that of O. monoceros (610.72 × 104 km2). Our findings inform decision-making and the development of quarantine measures against the two most important pests of palms.
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17
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Ma T, Hao M, Chen S, Ding F. The current and future risk of spread of Leptotrombidium deliense and Leptotrombidium scutellare in mainland China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 843:156986. [PMID: 35772555 DOI: 10.1016/j.scitotenv.2022.156986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/22/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The chigger mites Leptotrombidium deliense (L. deliense) and Leptotrombidium scutellare (L. scutellare) are two main vectors of mite-borne diseases in China. However, the associated environmental risk factors are poorly understood, and the potential geographic ranges of the two mite species are unknown. METHODS We combined an ensemble boosted regression tree modelling framework with contemporary records of mites and multiple environmental factors to explore the effects of environmental variables on both mites, as well as to predict the current and future environmental suitability distributions of both species. Additionally, the human population living in the potential spread risk zones of each species was also estimated across mainland China. RESULTS Our results indicated that climate, land cover, and elevation are significantly associated with the spatial distributions of the two mite species. The current environmental suitability distribution of L. deliense is mainly concentrated in southern China, and that of L. scutellare is mainly distributed in southern and eastern coastal areas. With climate warming, the geographical distribution of the two mites generally tends to expand to the north and northwest. In addition, we estimated that 305.1-447.6 and 398.3-430.7 million people will inhabit the future spread risk zones of L. deliense and L. scutellare, respectively, in mainland China. CONCLUSIONS Our findings provide novel insights into understanding the current and future risks of spread of these two mite species and highlight the target zones for helping public health authorities better prepare for and respond to future changes in mite-borne disease risk.
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Affiliation(s)
- Tian Ma
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mengmeng Hao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuai Chen
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
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He J, Wang Y, Liu P, Yin W, Wei X, Sun H, Xu Y, Li S, Soares Magalhaes RJ, Guo Y, Zhang W. Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis. One Health 2022; 15:100446. [PMID: 36277104 PMCID: PMC9582591 DOI: 10.1016/j.onehlt.2022.100446] [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: 06/20/2022] [Revised: 09/04/2022] [Accepted: 10/11/2022] [Indexed: 11/29/2022] Open
Abstract
Background Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. Methods We obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012-2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST. Results Wavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods. Conclusion The ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies.
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Affiliation(s)
- Junyu He
- Ocean College, Zhejiang University, Zhoushan, China,Ocean Academy, Zhejiang University, Zhoushan, China
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Ping Liu
- Department of General Practice, Chinese PLA General Hospital-Sixth Medical Center, Beijing, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hailong Sun
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Ricardo J. Soares Magalhaes
- Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia,Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia,Correspondence to: Y Guo, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China,Correspondence to: W Zhang, Chinese PLA Center for Disease Control and Prevention, 20 Dong-Da Street, Fengtai District, Beijing 100071, China.
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Qian L, Wang Y, Wei X, Liu P, Magalhaes RJS, Qian Q, Peng H, Wen L, Xu Y, Sun H, Yin W, Zhang W. Epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province during 2012–2020. PLoS Negl Trop Dis 2022; 16:e0010278. [PMID: 36174105 PMCID: PMC9553047 DOI: 10.1371/journal.pntd.0010278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/11/2022] [Accepted: 09/13/2022] [Indexed: 12/02/2022] Open
Abstract
Background Scrub typhus has become a serious public health concern in the Asia-Pacific region including China. There were new natural foci continuously recognized and dramatically increased reported cases in mainland China. However, the epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province have yet to be investigated. Objective This study proposes to explore demographic characteristics and spatiotemporal dynamics of scrub typhus cases in Fujian province, and to detect high-risk regions between January 2012 and December 2020 at county/district scale and thereby help in devising public health strategies to improve scrub typhus prevention and control measures. Method Monthly cases of scrub typhus reported at the county level in Fujian province during 2012–2020 were collected from the National Notifiable Disease Surveillance System. Time-series analyses, spatial autocorrelation analyses and space-time scan statistics were applied to identify and visualize the spatiotemporal patterns of scrub typhus cases in Fujian province. The demographic differences of scrub typhus cases from high-risk and low-risk counties in Fujian province were also compared. Results A total of 11,859 scrub typhus cases reported in 87 counties from Fujian province were analyzed and the incidence showed an increasing trend from 2012 (2.31 per 100,000) to 2020 (3.20 per 100,000) with a peak in 2018 (4.59 per 100,000). There existed two seasonal peaks in June-July and September-October every year in Fujian province. A significant positive spatial autocorrelation of scrub typhus incidence in Fujian province was observed with Moran’s I values ranging from 0.258 to 0.471 (P<0.001). Several distinct spatiotemporal clusters mainly concentrated in north and southern parts of Fujian province. Compared to low-risk regions, a greater proportion of cases were female, farmer, and older residents in high-risk counties. Conclusions These results demonstrate a clear spatiotemporal heterogeneity of scrub typhus cases in Fujian province, and provide the evidence in directing future researches on risk factors and effectively assist local health authorities in the refinement of public health interventions against scrub typhus transmission in the high risk regions. Scrub typhus is a vector-borne zoonotic disease caused by Orientia tsutsugamushi and is popular in the Asia-Pacific area. Nowadays scrub typhus has been recognized as a considerable burden on public health in Fujian province. We explored the epidemiological characteristics, spatiotemporal patterns and diffusion characteristics of scrub typhus, and detected high-risk regions at the county level in Fujian province between January 2012 and December 2020. Our results indicated that the majority of cases were reported in June-July and September-October and that that middle aged and elderly people were more prone to infection every year in Fujian province. The spatial autocorrelation analysis revealed clustering in geographic distribution of cases and several distinct spatiotemporal clusters were identified in north and southern parts of Fujian province. Compared with cases from low-risk areas, a higher proportion of cases were female, farmer, and older residents in high-risk counties.
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Affiliation(s)
- Li Qian
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, Chongqing, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Ping Liu
- Department of General Practice, Chinese PLA General Hospital-Sixth Medical Center, Beijing, China
| | - Ricardo J. Soares Magalhaes
- Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia
- Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Quan Qian
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hong Peng
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Liang Wen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hailong Sun
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
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20
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Hao M, Aidoo OF, Qian Y, Wang D, Ding F, Ma T, Tettey E, Ninsin KD, Osabutey AF, Borgemeister C. Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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21
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Aidoo OF, Hao M, Ding F, Wang D, Jiang D, Ma T, Qian Y, Tettey E, Yankey N, Dadzie Ninsin K, Borgemeister C. The Impact of Climate Change on Potential Invasion Risk of Oryctes monoceros Worldwide. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.895906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
As a significant threat to agriculture, pests have caused a great disservice to crop production and food security. Understanding the mechanisms of pests’ outbreaks and invasion is critical in giving sound suggestions on their control and prevention strategies. The African rhinoceros beetle, Oryctes monoceros (Olivier), as the most damaging pest of palms, banana, sugarcane, and pineapple, severely threatens their production due to its ability to kill both young and matured hosts. Analyzing the effect of climate change on major parameters of O. monoceros life history has been an important issue recently, given its sensitivity to thermal conditions. However, information on how climate change alters geographical distribution of O. monoceros is poorly understood. By combining environmental variables and occurrence records, we were able to assess environmental risk factors for O. monoceros and create risk maps for the pest using the Boosted Regression Tree model. Our results significance of environmental variables showed that the annual temperature variation (39.45%), seasonality of temperature (23.00%), the isothermality (18.76%), precipitation of the hottest quarter months (6.07%), average variation of day time temperature (3.27%), were relatively important environmental factors that affected the distribution O. monoceros. We also found that the projected potential distributions of the pest’s habitats in all future global warming scenarios exceeded its present known distribution. The model predicts that habitat suitability for O. monoceros is predominantly concentrated along Africa’s west and east coastlines, Asia’s south coasts, South America’s north and east coasts, and a few locations spread over North America’s southern coasts and coastal regions. These outputs provide a solid theoretical foundation for O. monoceros risk evaluations and control.
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Jiang D, Ma T, Hao M, Ding F, Sun K, Wang Q, Kang T, Wang D, Zhao S, Li M, Xie X, Fan P, Meng Z, Zhang S, Qian Y, Edwards J, Chen S, Li Y. Quantifying risk factors and potential geographic extent of African swine fever across the world. PLoS One 2022; 17:e0267128. [PMID: 35446903 PMCID: PMC9022809 DOI: 10.1371/journal.pone.0267128] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 04/02/2022] [Indexed: 11/26/2022] Open
Abstract
African swine fever (ASF) has spread to many countries in Africa, Europe and Asia in the past decades. However, the potential geographic extent of ASF infection is unknown. Here we combined a modeling framework with the assembled contemporary records of ASF cases and multiple covariates to predict the risk distribution of ASF at a global scale. Local spatial variations in ASF risk derived from domestic pigs is influenced strongly by livestock factors, while the risk of having ASF in wild boars is mainly associated with natural habitat covariates. The risk maps show that ASF is to be ubiquitous in many areas, with a higher risk in areas in the northern hemisphere. Nearly half of the world’s domestic pigs (1.388 billion) are in the high-risk zones. Our results provide a better understanding of the potential distribution beyond the current geographical scope of the disease.
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Affiliation(s)
- Dong Jiang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Tian Ma
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Mengmeng Hao
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Fangyu Ding
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Kai Sun
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Qian Wang
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Tingting Kang
- School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, Guangdong, China
| | - Di Wang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Shen Zhao
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Meng Li
- School of Geographic Sciences, Nantong University, Nantong, China
| | - Xiaolan Xie
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Peiwei Fan
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Ze Meng
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Shize Zhang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
| | - Yushu Qian
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - John Edwards
- School of Veterinary Medicine, Centre for Biosecurity and One Health, Murdoch University, Perth, Australia
| | - Shuai Chen
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Yin Li
- School of Veterinary Medicine, Centre for Biosecurity and One Health, Murdoch University, Perth, Australia.,Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia
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Zhang M, Jiang D, Yang M, Ma T, Ding F, Hao M, Chen Y, Zhang C, Zhang X, Li M. Influence of the Environment on the Distribution and Quality of Gentiana dahurica Fisch. FRONTIERS IN PLANT SCIENCE 2021; 12:706822. [PMID: 34646283 PMCID: PMC8503573 DOI: 10.3389/fpls.2021.706822] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 09/06/2021] [Indexed: 05/29/2023]
Abstract
Gentiana dahurica Fisch. is a characteristic medicinal plant found in Inner Mongolia, China. To meet the increase in market demand and promote the development of medicinal plant science, we explored the influence of the environment on its distribution and the quantity of its active compounds (loganic acid and 6'-O-β-D-glucosylgentiopicroside) to find suitable cultivation areas for G. dahurica. Based on the geographical distribution of G. dahurica in Inner Mongolia and the ecological factors that affect its growth, identified from the literature and field visits, a boosted regression tree (BRT) was used to model ecologically suitable areas in the region. The relationship between the content of each of active compound in the plant and ecological factors was also established for Inner Mongolia using linear regression. The results showed that elevation and soil type had the most significant influence on the distribution of G. dahurica-their relative contribution was 30.188% and 28.947%, respectively. The factors that had the greatest impact on the distribution of high-quality G. dahurica were annual precipitation, annual mean temperature, and temperature seasonality. The results of BRT and linear regression modeling showed that suitable areas for high-quality G. dahurica included eastern Ordos, southern Baotou, Hohhot, southern Wulanchabu, southern Xilin Gol, and central Chifeng. However, there were no significant correlations between the contents of loganic acid and 6'-O-β-D-glucosylgentiopicroside and the ecological factors. This study explored the influence of the environment on the growth and quantity of active compounds in G. dahurica to provide guidance for coordinating the development of medicinal plant science.
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Affiliation(s)
- Mingxu Zhang
- Baotou Medical College, Inner Mongolia, Baotou, China
- State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Min Yang
- Baotou Medical College, Inner Mongolia, Baotou, China
| | - Tian Ma
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Mengmeng Hao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Yuan Chen
- Inner Mongolia Medical University, Hohhot, China
| | | | - Xiaobo Zhang
- State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medical, China Academy of Chinese Medical Sciences, Beijing, China
| | - Minhui Li
- Baotou Medical College, Inner Mongolia, Baotou, China
- Inner Mongolia Medical University, Hohhot, China
- Inner Mongolia Hospital of Traditional Chinese Medicine, Hohhot, China
- Inner Mongolia Key Laboratory of Characteristic Geoherbs Resources Protection and Utilization, Baotou, China
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Li Z, Xin H, Sun J, Lai S, Zeng L, Zheng C, Ray SE, Weaver ND, Wang L, Yu J, Feng Z, Hay SI, Gao GF. Epidemiologic Changes of Scrub Typhus in China, 1952-2016. Emerg Infect Dis 2021; 26:1091-1101. [PMID: 32441637 PMCID: PMC7258452 DOI: 10.3201/eid2606.191168] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Scrub typhus, a miteborne rickettsiosis, has emerged in many areas globally. We analyzed the incidence and spatial–temporal distribution of scrub typhus in China during 1952–1989 and 2006–2016 using national disease surveillance data. A total of 133,623 cases and 174 deaths were recorded. The average annual incidence was 0.13 cases/100,000 population during 1952–1989; incidence increased sharply from 0.09/100,000 population in 2006 to 1.60/100,000 population in 2016. The disease, historically endemic to southern China, has expanded to all the provinces across both rural and urban areas. We identified 3 distinct seasonal patterns nationwide; infections peaked in summer in the southwest, summer-autumn in the southeast, and autumn in the middle-east. Persons >40 years of age and in nonfarming occupations had a higher risk for death. The changing epidemiology of scrub typhus in China warrants an enhanced disease control and prevention program.
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25
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Ding F, Li Y, Huang B, Edwards J, Cai C, Zhang G, Jiang D, Wang Q, Robertson ID. Infection and risk factors of human and avian influenza in pigs in south China. Prev Vet Med 2021; 190:105317. [PMID: 33744674 DOI: 10.1016/j.prevetmed.2021.105317] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/09/2021] [Accepted: 03/01/2021] [Indexed: 11/19/2022]
Abstract
The coinfection of swine influenza (SI) strains and avian/human-source influenza strains in piggeries can contribute to the evolution of new influenza viruses with pandemic potential. This study analyzed surveillance data on SI in south China and explored the spatial predictor variables associated with different influenza infection scenarios in counties within the study area. Blood samples were collected from 7670 pigs from 534 pig farms from 2015 to 2017 and tested for evidence of infection with influenza strains from swine, human and avian sources. The herd prevalences for EA H1N1, H1N1pdm09, classic H1N1, HS-like H3N2, seasonal human H1N1 and avian influenza H9N2 were 88.5, 64.5, 60.3, 57.8, 12.9 and 10.3 %, respectively. Anthropogenic factors including detection frequency, chicken density, duck density, pig density and human population density were found to be better predictor variables for three influenza infection scenarios (infection with human strains, infection with avian strains, and coinfection with H9N2 avian strain and at least one swine strain) than were meteorological and geographical factors. Predictive risk maps generated for the four provinces in south China highlighted that the areas with a higher risk of the three infection scenarios were predominantly clustered in the delta area of the Pearl River in Guangdong province and counties surrounding Poyang Lake in Jiangxi province. Identification of higher risk areas can inform targeted surveillance for influenza in humans and pigs, helping public health authorities in designing risk-based SI control strategies to address the pandemic influenza threat in south China.
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Affiliation(s)
- Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yin Li
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - Baoxu Huang
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - John Edwards
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - Chang Cai
- Zhejiang Agricultural and Forestry University, Hangzhou, China
| | - Guihong Zhang
- South China Agriculture University, Guangzhou, Guangdong, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land & Resources, Beijing, 100101, China.
| | - Qian Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ian D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China-Australia Joint Research and Training Centre for Veterinary Epidemiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, Hubei, China.
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Russo A, Berruti M, Giacobbe DR, Vena A, Bassetti M. Recent molecules in the treatment of severe infections caused by ESBL-producing bacteria. Expert Rev Anti Infect Ther 2021; 19:983-991. [PMID: 33596162 DOI: 10.1080/14787210.2021.1874918] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Introduction: The widespread increase in resistance to β-lactam antibiotics in Enterobacterales currently represents one of the main threats to human health worldwide. The primary mechanisms of resistance are the production of β-lactamase enzymes that are able to hydrolyze β-lactams.Areas covered: we summarize the most recent advances regarding the main characteristics and spectrum of activity of new available antibiotics and strategies for the treatment of ESBL-producing Enterobacterales infections.Expert opinion: ESBL-producing strains are recognized as a worldwide challenge in the treatment of both hospital- and community-acquired infections. Data from the literature point out the high mortality associated with severe infections due to ESBL strains, especially in patients who developed severe sepsis or septic shock, together with the importance of the source of infection and indicators of severity, as determinants of the patient's outcome. Carbapenems are currently considered the first-line therapy, although the diffusion of resistant strains is an evolving problem and is mandatory the introduction in clinical practice of new drug regimens and treatment strategies, based on clinical data, local epidemiology, and microbiology. As a possible carbapenem-sparing strategy, ceftolozane-tazobactam and ceftazidime-avibactam appear the best-available carbapenem-sparing therapies. The definitive role of new drugs should be definitively assessed.
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Affiliation(s)
- Alessandro Russo
- Policlinico Umberto I," Sapienza"University of Rome, Rome, Italy
| | - Marco Berruti
- Department of Health Sciences, University of Genoa, Genoa, Italy
| | | | - Antonio Vena
- Department of Health Sciences, University of Genoa, Genoa, Italy
| | - Matteo Bassetti
- Department of Health Sciences, University of Genoa, Genoa, Italy
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Xin H, Fu P, Sun J, Lai S, Hu W, Clements ACA, Sun J, Cui J, Hay SI, Li X, Li Z. Risk mapping of scrub typhus infections in Qingdao city, China. PLoS Negl Trop Dis 2020; 14:e0008757. [PMID: 33264282 PMCID: PMC7735632 DOI: 10.1371/journal.pntd.0008757] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 12/14/2020] [Accepted: 08/28/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The emergence and re-emergence of scrub typhus has been reported in the past decade in many global regions. In this study, we aim to identify potential scrub typhus infection risk zones with high spatial resolution in Qingdao city, in which scrub typhus is endemic, to guide local prevention and control strategies. METHODOLOGY/PRINCIPAL FINDINGS Scrub typhus cases in Qingdao city during 2006-2018 were retrieved from the Chinese National Infectious Diseases Reporting System. We divided Qingdao city into 1,101 gridded squares and classified them into two categories: areas with and without recorded scrub typhus cases. A boosted regression tree model was used to explore environmental and socioeconomic covariates associated with scrub typhus occurrence and predict the risk of scrub typhus infection across the whole area of Qingdao city. A total of 989 scrub typhus cases were reported in Qingdao from 2006-2018, with most cases located in rural and suburban areas. The predicted risk map generated by the boosted regression tree models indicated that the highest infection risk areas were mainly concentrated in the mid-east and northeast regions of Qingdao, with gross domestic product (20.9%±1.8% standard error) and annual cumulative precipitation (20.3%±1.1%) contributing the most to the variation in the models. By using a threshold environmental suitability value of 0.26, we identified 757 squares (68.7% of the total) with a favourable environment for scrub typhus infection; 66.2% (501/757) of the squares had not yet recorded cases. It is estimated that 6.32 million people (72.5% of the total population) reside in areas with a high risk of scrub typhus infection. CONCLUSIONS/SIGNIFICANCE Many locations in Qingdao city with no recorded scrub typhus cases were identified as being at risk for scrub typhus occurrence. In these at-risk areas, awareness and capacity for case diagnosis and treatment should be enhanced in the local medical service institutes.
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Affiliation(s)
- Hualei Xin
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- World Health Organization (WHO) Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Peng Fu
- Department of Anesthesiology, Qingdao Fuwai Cardiovascular Hospital, Qingdao, Shandong, China
| | - Junling Sun
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shengjie Lai
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Geography and Environmental Science, University of Southampton, Southampton 1BJ, United Kingdom
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Archie C. A. Clements
- Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Jianping Sun
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Jing Cui
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Simon I. Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States of America
| | - Xiaojing Li
- Division of Infectious Disease, Qingdao City Center for Disease Control and Prevention, Qingdao, Shandong, China
- * E-mail: (XL); (ZL)
| | - Zhongjie Li
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (XL); (ZL)
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Wangrangsimakul T, Elliott I, Nedsuwan S, Kumlert R, Hinjoy S, Chaisiri K, Day NPJ, Morand S. The estimated burden of scrub typhus in Thailand from national surveillance data (2003-2018). PLoS Negl Trop Dis 2020; 14:e0008233. [PMID: 32287307 PMCID: PMC7182275 DOI: 10.1371/journal.pntd.0008233] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 04/24/2020] [Accepted: 03/18/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Scrub typhus is a major cause of acute febrile illness in the tropics and is endemic over large areas of the Asia Pacific region. The national and global burden of scrub typhus remains unclear due to limited data and difficulties surrounding diagnosis. METHODOLOGY/PRINCIPAL FINDINGS Scrub typhus reporting data from 2003-2018 were collected from the Thai national disease surveillance system. Additional information including the district, sub-district and village of residence, population, geographical, meteorological and satellite imagery data were also collected for Chiangrai, the province with the highest number of reported cases from 2003-2018. From 2003-2018, 103,345 cases of scrub typhus were reported with the number of reported cases increasing substantially over the observed period. There were more men than women, with agricultural workers the main occupational group affected. The majority of cases occurred in the 15-64 year old age group (72,144/99,543, 72%). Disease burden was greatest in the northern region, accounting for 53% of the total reported cases per year (mean). In the northern region, five provinces-Chiangrai, Chiangmai, Tak, Nan and Mae Hong Son-accounted for 84% (46,927/55,872) of the total cases from the northern region or 45% (46,927/103,345) of cases nationally. The majority of cases occurred from June to November but seasonality was less marked in the southern region. In Chiangrai province, elevation, rainfall, temperature, population size, habitat complexity and diversity of land cover contributed to scrub typhus incidence. INTERPRETATION The burden of scrub typhus in Thailand is high with disease incidence rising significantly over the last two decades. However, disease burden is not uniform with northern provinces particularly affected. Agricultural activity along with geographical, meteorological and land cover factors are likely to contribute to disease incidence. Our report, along with existing epidemiological data, suggests that scrub typhus is the most clinically important rickettsial disease globally.
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Affiliation(s)
- Tri Wangrangsimakul
- Mahidol-Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Ivo Elliott
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane Capital, Lao People’s Democratic Republic
| | - Supalert Nedsuwan
- Social and Preventative Medicine Department, Chiangrai Prachanukroh Hospital, Ministry of Public Health, Chiangrai, Thailand
| | - Rawadee Kumlert
- The Office of Disease Prevention and Control 12 Songkhla Province, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand
| | - Soawapak Hinjoy
- Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand
| | - Kittipong Chaisiri
- Department of Helminthology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Nicholas P. J. Day
- Mahidol-Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Serge Morand
- CNRS ISEM-CIRAD ASTRE, Faculty of Veterinary Technology, Kasetsart University, Bangkok, Thailand
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Abstract
Artemisinin, which is isolated from the naturally occurring plant Artemisia annua L. (A. annua; Qinghao in traditional Chinese medicine), is considered to be the active ingredient in the most effective treatment for malaria. Current malaria eradication plans rely on an affordable and robust supply of artemisinin, resulting in the demand to expand the area of A. annua under cultivation. However, there is no reliable assessment of the potential land resources suitable for planting A. annua at the global scale. By explicitly incorporating the assembled contemporary occurrence records of A. annua with various spatial predictor variables, a species distribution modelling procedure was adopted to produce the first global environmental suitability map for A. annua with high geographic detail (5 × 5 km2). The estimated map reveals that the total amount of potential land resources suitable for planting A. annua is approximately 1496.56 million hectares, mainly distributed in Asia (516.50 million hectares), Europe (378.82 million hectares), North America (354.56 million hectares) and South America (172.01 million hectares). The relationships between the relevant variables and A. annua were explored, and these illustrated that the most noteworthy predictor variables were meteorological factors, followed by solar radiation factors, soil factors and topographical factors. The map provides a rigorous environmental niche baseline to support the reasonable expansion of the A. annua cultivation area.
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Xin H, Sun J, Yu J, Huang J, Chen Q, Wang L, Lai S, Clements ACA, Hu W, Li Z. Spatiotemporal and demographic characteristics of scrub typhus in Southwest China, 2006–2017: An analysis of population‐based surveillance data. Transbound Emerg Dis 2020; 67:1585-1594. [DOI: 10.1111/tbed.13492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 01/09/2020] [Accepted: 01/13/2020] [Indexed: 01/31/2023]
Affiliation(s)
- Hualei Xin
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Qingdao City Center for Disease Control and Prevention Qingdao China
| | - Junling Sun
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Jianxing Yu
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Ministry of Health Key Laboratory of Systems Biology of Pathogens and Dr. Christophe Mérieux Laboratory CAMS‐Foundation Mérieux Institute of Pathogen Biology Academy of Medical Sciences of China and Peking Union Medical College Beijing China
| | - Jilei Huang
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- Chinese Center for Disease Control and Prevention National Institute of Parasitic Diseases Shanghai China
| | - Qiulan Chen
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Liping Wang
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
| | - Shengjie Lai
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
- WorldPop School of Geography and Environmental Science University of Southampton Southampton UK
- School of Public Health Key Laboratory of Public Health Safety Ministry of Education Fudan University Shanghai China
| | - Archie C. A. Clements
- Faculty of Health Sciences Curtin University Bentley WA Australia
- Telethon Kids Institute Nedlands WA Australia
| | - Wenbiao Hu
- School of Public Health and Social Work Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane Australia
| | - Zhongjie Li
- Key Laboratory of Surveillance and Early Warning on Infectious Disease Division of Infectious Disease Chinese Center for Disease Control and Prevention Beijing China
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Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16234845. [PMID: 31810239 PMCID: PMC6926588 DOI: 10.3390/ijerph16234845] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 11/26/2019] [Accepted: 11/28/2019] [Indexed: 11/17/2022]
Abstract
Being a globally emerging mite-borne zoonotic disease, scrub typhus is a serious public health concern in Nepal. Mapping environmental suitability and quantifying the human population under risk of the disease is important for prevention and control efforts. In this study, we model and map the environmental suitability of scrub typhus using the ecological niche approach, machine learning modeling techniques, and report locations of scrub typhus along with several climatic, topographic, Normalized Difference Vegetation Index (NDVI), and proximity explanatory variables and estimated population under the risk of disease at a national level. Both MaxEnt and RF technique results reveal robust predictive power with test The area under curve (AUC) and true skill statistics (TSS) of above 0.8 and 0.6, respectively. Spatial prediction reveals that environmentally suitable areas of scrub typhus are widely distributed across the country particularly in the low-land Tarai and less elevated river valleys. We found that areas close to agricultural land with gentle slopes have higher suitability of scrub typhus occurrence. Despite several speculations on the association between scrub typhus and proximity to earthquake epicenters, we did not find a significant role of proximity to earthquake epicenters in the distribution of scrub typhus in Nepal. About 43% of the population living in highly suitable areas for scrub typhus are at higher risk of infection, followed by 29% living in suitable areas of moderate-risk, and about 22% living in moderately suitable areas of lower risk. These findings could be useful in selecting priority areas for surveillance and control strategies effectively.
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Yao H, Wang Y, Mi X, Sun Y, Liu K, Li X, Ren X, Geng M, Yang Y, Wang L, Liu W, Fang L. The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors. Emerg Microbes Infect 2019; 8:909-919. [PMID: 31233387 PMCID: PMC6598543 DOI: 10.1080/22221751.2019.1631719] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
In mainland China, a geographic northward expansion of scrub typhus has been seen, highlighting the need to understand the factors and identify the risk for disease prevention. Incidence data from 1980 to 2013 were used. A Cox proportional hazard model was used to identify drivers for spatial spread, and a boosted regression tree (BRT) model was constructed to predict potential risk areas. Since the 1980s, an invasive expansion from South Natural Foci towards North Natural Foci was clearly identified, with the epidemiological heterogeneity observed between two regions, mainly in spatial distribution, seasonality, and demographic characteristics. Survival analysis disclosed significant factors contributing to the spatial expansion as following: being intersected by freeway (HR = 1.31, 95% CI: 1.11-1.54), coverage percentage of broadleaf forest (HR = 1.10, 95% CI: 1.06-1.15), and monthly average temperature (HR = 1.27, 95% CI: 1.25-1.30). The BRT models showed that precipitation, sunshine hour, temperature, crop field, and relative humidity contributed substantially to the spatial distribution of scrub typhus. A county-scale risk map was created to predict the regions with high probability of the disease. The current study enabled a comprehensive overview of epidemiological characteristics of scrub typhus in mainland China.
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Affiliation(s)
- Hongwu Yao
- a Department of Infection Management and Disease Control , Chinese PLA General Hospital , Beijing , People's Republic of China
| | - Yixing Wang
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China
| | - Xianmiao Mi
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China
| | - Ye Sun
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China.,c Center for Disease Control and Prevention of the North Military region , Jinan , People's Republic of China
| | - Kun Liu
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China.,d Department of Epidemiology and Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment , School of Public Health, Fourth Military Medical University , Xi'an , People's Republic of China
| | - Xinlou Li
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China.,e PLA Strategic Support Force Characteristic Medical Center , Beijing , People's Republic of China
| | - Xiang Ren
- f Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease , Chinese Centre for Disease Control and Prevention , Beijing , People's Republic of China
| | - Mengjie Geng
- f Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease , Chinese Centre for Disease Control and Prevention , Beijing , People's Republic of China
| | - Yang Yang
- g Department of Biostatistics , College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida , Gainesville , FL , USA
| | - Liping Wang
- f Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease , Chinese Centre for Disease Control and Prevention , Beijing , People's Republic of China
| | - Wei Liu
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China.,h Beijing Key Laboratory of Vector Borne and Natural Focus Infectious Diseases , Beijing , People's Republic of China
| | - Liqun Fang
- b The State Key Laboratory of Pathogen and Biosecurity , Beijing Institute of Microbiology and Epidemiology , Beijing , People's Republic of China
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