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Chen NT, Chen YC, Wu CD, Chen MJ, Guo YL. The impact of heavy precipitation and its impact modifiers on shigellosis occurrence during typhoon season in Taiwan: A case-crossover design. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 848:157520. [PMID: 35882342 DOI: 10.1016/j.scitotenv.2022.157520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 07/07/2022] [Accepted: 07/16/2022] [Indexed: 06/15/2023]
Abstract
Because of climate change, heavy precipitation is likely to become frequent and intense, thereby increasing the risk of shigellosis occurrence. However, few studies examined the impact of heavy precipitation on shigellosis and its impact modifiers in developed countries. This study aims to analyze the association between heavy precipitation and shigellosis in Taiwan, and to identify the vulnerable population and impact modifiers. We adopted a case-crossover design, and used conditional logistic regression to estimate odds ratios (ORs) for shigellosis occurrence. Information were collected on the daily shigellosis cases, precipitation, temperature, and typhoons from 1994 to 2015, and yearly data of medical resources and environmental factors were obtained at the city level from 1998 to 2015. Stratification analyses were performed by age, sex, medical resource, and environmental factors. We discovered that heavy precipitation ≥80 mm/day considerably increased the risk of shigellosis occurrence. The ORs of heavy rain (80 to <200 mm/day) were 2.08-2.26 at lags 0-1. The ORs of extremely heavy rain (≥200 mm/day) increased to 2.17-4.73 at lags 5-8. Moreover, the effect of heavy precipitation was greater under high temperature condition (≥23.6 °C). Adults were more susceptible to heavy-precipitation-associated shigellosis, especially the elderly. Males experienced marginally higher effects than females did. Moreover, cities with more medical resources and forest cover and higher percentage of completed storm sewers had lower effects; however, dense population and higher pig density were the risk factors. Although the high water-supply penetration rate did not decrease Shigella infection after heavy precipitation, it did lower the risk of typhoon-related shigellosis. In conclusion, hot temperature could enhance the impact of heavy precipitation on shigellosis. Public health interventions should be introduced according to the lag period after heavy precipitation, particularly in areas with high population density, proportion of elderly people, and pig density. The improvement of medical resources and tree cover as well as the construction of storm sewers and piped water systems might be mitigation measures that can be considered.
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Affiliation(s)
- Nai-Tzu Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli 35053, Taiwan; Research Center of Environmental Trace Toxic Substances, National Cheng Kung University, Tainan 704302, Taiwan
| | - Yu-Cheng Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli 35053, Taiwan; Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan
| | - Chih-Da Wu
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli 35053, Taiwan; Department of Geomatics, National Cheng Kung University, Tainan 70101, Taiwan
| | - Mu-Jean Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli 35053, Taiwan
| | - Yue-Liang Guo
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli 35053, Taiwan; Department of Environmental and Occupational Medicine, College of Medicine, National Taiwan University (NTU) and NTU Hospital, Taipei 10051, Taiwan; Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, Taipei 10055, Taiwan.
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Yang Y, Chen J, Huang R, Feng Z, Zhou G, You H, Han X. Construction of Ecological Security Pattern Based on the Importance of Ecological Protection-A Case Study of Guangxi, a Karst Region in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:5699. [PMID: 35565095 PMCID: PMC9101742 DOI: 10.3390/ijerph19095699] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023]
Abstract
The ecological security pattern is an important way to coordinate the contradiction between regional economic development and ecological protection and is conducive to promoting regional sustainable development. This study examines Guangxi, a karst region in China. The ecosystem service function and ecological environment sensitivity were both selected to evaluate the ecological conservation importance, and based on the results of the ecological conservation importance evaluation, suitable patches were selected as ecological sources. Meanwhile, resistance factors were selected from both natural factors and human activities to construct a comprehensive resistance surface, circuit theory was used to identify ecological corridors, ecological pinch points, and ecological barrier points, and ecological protection suggestions were then proposed. The results show that there are 50 patches of ecological sources in Guangxi, with a total area of 60,556.99 km2; 115 ecological corridors, with the longest corridor reaching 194.97 km; 301 ecological pinch points, whose spatial distribution is fragmented; and 286 ecological barrier points, most of which are concentrated in the central part of Guangxi. The results of this study provide a reference for the construction of ecological security patterns and ecological conservation in developing countries and karst areas.
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Affiliation(s)
- Yanping Yang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
| | - Jianjun Chen
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Renjie Huang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
| | - Zihao Feng
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
| | - Guoqing Zhou
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Haotian You
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xiaowen Han
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (R.H.); (Z.F.); (G.Z.); (H.Y.); (X.H.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
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Yang Y, Chen J, Lan Y, Zhou G, You H, Han X, Wang Y, Shi X. Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031595. [PMID: 35162617 PMCID: PMC8835525 DOI: 10.3390/ijerph19031595] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 12/10/2022]
Abstract
Due to ecological environmental fragility and soil erosion in Guangxi, studies of landscape patterns and associated ecological risks are needed to guide sustainable land development and ecologically sensitive land management. This study assesses dynamic spatial and temporal change patterns in land use and ecological risks based on 30 m land-use data, analyzes spatial correlations with ecological risks, and explores natural and socio-economic factor impacts on ecological risks. The results reveal: (1) A rapid and sizeable construction land increase in Guangxi from 2000 to 2018 associated mainly with loss of woodland and grassland. (2) Guangxi had the highest number of arable land patches from 2000 to 2018, and the distribution tended to be fragmented; moreover, the construction land gradually expanded outward from concentrated areas to form larger aggregates with increasing internal stability each year. (3) Guangxi ecological risk levels were low, low–medium, and medium, with significantly different spatial distributions observed for areas possessing different ecological risk levels. Regional ecological risk gradually decreased from the middle Guangxi regions to the surrounding areas and was positively correlated with spatial distribution. (4) Socio-economic factor impacts on ecological risk exceeded natural factor impacts. These results provide guidance toward achieving ecologically sensitive regional land-use management and ecological risk reduction and control, it can also provide a reference for ecological risk research in other similar regions in the world.
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Affiliation(s)
- Yanping Yang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
| | - Jianjun Chen
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
- Correspondence:
| | - Yanping Lan
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Guoqing Zhou
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Haotian You
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xiaowen Han
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Yu Wang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xue Shi
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
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Li S, Schmidt AM, Elliott SJ. Socioeconomic factors and bacillary dysentery risk in Jiangsu Province, China: a spatial investigation using Bayesian hierarchical models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2022; 32:220-231. [PMID: 32268797 DOI: 10.1080/09603123.2020.1746745] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 03/20/2020] [Indexed: 06/11/2023]
Abstract
Bacillary dysentery (BD) is an acute diarrheal disease prevalent in areas affected by socioeconomic disparities. We investigated BD risk and its associations with socioeconomic factors at the county-level in Jiangsu province, China using epidemiological and socioeconomic data from 2011-2014. We fitted four Bayesian hierarchical models with various prior specifications for random effects. As all model comparison criteria values were similar, we presented results from a reparameterized Besag-York-Mollié model, which addressed issues with the identifiability of variance captured by spatial and independent effects. Our model adjusted for year and socioeconomic status showed 18-65% decreased BD risk compared to 2011. We found a high relative risk in the northwestern and southwestern counties. Increasing the percentage of rural households, rural income per capita, health institutions per capita, or hospital beds per capita decreases the relative risk of BD, respectively. Our findings can be used to improve infectious diarrhea surveillance and enhance existing public health interventions.
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Affiliation(s)
- Sabrina Li
- Department of Geography and the Environment, University of Waterloo, Waterloo, ON, Canada
| | - Alexandra M Schmidt
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada
| | - Susan J Elliott
- Department of Geography and the Environment, University of Waterloo, Waterloo, ON, Canada
- School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada
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Abstract
The article aims to estimate and forecast the transmissibility of shigellosis and explore the association of meteorological factors with shigellosis. The mathematical model named Susceptible–Exposed–Symptomatic/Asymptomatic–Recovered–Water/Food (SEIARW) was used to explore the feature of shigellosis transmission based on the data of Wuhan City, China, from 2005 to 2017. The study applied effective reproduction number (Reff) to estimate the transmissibility. Daily meteorological data from 2008 to 2017 were used to determine Spearman's correlation with reported new cases and Reff. The SEIARW model fit the data well (χ2 = 0.00046, p > 0.999). The simulation results showed that the reservoir-to-person transmission of the shigellosis route has been interrupted. The Reff would be reduced to a transmission threshold of 1.00 (95% confidence interval (CI) 0.82–1.19) in 2035. Reducing the infectious period to 11.25 days would also decrease the value of Reff to 0.99. There was a significant correlation between new cases of shigellosis and atmospheric pressure, temperature, wind speed and sun hours per day. The correlation coefficients, although statistically significant, were very low (<0.3). In Wuhan, China, the main transmission pattern of shigellosis is person-to-person. Meteorological factors, especially daily atmospheric pressure and temperature, may influence the epidemic of shigellosis.
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Zhao ZY, Chen Q, Zhao B, Hannah MN, Wang N, Wang YX, Xuan XF, Rui J, Chu MJ, Yu SS, Wang Y, Liu XC, An R, Pan LL, Chiang YC, Su YH, Zhao BH, Chen TM. Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China. Infect Dis Poverty 2020; 9:39. [PMID: 32299485 PMCID: PMC7162736 DOI: 10.1186/s40249-020-00654-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 03/30/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Developing countries exhibit a high disease burden from shigellosis. Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model. METHODS The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. A sex-based Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model was applied to explore the dataset, and a sex-age-based SEIAR model was applied in 2010 to explore the sex- and age-specific transmissions. RESULTS From 2005 to 2017, 130 770 shigellosis cases (including 73 981 male and 56 789 female cases) were reported in Hubei Province. The SEIAR model exhibited a significant fitting effect with the shigellosis data (P < 0.001). The median values of the shigellosis transmission were 2.3225 × 108 for SARmm (secondary attack rate from male to male), 2.5729 × 108 for SARmf, 2.7630 × 10-8 for SARfm, and 2.1061 × 10-8 for SARff. The top five mean values of the transmission relative rate in 2010 (where the subscript 1 was defined as male and age ≤ 5 years, 2 was male and age 6 to 59 years, 3 was male and age ≥ 60 years, 4 was female and age ≤ 5 years, 5 was female and age 6 to 59 years, and 6 was male and age ≥ 60 years) were 5.76 × 10-8 for β61, 5.32 × 10-8 for β31, 4.01 × 10-8 for β34, 7.52 × 10-9 for β62, and 6.04 × 10-9 for β64. CONCLUSIONS The transmissibility of shigellosis differed among male and female individuals. The transmissibility between the genders was higher than that within the genders, particularly female-to-male transmission. The most important route in children (age ≤ 5 years) was transmission from the elderly (age ≥ 60 years). Therefore, the greatest interventions should be applied in females and the elderly.
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Affiliation(s)
- Ze-Yu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Qi Chen
- Hubei Provincial Center for Disease Control and Prevention, Wuhan City, Hubei Province, People's Republic of China
| | - Bin Zhao
- Laboratory Department, Xiang'an Hospital of Xiamen University, State Key Laboratory of Molecular Vaccinology and Molecular Diagnosis, Xiamen, Fujian, People's Republic of China
| | - Mikah Ngwanguong Hannah
- Medical College, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Ning Wang
- Respiratory Department, Shanghai General Hospital, Shanghai, People's Republic of China
| | - Yu-Xin Wang
- Department of Nephrology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, People's Republic of China
| | - Xian-Fa Xuan
- Department of Nephrology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, People's Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Mei-Jie Chu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Shan-Shan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Yao Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Xing-Chun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Ran An
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Li-Li Pan
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China
| | - Yan-Hua Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China.
| | - Ben-Hua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China.
| | - Tian-Mu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, Fujian Province, People's Republic of China.
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Mao Y, Zhang N, Zhu B, Liu J, He R. A descriptive analysis of the Spatio-temporal distribution of intestinal infectious diseases in China. BMC Infect Dis 2019; 19:766. [PMID: 31477044 PMCID: PMC6721277 DOI: 10.1186/s12879-019-4400-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 08/23/2019] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Intestinal infectious diseases (IIDs) have caused numerous deaths worldwide, particularly among children. In China, eight IIDs are listed as notifiable infectious diseases, including cholera, poliomyelitis, dysentery, typhoid and paratyphoid (TAP), viral Hepatitis A, viral Hepatitis E, hand-foot-mouth disease (HFMD) and other infectious diarrhoeal diseases (OIDDs). The aim of the study is to analyse the spatio-temporal distribution of IIDs from 2006 to 2016. METHODS Data on the incidence of IIDs from 2006 to 2016 were collected from the public health science data centre issued by the Chinese Center for Disease Control and Prevention. This study applied seasonal decomposition analysis, spatial autocorrelation analysis and space-time scan analysis. Plots and maps were constructed to visualize the spatio-temporal distribution of IIDs. RESULTS Regarding temporal analysis, the incidence of HFMD and Hepatitis E showed a distinct increasing trend, while the incidence of TAP, dysentery, and Hepatitis A presented decreasing trends over the last decade. The incidence of OIID remained steady. Summer is the season with the greatest number of cases of different IIDs. Regarding the spatial distribution, approximately all p values for the global Moran's I from 2006 to 2016 were less than 0.05, indicating that the incidences of the epidemics were unevenly distributed throughout the country. The high-risk areas for HFMD and OIDD were located in the Beijing-Tianjin-Tangshan (BTT) region and south China. The high-risk areas for TAP were located in some parts of southwest China. A higher incidence rates for dysentery and Hepatitis A were observed in the BTT region and some west provincial units. The high-risk areas for Hepatitis E were the BTT region and the Yangtze River Delta area. CONCLUSIONS Based on our temporal and spatial analysis of IIDs, we identified the high-risk periods and clusters of regions for the diseases. HFMD and OIDD exhibited high incidence rates, which reflected the negligence of Class C diseases by the government. At the same time, the incidence rate of Hepatitis E gradually surpassed Hepatitis A. The authorities should pay more attention to Class C diseases and Hepatitis E. Regardless of the various distribution patterns of IIDs, disease-specific, location-specific, and disease-combined interventions should be established.
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Affiliation(s)
- Ying Mao
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, 710049 China
| | - Ning Zhang
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, 710049 China
| | - Bin Zhu
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, 710049 China
- Department of Public Policy, City University of Hong Kong, Hong Kong, 999077 China
| | - Jinlin Liu
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, 710049 China
| | - Rongxin He
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, 710049 China
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Spatiotemporal Characteristics of Bacillary Dysentery from 2005 to 2017 in Zhejiang Province, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15091826. [PMID: 30149494 PMCID: PMC6163953 DOI: 10.3390/ijerph15091826] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 08/10/2018] [Accepted: 08/17/2018] [Indexed: 11/24/2022]
Abstract
Background: This study aimed to analyze the epidemiological and spatiotemporal characteristics of bacillary dysentery in Zhejiang Province and to provide the basis for its monitoring, prevention and control. Methods: This study included cases registered in China Information System for Diseases Control and Prevention from 1 January 2005 to 31 December 2017 in Zhejiang. Descriptive methods were employed to investigate the long trend of this disease: gender distribution, high-risk population, seasonality, and circular distribution was explored to detect the peak period; incidence maps were made to show the incidence trend of disease at county level; spatial autocorrelation was explored and the regions with autocorrelation were detected; and spatiotemporal scan was conducted to map out the high-risk regions of disease and how long they lasted. Statistical significance was assumed at p value of <0.05. Results: A total of 105,577 cases of bacillary dysentery were included, the incidence declining sharply from 45.84/100,000 to 3.44/100,000 with an obvious seasonal peak from July to October. Males were more predisposed to the infection than females. Pre-education children had the highest proportion among all occupation categories. Incidence in all age groups were negatively correlated with the year (p < 0.001), and the incidences were negatively correlated with the age groups in 2005–2008 (p = 0.022, 0.025, 0.044, and 0.047, respectively). Local autocorrelation showed that counties in Hangzhou were high-risk regions of bacillary dysentery. The spatiotemporal scan indicated that all clusters occurred before 2011, and the most likely cluster for disease was found in Hangzhou, Jiaxing and Huzhou. Conclusions: The incidence of bacillary dysentery in Zhejiang from 2005 to 2017 featured spatiotemporal clustering, and remained high in some areas and among the young population. Findings in this study serve as a panorama of bacillary dysentery in Zhejiang and provide useful information for better interventions and public health planning.
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Xu C, Xiao G, Wang J, Zhang X, Liang J. Spatiotemporal Risk of Bacillary Dysentery and Sensitivity to Meteorological Factors in Hunan Province, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 15:E47. [PMID: 29286297 PMCID: PMC5800146 DOI: 10.3390/ijerph15010047] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 11/27/2017] [Accepted: 12/08/2017] [Indexed: 11/16/2022]
Abstract
Bacillary dysentery remains a public health concern in the world. Hunan Province is one of the provinces having the highest risk of bacillary dysentery in China, however, the spatial-temporal distribution, variation of bacillary dysentery and sensitivity to meteorological factors in there are unclear. In this paper, a Bayesian space-time hierarchical model (BSTHM) was used to detect space-time variation, and effects of meteorological factors between 2010 and 2015. The risk of bacillary dysentery showed apparent spatial-temporal heterogeneity. The highest risk occurred in the summer season. Economically undeveloped mountainous areas in the west and south of the province had the highest incidence rates. Twenty three (18.9%) and 20 (16.4%) counties were identified as hot and cold spots, respectively. Among the hotspots, 11 counties (47.8%) exhibited a rapidly decreasing trend, suggesting they may become low-risk areas in the future. Of the cold spot counties, six (30%) showed a slowly decreasing trend, and may have a higher risk in the future. Among meteorological factors, air temperature, relative humidity, and wind speed all played a significant role in the spatial-temporal distribution of bacillary dysentery risk. These findings can contribute to the implementation of an early warning system for controlling and preventing bacillary dysentery.
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Affiliation(s)
- Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Gexin Xiao
- China National Center for Food Safety Risk Assessment, Beijing 100022, China.
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China.
| | - Xiangxue Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- The School of Earth Science and Resources, Chang'an University, Xi'an 710054, China.
| | - Jinjun Liang
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China.
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10
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Liu X, Liu Z, Ding G, Jiang B. Projected burden of disease for bacillary dysentery due to flood events in Guangxi, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2017; 601-602:1298-1305. [PMID: 28605848 DOI: 10.1016/j.scitotenv.2017.05.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 05/02/2017] [Accepted: 05/02/2017] [Indexed: 05/16/2023]
Abstract
Many researchers have been studying the influence of floods on intestinal infection in recent years. This study aimed to project the future disease burden of bacillary dysentery associated with floods in Guangxi, China. Relying on the longitudinal data, a generalized additive mixed model was applied to quantify the relationship between the monthly morbidity of bacillary dysentery and floods with two severity levels from 2004 to 2010, controlling for other meteorological variables. Years Lived with Disability (YLDs) was used as the measure of the burden of bacillary dysentery in the future of Guangxi, China. According to the generalized additive mixed model, the relative risks (RR) of moderate and severe floods on the morbidity of bacillary dysentery were 1.17 (95% CI: 1.03-1.33) and 1.39 (95% CI: 1.14-1.70), respectively. The regression analysis also indicated that the flood duration was negatively associated with the morbidity of bacillary dysentery (with RR: 0.63, 95% CI: 0.44-0.90). Considering the effects of floods only, compared with the YLDs in 2010, increasing flood events may lead to a 4.0% increase in the YLDs for bacillary dysentery by 2020, 2100, 0.0% by 2050, and an 8.0% increase by 2030 in Guangxi, if other factors remain constant. Considering all potential changes include floods, temperature and population size, the YLDs for bacillary dysentery may increase by up to 16.0% by 2020, 20.0% by 2030, 2050, and 0.0% by 2100, compared to that in 2010 under the moderate flood scenario; Under the severe flood scenario, the YLDs for bacillary dysentery may increase by up to 16.0% by 2020, 20.0% by 2030, 2050, and 4.0% by 2100.
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Affiliation(s)
- Xuena Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China; Center for Climate Change and Health, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China
| | - Zhidong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China; Center for Climate Change and Health, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China
| | - Guoyong Ding
- Department of Epidemiology and Health Statistics, School of Public Health, Taishan Medical University, Taian City, Shandong Province, PR China
| | - Baofa Jiang
- Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China; Center for Climate Change and Health, School of Public Health, Shandong University, Jinan City, Shandong Province, PR China.
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11
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Qin X, Luo H, Feng J, Li Y, Wei B, Feng Q. Equity in health financing of Guangxi after China's universal health coverage: evidence based on health expenditure comparison in rural Guangxi Zhuang autonomous region from 2009 to 2013. Int J Equity Health 2017; 16:174. [PMID: 28962656 PMCID: PMC5622556 DOI: 10.1186/s12939-017-0669-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 09/17/2017] [Indexed: 11/25/2022] Open
Abstract
Background Healthcare financing should be equitable. Fairness in financial contribution and protection against financial risk is based on the notion that every household should pay a fair share. Health policy makers have long been concerned with protecting people from the possibility that ill health will lead to catastrophic financial payments and subsequent impoverishment. A number of studies on health care financing equity have been conducted in some provinces of China, but in Guangxi, we found such observation is not enough. What is the situation in Guagnxi? A research on rural areas of Guangxi can add knowledge in this field and help improve the equity and efficiency of health financing, particularly in low-income citizens in rural countries, is a major concern in China’s medical sector reform. Methods Socio-economic characteristics and healthcare payment data were obtained from two rounds of household surveys conducted in 2009 (4634 respondents) and 2013 (3951 respondents). The contributions of funding sources were determined and a progressivity analysis of government healthcare subsidies was performed. Household consumption expenditure and total healthcare payments were calculated and incidence and intensity of catastrophic health payments were measured. Summary indices (concentration index, Kakwani index and Gini coefficient) were obtained for the sources of healthcare financing: indirect taxes, out of pocket payments, and social insurance contributions. Results The overall health-care financing system was regressive. In 2013, the Kakwani index was 0.0013, the vertical effect of all the three funding sources was 0.0001, and some values exceeded 100%, indicating that vertical inequity had a large influence on causing total health financing inequity. The headcount of catastrophic health payment declined sharply between 2009 and 2013, using total expenditure (from 7.3% to 1.2%) or non-food expenditure (from 26.1% to 7.5%) as the indicator of household capacity to pay. Conclusion Our study demonstrates an inequitable distribution of government healthcare subsidies in China from 2009 to 2013, and the inequity was reduced, especially in rural areas. Future healthcare reforms in China should not only focus on expanding the coverage, but also on improving the equity of distribution of healthcare benefits.
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Affiliation(s)
- Xianjing Qin
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Hongye Luo
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Jun Feng
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yanning Li
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Bo Wei
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Qiming Feng
- School of Information And Management, Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, China.
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12
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Lee S, Cho YM, Kim SY. Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis. Global Health 2017; 13:63. [PMID: 28830540 PMCID: PMC5568212 DOI: 10.1186/s12992-017-0286-9] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 08/10/2017] [Indexed: 11/10/2022] Open
Abstract
Background Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. Methods As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran’s I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. Results From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. Conclusions This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended. Electronic supplementary material The online version of this article (doi:10.1186/s12992-017-0286-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Seohyun Lee
- Department of Management, Policy and Community Health, University of Texas Health Science Center at Houston, School of Public Health, 1200 Pressler Street, Houston, TX, 77030, USA.,Center for Global Health Research, Seoul National University, Graduate School of Public Health, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Yoon-Min Cho
- Department of Public Health, Seoul National University, Graduate School of Public Health, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea.,Center for Global Health Research, Seoul National University, Graduate School of Public Health, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Sun-Young Kim
- Department of Public Health, Seoul National University, Graduate School of Public Health, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea. .,Center for Global Health Research, Seoul National University, Graduate School of Public Health, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea.
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13
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Zhang H, Si Y, Wang X, Gong P. Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 14:ijerph14070782. [PMID: 28708077 PMCID: PMC5551220 DOI: 10.3390/ijerph14070782] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 07/02/2017] [Accepted: 07/11/2017] [Indexed: 11/26/2022]
Abstract
Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk.
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Affiliation(s)
- Han Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China.
| | - Yali Si
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China.
- Joint Center for Global Change Studies, Beijing 100875, China.
| | - Xiaofeng Wang
- Center for Public Health Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| | - Peng Gong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China.
- Joint Center for Global Change Studies, Beijing 100875, China.
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14
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Li YN, Nong DX, Wei B, Feng QM, Luo HY. The impact of predisposing, enabling, and need factors in utilization of health services among rural residents in Guangxi, China. BMC Health Serv Res 2016; 16:592. [PMID: 27760531 PMCID: PMC5070132 DOI: 10.1186/s12913-016-1825-4] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 10/07/2016] [Indexed: 11/21/2022] Open
Abstract
Background Healthcare in China has significantly improved, meanwhile many socio-economic risk factors and health conditions factors affect accessibility and utilization of health services in rural areas. Inequity of health service in China needs to be estimated and reduced. Andersen behavioral model is useful to assess the association of health service utilization with predisposing, enabling, and need factors. Methods A survey was conducted among 4634 residents of 897 households in 2012. Logistic regression analysis was performed to explore the association of predisposing (age, gender, marital status, ethnicity and family size), enabling (education level, travel time to the nearest health facility, medical expense per capita, and health insurance coverage), and need factors (chronic disease) with the utilization of health services (i.e. physician visit and hospitalization). Results We observed a significant association between need factor (chronic diseases) and health service unitization, after adjusting for all predisposing and enabling factors (physician visits: odds ratio (OR) = 5.87, 95 % confidence interval (CI) = 4.71–7.32; hospitalization: OR = 4.04, 95 % CI = 2.90–5.61, respectively). In addition, age, gender, marital status, family size and education level were significant predictors of health service utilization. The travel time to the nearest health facility was associated with the utilization of physician visits, and expenditure on healthcare was a hindering factor of hospitalization. Conclusions The predisposing and enabling factors had a minor impact on health service utilization, while the need factor was a dominant predictor of health service utilization among rural residents in China. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1825-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yan-Ning Li
- Department of Health Service Management, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Dong-Xiao Nong
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Bo Wei
- Department of Health Service Management, Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
| | - Qi-Ming Feng
- Department of Health Service Management, Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
| | - Hong-Ye Luo
- Department of Health Service Management, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
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15
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Zhang H, Si Y, Wang X, Gong P. Patterns of Bacillary Dysentery in China, 2005-2010. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:164. [PMID: 26828503 PMCID: PMC4772184 DOI: 10.3390/ijerph13020164] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 01/19/2016] [Accepted: 01/21/2016] [Indexed: 02/06/2023]
Abstract
Although the incidence of bacillary dysentery in China has been declining progressively, a considerable disease burden still exists. Few studies have analyzed bacillary dysentery across China and knowledge gaps still exist in the aspects of geographic distribution and ecological drivers, seasonality and its association with meteorological factors, urban-rural disparity, prevalence and distribution of Shigella species. Here, we performed nationwide analyses to fill the above gaps. Geographically, we found that incidence increased along an east-west gradient which was inversely related to the economic conditions of China. Two large endemically high-risk regions in western China and their ecological drivers were identified for the first time. We characterized seasonality of bacillary dysentery incidence and assessed its association with meteorological factors, and saw that it exhibits north-south differences in peak duration, relative amplitude and key meteorological factors. Urban and rural incidences among China’s cities were compared, and disparity associated with urbanization level was invariant in most cities. Balanced decrease of urban and rural incidence was observed for all provinces except Hunan. S. flexneri and S. sonnei were identified as major causative species. Increasing prevalence of S. sonnei and geographic distribution of Shigella species were associated with economic status. Findings and inferences from this study draw broader pictures of bacillary dysentery in mainland China and could provide useful information for better interventions and public health planning.
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Affiliation(s)
- Han Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
| | - Yali Si
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
- Joint Center for Global Change Studies, Beijing 100875, China.
| | - Xiaofeng Wang
- Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| | - Peng Gong
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
- Joint Center for Global Change Studies, Beijing 100875, China.
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16
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Ma Y, Zhang T, Liu L, Lv Q, Yin F. Spatio-Temporal Pattern and Socio-Economic Factors of Bacillary Dysentery at County Level in Sichuan Province, China. Sci Rep 2015; 5:15264. [PMID: 26469274 PMCID: PMC4606827 DOI: 10.1038/srep15264] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 09/21/2015] [Indexed: 11/16/2022] Open
Abstract
Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statistic to detect the high risk spatio-temporal clusters in each year. Then, bivariate spatial correlation and Bayesian spatio-temporal model were utilized to examine the associations between the socio-economic factors and BD incidence. Spatio-temporal clusters of BD were mainly located in the northern-southern belt of the midwest area of Sichuan province. The proportion of primary industry, the proportion of rural population and the rates of BD incidence show statistically significant positive correlation. The proportion of secondary industry, proportion of tertiary Industry, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons, per capital GDP and the rate of BD incidence show statistically significant negative correlation. The best fitting spatio-temporal model showed that medical and technical personnel per thousand persons and per capital GDP were significantly negative related to the risk of BD.
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Affiliation(s)
- Yue Ma
- West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Tao Zhang
- West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Lei Liu
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, People's Republic of China
| | - Qiang Lv
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, People's Republic of China
| | - Fei Yin
- West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China
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