1
|
Wang J, Lu K, Wei Y, Wang W, Zhou Y, Zeng J, Deng Y, Zhang T, Yin F, Ma Y, Shui T. Using a Leroux-prior-based conditional autoregression-based strategy to map the short-term association between temperature and bacillary dysentery and its attributable burden in China. Front Public Health 2024; 12:1297635. [PMID: 38827625 PMCID: PMC11140140 DOI: 10.3389/fpubh.2024.1297635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 04/23/2024] [Indexed: 06/04/2024] Open
Abstract
Background In China, bacillary dysentery (BD) is the third most frequently reported infectious disease, with the greatest annual incidence rate of 38.03 cases per 10,000 person-years. It is well acknowledged that temperature is associated with BD and the previous studies of temperature-BD association in different provinces of China present a considerable heterogeneity, which may lead to an inaccurate estimation for a region-specific association and incorrect attributable burdens. Meanwhile, the common methods for multi-city studies, such as stratified strategy and meta-analysis, have their own limitations in handling the heterogeneity. Therefore, it is necessary to adopt an appropriate method considering the spatial autocorrelation to accurately characterize the spatial distribution of temperature-BD association and obtain its attributable burden in 31 provinces of China. Methods A novel three-stage strategy was adopted. In the first stage, we used the generalized additive model (GAM) model to independently estimate the province-specific association between monthly average temperature (MAT) and BD. In the second stage, the Leroux-prior-based conditional autoregression (LCAR) was used to spatially smooth the association and characterize its spatial distribution. In the third stage, we calculate the attribute BD cases based on a more accurate estimation of association. Results The smoothed association curves generally show a higher relative risk with a higher MAT, but some of them have an inverted "V" shape. Meanwhile, the spatial distribution of association indicates that western provinces have a higher relative risk of MAT than eastern provinces with 0.695 and 0.645 on average, respectively. The maximum and minimum total attributable number of cases are 224,257 in Beijing and 88,906 in Hainan, respectively. The average values of each province in the eastern, western, and central areas are approximately 40,991, 42,025, and 26,947, respectively. Conclusion Based on the LCAR-based three-stage strategy, we can obtain a more accurate spatial distribution of temperature-BD association and attributable BD cases. Furthermore, the results can help relevant institutions to prevent and control the epidemic of BD efficiently.
Collapse
Affiliation(s)
- Jianping Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Kai Lu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuxin Wei
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wei Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yongming Zhou
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Jing Zeng
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Ying Deng
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, China
| |
Collapse
|
2
|
Zhan Y, Gu H, Li X. Study on association factors of intestinal infectious diseases based-Bayesian spatio-temporal model. BMC Infect Dis 2023; 23:720. [PMID: 37875791 PMCID: PMC10598920 DOI: 10.1186/s12879-023-08665-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/03/2023] [Indexed: 10/26/2023] Open
Abstract
BACKGROUND Intestinal infectious diseases (IIDs) are a significant public health issue in China, and the incidence and distribution of IIDs vary greatly by region and are affected by various factors. This study aims to describe the spatio-temporal trends of IIDs in the Chinese mainland and investigate the association between socioeconomic and meteorological factors with IIDs. METHODS In this study, IIDs in mainland China from 2006 to 2017 was analyzed using data obtained from the China Center for Disease Control and Prevention. Spatio-temporal mapping techniques was employed to visualize the spatial and temporal distribution of IIDs. Additionally, mean center and standard deviational ellipse analyses were utilized to examine the spatial trends of IIDs. To investigate the potential associations between IIDs and meteorological and socioeconomic variables, spatiotemporal zero-inflated Poisson and negative binomial models was employed within a Bayesian framework. RESULTS During the study period, the occurrence of most IIDs has dramatically reduced, with uneven reductions in different diseases. Significant regional differences were found among IIDs and influential factors. Overall, the access rate to harmless sanitary toilets (ARHST) was positively associated with the risk of cholera (RR: 1.73, 95%CI: 1.08-2.83), bacillary dysentery (RR: 1.32, 95%CI: 1.06-1.63), and other intestinal infectious diseases (RR: 1.88, 95%CI: 1.52-2.36), and negatively associated with typhoid fever (RR: 0.66, 95%CI: 0.51-0.92), paratyphoid fever (RR: 0.71, 95%CI: 0.55-0.92). Urbanization is only associated with hepatitis E (RR: 2.48, 95%CI: 1.12-5.72). And GDP was negatively correlated with paratyphoid fever (RR: 0.82, 95%CI: 0.70-0.97), and bacillary dysentery (RR: 0.77, 95%CI: 0.68-0.88), and hepatitis A (RR: 0.84, 95%CI: 0.73-0.97). Humidity showed positive correlation with some IIDs except for amoebic dysentery (RR: 1.64, 95%CI: 1.23-2.17), while wind speed showed a negative correlation with most IIDs. High precipitation was associated with an increased risk of typhoid fever (RR: 1.52, 95%CI: 1.09-2.13), and high temperature was associated with an increased risk of typhoid fever (RR: 2.82, 95%CI: 2.06-3.89), paratyphoid fever (RR: 2.79, 95%CI: 2.02-3.90), and HMFD (RR: 1.34, 95%CI: 1.01-1.77). CONCLUSIONS This research systematically and quantitatively studied the effect of socioeconomic and meteorological factors on IIDs, which provided causal clues for future studies and guided government planning.
Collapse
Affiliation(s)
- Yancen Zhan
- Department of Big Data in Health Sciences, and Center for Clinical Big Data and Statistics, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Hua Gu
- The Cancer Hospital, University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou, 310022, China
| | - Xiuyang Li
- Department of Big Data in Health Sciences, and Center for Clinical Big Data and Statistics, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
| |
Collapse
|
3
|
Feifei L, Hairong L, Linsheng Y, Li W, Lijuan G, Gemei Z, Lan Z. The spatial-temporal pattern of Japanese encephalitis and its influencing factors in Guangxi, China. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 111:105433. [PMID: 37037290 DOI: 10.1016/j.meegid.2023.105433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 04/01/2023] [Accepted: 04/06/2023] [Indexed: 04/12/2023]
Abstract
Japanese encephalitis (JE) is a major global public health threat. Using Japanese encephalitis incidence data from 2004 to 2010 in Guangxi Province, China, this study comprehensively explored the driving forces and the interactive effects between environmental and social factors of Japanese encephalitis using the Geo-detector method. The results indicated that the incidence of Japanese encephalitis showed a fluctuating downward trend from 2004 to 2010. The onset of JE was seasonal, mainly concentrated in June-July, and highly aggregated in northwestern Guangxi. Among the factors associated with Japanese encephalitis, days with temperatures >30 °C, accumulated temperatures >25 °C, slope, the normalized difference vegetation index, the gross domestic product of tertiary industries, the gross domestic product of primary industries and the number of pigs slaughtered showed higher contributions to Japanese encephalitis incidence. An enhanced interactive effect was found between environmental and social factors, and the interaction between days with humidity levels >80% and the gross domestic product of tertiary industries had the greatest combined effect on JE. These findings enhanced the understanding of the combined effect of social and environmental factors on the incidence of Japanese encephalitis and could help improve Japanese encephalitis transmission control and prevention strategies.
Collapse
Affiliation(s)
- Li Feifei
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Li Hairong
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yang Linsheng
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Wang Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Gu Lijuan
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Zhong Gemei
- Guangxi Center for Disease Prevention and Control, Guangxi 530000, China
| | - Zhang Lan
- National Institute of Environmental Health, China CDC, Beijing 100021, China
| |
Collapse
|
4
|
Ni H, Zeng Q, Xu T, Xiao L, Yu X, Hu J, Li Y, Lin H, Guo P, Zhou H. The size of the susceptible pool differentiates climate effects on seasonal epidemics of bacillary dysentery. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 861:160553. [PMID: 36455742 DOI: 10.1016/j.scitotenv.2022.160553] [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: 09/11/2022] [Revised: 11/22/2022] [Accepted: 11/24/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVES At present, some studies have pointed out several possible climate drivers of bacillary dysentery. However, there is a complex nonlinear interaction between climate drivers and susceptible population in the spread of diseases, which makes it challenging to detect climate drivers at the size of susceptible population. METHODS By using empirical dynamic modeling (EDM), the climate drivers of bacillary dysentery dynamic were explored in China's five temperature zones. RESULTS We verified the availability of climate drivers and susceptible population size on bacillary dysentery, and used this information for bacillary dysentery dynamic prediction. Moreover, we found that their respective effects increased with the increase of temperature and relative humidity, and their states (temperature and relative humidity) were different when they reached their maximum effects, and the negative effect between the effect of temperature and disease incidence increased with the change of temperature zone (from temperate zone to warm temperate zone to subtropical zone) and the climate driving effect of the temperate zone (warm temperate zone) was greater than that of the colder (temperate zone) and warmer (subtropics) zones. When we viewed from single temperature zone, the climatic effect arose only when the size of the susceptible pool was large. CONCLUSIONS These results provide empirical evidence that the climate factors on bacillary dysentery are nonlinear, complex but dependent on the size of susceptible populations and different climate scenarios.
Collapse
Affiliation(s)
- Haobo Ni
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Ting Xu
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Lina Xiao
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Jinrui Hu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yang Li
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China; Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou 515041, China.
| | - Haijian Zhou
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| |
Collapse
|
5
|
Li H, Ge M, Pei Z, He J, Wang C. Associations of environmental factors with total cholesterol level of middle-aged and elderly people in China. BMC Public Health 2022; 22:2423. [PMID: 36564736 PMCID: PMC9783789 DOI: 10.1186/s12889-022-14922-y] [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: 03/28/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Dyslipidemia is a key factor causing cardio cerebrovascular diseases, and the total cholesterol (TC) is an important lipid indicator among them. Studies have shown that environmental factors have a strong association with TC levels. Previous studies only focused on the seasonal variation of TC level and the short-term effects of some environmental factors on TC level over time, and few studies explored the geographical distribution of TC level and quantified the impact of environmental factors in space. METHODS Based on blood test data which was from China Health and Retirement Longitudinal Study (Charls) database, this study selected the TC level test data of middle-aged and elderly people in China in 2011 and 2015, and collected data from 665 meteorological stations and 1496 air pollutant monitoring stations in China. After pretreatment, the spatial distribution map of TC level was prepared and the regional statistics were made. GeoDetector and geographically weighted regression (GWR) were used to measure the relationship between environmental factors and TC level. RESULTS The TC level of middle-aged and elderly in China was higher in females than in males, and higher in urban areas than in rural areas, showing a clustered distribution. The high values were mainly in South China, Southwest China and North China. Temperature, humidity, PM10 and PM2.5 were significant environmental factors affecting TC level of middle-aged and elderly people. The impact of pollutants was more severe in northern China, and TC level in southern China was mainly affected by meteorological factors. CONCLUSIONS There were gender and urban-rural differences in TC levels among the middle-aged and elderly population in China, showing aggregation in geographical distribution. Meteorological factors and air pollutants may be very important control factors, and their influencing mechanism needs further study.
Collapse
Affiliation(s)
- Hao Li
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Miao Ge
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Zehua Pei
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Jinwei He
- grid.440747.40000 0001 0473 0092Medical School, Yan’an University, 580 Shengdi Road, Yan’an, 716000 China
| | - Congxia Wang
- grid.43169.390000 0001 0599 1243Department of Cardiology, the Second Affiliated Hospital of Medical College, Xi’an Jiaotong University, No. 157, Xiwu Road, Xi’an, 710004 China
| |
Collapse
|
6
|
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.
Collapse
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.
| |
Collapse
|
7
|
Venkatesh K, John R, Chen J, Xiao J, Amirkhiz RG, Giannico V, Kussainova M. Optimal ranges of social-environmental drivers and their impacts on vegetation dynamics in Kazakhstan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157562. [PMID: 35901895 DOI: 10.1016/j.scitotenv.2022.157562] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/18/2022] [Accepted: 07/18/2022] [Indexed: 06/15/2023]
Abstract
Kazakhstan is part of the Eurasian Steppes, the world's largest contiguous grassland system. Kazakh grassland systems are largely understudied despite being historically important for agropastoral practices. These grasslands are considered vulnerable to anthropogenic activities and climatic variability. Few studies have examined vegetation dynamics in Central Asia owing to the complex impacts of moisture, climatic and anthropogenic forcings. A comprehensive analysis of spatiotemporal changes of vegetation and its driving factors will help elucidate the causes of grassland degradation. Here, we investigated the individual and pairwise interactive influences of various social-environmental system (SES) drivers on greenness dynamics in Kazakhstan. We sought to examine whether there is a relationship between peak season greenness and its drivers - spring drought, preceding winter freeze-thaw cycles, percent snow cover and snow depth - for Kazakhstan during 2000-2016. As hypothesized, snow depth and spring drought accounted for 60 % and 52 % of the variance in the satellite-derived normalized difference vegetation index (NDVI) in Kazakhstan. The freeze-thaw process accounted for 50 % of NDVI variance across the country. In addition, continuous thawing during the winter increased vegetation greenness. We also found that moisture and topographic factors impacted NDVI more significantly than socioeconomic factors. However, the impacts of socioeconomic drivers on vegetation growth were amplified when they interacted with environmental drivers. Terrain slope and soil moisture had the highest q-values or power of determinant, accounting for ~70 % of the variance in NDVI across the country. Socioeconomic drivers, such as crop production (59 %), population density (48 %), and livestock density (26 %), had significant impacts on vegetation dynamics in Kazakhstan. We found that most of the pairwise interactive influences of the drivers exhibited bi-factor enhancement, and the interaction between soil moisture and elevation was the largest (q = 0.92). Our study revealed the optimal ranges and tipping points of SES drivers and quantified the impacts of various driving factors on NDVI. These findings can help us identify the factors causing grassland degradation and provide a scientific basis for ecological protection in semiarid regions.
Collapse
Affiliation(s)
- Kolluru Venkatesh
- Department of Sustainability and Environment, University of South Dakota, Vermillion, SD 57069, USA.
| | - Ranjeet John
- Department of Sustainability and Environment, University of South Dakota, Vermillion, SD 57069, USA; Department of Biology, University of South Dakota, Vermillion, SD 57069, USA.
| | - Jiquan Chen
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI 48823, USA; Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48823, USA.
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA.
| | | | - Vincenzo Giannico
- Department of Agricultural and Environmental Sciences, University of Bari A. Moro, Via Amendola 165/A, 70126 Bari, Italy.
| | - Maira Kussainova
- Kazakh National Agrarian Research University, AgriTech Hub KazNARU, 8 Abay avenue, Almaty 050010, Kazakhstan; Kazakh-German University (DKU), Nazarbaev avenue, 173, 050010 Almaty, Kazakhstan.
| |
Collapse
|
8
|
Pan Y, Lin Y, Yang R. Agricultural Production Space Suitability in China: Spatial Pattern, Influencing Factors and Optimization Strategies. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13812. [PMID: 36360693 PMCID: PMC9657764 DOI: 10.3390/ijerph192113812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/18/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
The paper uses the analytic hierarchy process (AHP), spatial autocorrelation analysis, and geographic detectors to reveal the spatial pattern of agricultural production space suitability in China, explores the impact mechanism of agricultural production development, and explores the optimization and promotion strategies for the development of regional agricultural production in various regions in the future. The results show that the resource and environmental carrying capacity, and the agricultural production space suitability under the direction of China's agricultural production function, show a 'polarization' development trend in space, with high levels in the southeast and low levels in the northwest, with significant spatial agglomeration. The factors influencing the suitability of agricultural production have significant spatial differentiation laws in the Nine Agricultural Areas of China. Climate change factors are the dominant factors affecting the areas with poor resource endowment and traditional agricultural areas in the northwest. Factors that reflect the level of urbanization are the main factors that affect the agricultural production space suitability in the middle and lower reaches of the Yangtze River and South China. China's agricultural production spatial suitability areas can be divided into nine types of suitable geographical areas. In the future, the impacts of climate change and urbanization on agricultural production space should be considered, and strategies should be taken, according to local conditions, in different regions to improve their suitability.
Collapse
|
9
|
Zheng J, Zhang N, Shen G, Liang F, Zhao Y, He X, Wang Y, He R, Chen W, Xue H, Shen Y, Fu Y, Zhang WH, Zhang L, Bhatt S, Mao Y, Zhu B. Spatiotemporal and Seasonal Trends of Class A and B Notifiable Infectious Diseases in China: A Retrospective Analysis (Preprint). JMIR Public Health Surveill 2022; 9:e42820. [PMID: 37103994 PMCID: PMC10176137 DOI: 10.2196/42820] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND China is the most populous country globally and has made significant achievements in the control of infectious diseases over the last decades. The 2003 SARS epidemic triggered the initiation of the China Information System for Disease Control and Prevention (CISDCP). Since then, numerous studies have investigated the epidemiological features and trends of individual infectious diseases in China; however, few considered the changing spatiotemporal trends and seasonality of these infectious diseases over time. OBJECTIVE This study aims to systematically review the spatiotemporal trends and seasonal characteristics of class A and class B notifiable infectious diseases in China during 2005-2020. METHODS We extracted the incidence and mortality data of 8 types (27 diseases) of notifiable infectious diseases from the CISDCP. We used the Mann-Kendall and Sen's methods to investigate the diseases' temporal trends, Moran I statistic for their geographical distribution, and circular distribution analysis for their seasonality. RESULTS Between January 2005 and December 2020, 51,028,733 incident cases and 261,851 attributable deaths were recorded. Pertussis (P=.03), dengue fever (P=.01), brucellosis (P=.001), scarlet fever (P=.02), AIDS (P<.001), syphilis (P<.001), hepatitis C (P<.001) and hepatitis E (P=.04) exhibited significant upward trends. Furthermore, measles (P<.001), bacillary and amebic dysentery (P<.001), malaria (P=.04), dengue fever (P=.006), brucellosis (P=.03), and tuberculosis (P=.003) exhibited significant seasonal patterns. We observed marked disease burden-related geographic disparities and heterogeneities. Notably, high-risk areas for various infectious diseases have remained relatively unchanged since 2005. In particular, hemorrhagic fever and brucellosis were largely concentrated in Northeast China; neonatal tetanus, typhoid and paratyphoid, Japanese encephalitis, leptospirosis, and AIDS in Southwest China; BAD in North China; schistosomiasis in Central China; anthrax, tuberculosis, and hepatitis A in Northwest China; rabies in South China; and gonorrhea in East China. However, the geographical distribution of syphilis, scarlet fever, and hepatitis E drifted from coastal to inland provinces during 2005-2020. CONCLUSIONS The overall infectious disease burden in China is declining; however, hepatitis C and E, bacterial infections, and sexually transmitted infections continue to multiply, many of which have spread from coastal to inland provinces.
Collapse
Affiliation(s)
- Junyao Zheng
- China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai, China
- School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Zhang
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Guoquan Shen
- School of Public Administration and Policy, Renmin University of China, Beijing, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | - Yang Zhao
- The George Institute for Global Health, Peking University Health Science Center, Beijing, China
- WHO Collaborating Centre on Implementation Research for Prevention and Control of Noncommunicable Diseases, Melbourne, Australia
| | - Xiaochen He
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Ying Wang
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Rongxin He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Wenna Chen
- Center for Chinese Public Administration Research and School of Government, Sun Yat-sen University, Guangzhou, China
| | - Hao Xue
- Stanford Center on China's Economy and Institutions, Stanford University, Stanford, CA, United States
| | - Yue Shen
- Laboratory for Urban Future, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Yang Fu
- Department of public administration, School of Government, Shenzhen University, Shenzhen, China
| | - Wei-Hong Zhang
- International Centre for Reproductive Health, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Lei Zhang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College, London, United Kingdom
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ying Mao
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
| | - Bin Zhu
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| |
Collapse
|
10
|
Chang Q, Wang K, Zhang H, Li C, Wang Y, Jing H, Li S, Guo Y, Cui Z, Zhang W. Effects of daily mean temperature and other meteorological variables on bacillary dysentery in Beijing-Tianjin-Hebei region, China. Environ Health Prev Med 2022; 27:13. [PMID: 35314583 PMCID: PMC9251629 DOI: 10.1265/ehpm.21-00005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background Although previous studies have shown that meteorological factors such as temperature are related to the incidence of bacillary dysentery (BD), researches about the non-linear and interaction effect among meteorological variables remain limited. The objective of this study was to analyze the effects of temperature and other meteorological variables on BD in Beijing-Tianjin-Hebei region, which is a high-risk area for BD distribution. Methods Our study was based on the daily-scale data of BD cases and meteorological variables from 2014 to 2019, using generalized additive model (GAM) to explore the relationship between meteorological variables and BD cases and distributed lag non-linear model (DLNM) to analyze the lag and cumulative effects. The interaction effects and stratified analysis were developed by the GAM. Results A total of 147,001 cases were reported from 2014 to 2019. The relationship between temperature and BD was approximately liner above 0 °C, but the turning point of total temperature effect was 10 °C. Results of DLNM indicated that the effect of high temperature was significant on lag 5d and lag 6d, and the lag effect showed that each 5 °C rise caused a 3% [Relative risk (RR) = 1.03, 95% Confidence interval (CI): 1.02–1.05] increase in BD cases. The cumulative BD cases delayed by 7 days increased by 31% for each 5 °C rise in temperature above 10 °C (RR = 1.31, 95% CI: 1.30–1.33). The interaction effects and stratified analysis manifested that the incidence of BD was highest in hot and humid climates. Conclusions This study suggests that temperature can significantly affect the incidence of BD, and its effect can be enhanced by humidity and precipitation, which means that the hot and humid environment positively increases the incidence of BD. Supplementary information The online version contains supplementary material available at https://doi.org/10.1265/ehpm.21-00005.
Collapse
Affiliation(s)
- Qinxue Chang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University
| | - Keyun Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University
| | - Honglu Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University
| | - Changping Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention
| | - Huaiqi Jing
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University
| | - Zhuang Cui
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention
| |
Collapse
|
11
|
Zhao R, Gao Q, Hao Q, Wang S, Zhang Y, Li H, Jiang B. The exposure-response association between humidex and bacillary dysentery: A two-stage time series analysis of 316 cities in mainland China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 797:148840. [PMID: 34303970 DOI: 10.1016/j.scitotenv.2021.148840] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/22/2021] [Accepted: 06/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Many studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers. METHODS Daily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers. RESULTS The pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29-1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons. CONCLUSIONS High humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.
Collapse
Affiliation(s)
- Ran Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Qi Gao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Qiang Hao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Shuzi Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Yiwen Zhang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Hao Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Baofa Jiang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China.
| |
Collapse
|
12
|
Wang S, Liu Z, Tong M, Xiang J, Zhang Y, Gao Q, Zhang Y, Lu L, Jiang B, Bi P. Real-time forecasting and early warning of bacillary dysentery activity in four meteorological and geographic divisions in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 761:144093. [PMID: 33360132 DOI: 10.1016/j.scitotenv.2020.144093] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 11/08/2020] [Accepted: 11/20/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Accurate and timely forecasts of bacillary dysentery (BD) incidence can be used to inform public health decision-making and response preparedness. However, our ability to detect BD dynamics and outbreaks remains limited in China. OBJECTIVES This study aims to explore the impacts of meteorological factors on BD transmission in four representative regions in China and to forecast weekly number of BD cases and outbreaks. METHODS Weekly BD and meteorological data from 2014 to 2016 were collected for Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China). A boosted regression tree (BRT) model was conducted to assess the impacts of meteorological factors on BD transmission. Then a real-time forecast and early warning model based on BRT was developed to track the dynamics of BD and detect the outbreaks. The forecasting methodology was compared with generalized additive model (GAM) and seasonal autoregressive integrated moving average model (SARIMA) that have been used to model the BD case data previously. RESULTS Ambient temperature was the most important meteorological factor contributing to the transmission of BD (80.81%-92.60%). A positive effect of temperature was observed when weekly mean temperature exceeded 4 °C, -3 °C, 9 °C and 16 °C in Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China), respectively. BD incidence (Beijing and Shenyang) in temperate cities was more sensitive to high temperature than that in subtropical cities (Chongqing and Shenzhen). The dynamics and outbreaks of BD can be accurately forecasted and detected by the BRT model. Compared to GAM and SARIMA, BRT model showed more accurate forecasting for 1-, 2-, 3-weeks ahead forecasts in Beijing, Shenyang and Shenzhen. CONCLUSIONS Temperature plays the most important role in weather-attributable BD transmission. The BRT model achieved a better performance in comparison with GAM and SARIMA in most study cities, which could be used as a more accurate tool for forecasting and outbreak alert of BD in China.
Collapse
Affiliation(s)
- Shuzi Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
| | - Zhidong Liu
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
| | - Michael Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Jianjun Xiang
- School of Public Health, Fujian Medical University, Fuzhou 350121, Fujian, China; School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Ying Zhang
- School of Public Health, China Studies Centre, The University of Sydney, New South Wales, Australia
| | - Qi Gao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
| | - Yiwen Zhang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
| | - Baofa Jiang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China.
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| |
Collapse
|
13
|
Zhang X, Gu X, Wang L, Zhou Y, Huang Z, Xu C, Cheng C. Spatiotemporal variations in the incidence of bacillary dysentery and long-term effects associated with meteorological and socioeconomic factors in China from 2013 to 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 755:142626. [PMID: 33039932 DOI: 10.1016/j.scitotenv.2020.142626] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 09/23/2020] [Accepted: 09/23/2020] [Indexed: 06/11/2023]
Abstract
Bacillary dysentery is a global public health problem that exhibits manifest spatiotemporal heterogeneity. However, long-term variations and regional determinant factors remain unclear. In this study, the Bayesian space-time hierarchy model was used to identify the long-term spatiotemporal heterogeneity of the incidence of bacillary dysentery and quantify the associations of meteorological factors with the incidence of bacillary dysentery in northern and southern China from 2013 to 2017. GeoDetector was used to quantify the determinant powers of socioeconomic factors in the two regions. The results showed that the incidence of bacillary dysentery peaked in summer (June to August), indicating temporal seasonality. Geographically, the hot spots (high-risk areas) were distributed in northwestern China (Xinjiang, Gansu, and Ningxia) and northern China (including Beijing, Tianjin, and Hebei), whereas the cold spots (low-risk areas) were concentrated in southeastern China (Jiangsu, Zhejiang, Fujian, and Guangdong). Moreover, significant regional differences were found among the meteorological and socioeconomic factors. Average temperature was the dominant meteorological factor in both northern and southern China. In northern and southern China, a 1 °C increase in the average temperature led to an increase of 1.01% and 4.26% in bacillary dysentery risk, respectively. The dominant socioeconomic factors in northern and southern China were per capita gross domestic product and the number of health technicians, with q statistic values of 0.81 and 0.49, respectively. These findings suggest that hot, moist, and overcrowded environments or poor health conditions increase the risk of bacillary dysentery. This study provides suggestions and serves as a basis for surveillance efforts. Further, the suggestions may aid in the control of bacillary dysentery and in the implementation of disease prevention policies.
Collapse
Affiliation(s)
- Xiangxue Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xinchen Gu
- College of Water & Architectural Engineering, Shihezi University, Shihezi 832003, China
| | - Li Wang
- College of Environment and Planning, Henan University, KaiFeng 475001, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, KaiFeng 475001, China
| | - Yuke Zhou
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhentao Huang
- College of Oceanography and Space Informatics, China University of Petroleum, Qingdao 266580, China
| | - 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.
| | - Changxiu Cheng
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| |
Collapse
|
14
|
Quantitative Analysis of Spatial Heterogeneity and Driving Forces of the Thermal Environment in Urban Built-up Areas: A Case Study in Xi’an, China. SUSTAINABILITY 2021. [DOI: 10.3390/su13041870] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Clarifying the spatial heterogeneity of urban heat island (UHI) effect is of great significance for promoting sustainable urban development. A GeoDetector was used to detect the influential natural and society factors. Natural factors (normalized difference vegetation index (NDVI), soil-regulating vegetation index (SAVI), normalized building index (NDBI), and modified normalized difference water index (MNDWI)) as well as society factors (road density (RDD), and population density (POPD)) were selected as driving factors to be tested for their explanatory power for land surface temperature (LST). Results indicated that the Moran’s I index value for the LST of the built-up area is 0.778. The top three factors influencing the LST were NDBI, NDVI, and SAVI, the explanatory power of which was 0.7593, 0.6356, and 0.6356, respectively. The interactive explanatory power for NDBI and MNDWI was 0.8108 and for NDBI and RDD was 0.8002, these two interactions are double enhanced interaction relationships. The results of this study play a guiding role in the development of urban thermal environment regulation schemes and ecological environment planning.
Collapse
|
15
|
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.
Collapse
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.
| |
Collapse
|
16
|
Zhang X, Xu C, Xiao G. Spatial heterogeneity of the association between temperature and hand, foot, and mouth disease risk in metropolitan and other areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 713:136623. [PMID: 31954246 DOI: 10.1016/j.scitotenv.2020.136623] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 01/08/2020] [Accepted: 01/08/2020] [Indexed: 05/26/2023]
Abstract
Interest in assessing the effects of temperature on hand, foot, and mouth disease (HFMD) has increased. However, little evidence is available on spatial heterogeneity in relationship to temperature and HFMD in metropolitan (capital city and municipal districts) and other areas where economic levels are significantly different. In this study, the Bayesian space-time hierarchy model was applied to identify the spatiotemporal heterogeneity of HFMD. GeoDetector was then used to quantify the determinant power of temperature to the disease in regions where the economic level has significant spatial heterogeneity. There was significant spatial heterogeneity in the influence of temperature on the incidence of HFMD in metropolitan and other areas. In metropolitan areas, where the disease risk is higher (hot spots), the HFMD incidence was higher alongside an increase in average temperature. However, in non-metropolitan areas, where the disease risk is lower (cold spots), there was an approximately S-shaped relationship between the temperature and the HFMD risk. More specifically, when the temperature was >25 °C, the HFMD incidence no longer increased monotonically with the increasing temperature. There was significant spatial heterogeneity in the effects of temperature on the HFMD incidence in metropolitan and non-metropolitan areas. This finding may serve as a suggestion and basis for the surveillance and control of this disease and it is conducive to the rational allocation of medical resources in different areas.
Collapse
Affiliation(s)
- XiangXue Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - 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
| |
Collapse
|
17
|
Microbial Indicators and Their Use for Monitoring Drinking Water Quality—A Review. SUSTAINABILITY 2020. [DOI: 10.3390/su12062249] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
An increase in the incidence of water-borne human diseases, such as diarrhea and emesis, has occurred due to drinking polluted water. These water-borne diseases can lead to death, if correct treatment is not provided. Assuring that drinking water quality is safe has been a crucial challenge for public health. Water contamination with pathogenic microorganisms represents a seriously increased threat to human health. Currently, different microorganisms are being used as the primary indicator to assess water quality total coliform and Escherichia coli (E. coli) being the most common. However, increasing the occurrence of water-borne illness from sources deemed safe by the microbial standard criteria has raised the question—are these microbial indicators reliable and sensitive enough to ensure water quality? Currently, other microorganisms including bacteria, enteric virus, and protozoa are being tested and used in different countries as alternative indicators to monitor water quality. It is necessary to study the diverse water quality indicator systems used throughout the world and their efficacy with the present water quality. Although water quality standards suggest adding pathogenic microorganisms such as enteric virus as an indicator, China only uses pathogenic E. coli, protozoa. Pin-pointing the shortage of the current water quality indicator system in China is crucial in order to propose changes in future water quality indicator systems.
Collapse
|
18
|
Meng Q, Liu X, Xie J, Xiao D, Wang Y, Deng D. Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors. Environ Health Prev Med 2019; 24:82. [PMID: 31883513 PMCID: PMC6935186 DOI: 10.1186/s12199-019-0829-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 11/12/2019] [Indexed: 12/19/2022] Open
Abstract
Background This study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD. Methods In this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence. Results In total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R2) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively. Conclusion From 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.
Collapse
Affiliation(s)
- Qiuyu Meng
- School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, 400016, China
| | - Xun Liu
- Department of Healthcare-associated Infection Control, The Second Affiliated Hospital of Military Medical University, Chongqing, 400037, China
| | - Jiajia Xie
- School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, 400016, China
| | - Dayong Xiao
- Institute for Prevention and Control of Endemic and Parasitic Diseases, Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Yi Wang
- School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, 400016, China
| | - Dan Deng
- School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, 400016, China.
| |
Collapse
|
19
|
Liu H, Song G, He N, Zhai S, Song H, Kong Y, Liang L, Liu X. Spatial-temporal variation and risk factor analysis of hand, foot, and mouth disease in children under 5 years old in Guangxi, China. BMC Public Health 2019; 19:1491. [PMID: 31703735 PMCID: PMC6842152 DOI: 10.1186/s12889-019-7619-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 09/13/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Hand, foot and mouth disease (HFMD) incidence is a critical challenge to disease control and prevention in parts of China, particularly Guangxi. However, the association between socioeconomic factors and meteorological factors on HFMD is still unclear. METHODS This study applied global and local Moran's I to examine the spatial pattern of HFMD and series analysis to explore the temporal pattern. The effects of meteorological factors and socioeconomic factors on HFMD incidence in Guangxi, China were analyzed using GeoDetector Model. RESULTS This study collected 45,522 cases from 87 counties in Guangxi during 2015, among which 43,711 cases were children aged 0-4 years. Temporally, there were two HFMD risk peaks in 2015. One peak was in September with 7890 cases. The other appeared in May with 4687 cases of HFMD. A high-risk cluster was located in the valley areas. The tertiary industry, precipitation and second industry had more influence than other risk factors on HFMD incidence with explanatory powers of 0.24, 0.23 and 0.21, respectively. The interactive effect of any two risk factors would enhance the risk of HFMD. CONCLUSIONS This study suggests that precipitation and tertiary industry factors might have stronger effects on the HFMD incidence in Guangxi, China, compared with other factors. High-risk of HFMD was identified in the valley areas characterized by high temperature and humidity. Local government should pay more attention and strengthen public health services level in this area.
Collapse
Affiliation(s)
- Huan Liu
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
| | - Genxin Song
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
| | - Nan He
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
| | - Shiyan Zhai
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
- Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, 475004 Henan China
| | - Hongquan Song
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
- Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, 475004 Henan China
| | - Yunfeng Kong
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004 Henan China
- Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, 475004 Henan China
| | - Lizhong Liang
- The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001 China
| | - Xiaoxiao Liu
- Department of Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, Canada
| |
Collapse
|
20
|
Wen X, Zheng H, Yuan F, Zhu H, Kuang D, Shen Z, Lu Y, Yuan Z. Comparative Study of Two Methods of Enteric Virus Detection and Enteric Virus Relationship with Bacterial Indicator in Poyang Lake, Jiangxi, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16183384. [PMID: 31547457 PMCID: PMC6765907 DOI: 10.3390/ijerph16183384] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Revised: 08/28/2019] [Accepted: 09/02/2019] [Indexed: 02/01/2023]
Abstract
Currently, water contaminated with fecal matter poses a threat to public health and safety. Thus, enteric viruses are tested for as a part of water quality indicator assays; however, enteric viruses have not yet been listed in the criteria. Effective and sensitive methods for detecting enteric viruses are required in order to increase water safety. This study utilized enteric viruses as possible alternative indicators of water quality to examine fresh water in six sites in Poyang Lake, Nanchang, Jiangxi Province. The presence of norovirus geno-groups II (NoV GII), enteroviruses (EoV) and adenoviruses (AdV) were determined using Tianjin's protocol and Hawaii's protocol during a six month period from 2016-2017. The former used an electropositive material method for viral concentration and Taqman-q reverse transcription polymerase chain reaction (RT-PCR) to detect enteric viruses; while the latter used a filtration-based method for viral concentration and RT-PCR for enteric virus detection. There is a statistically significant difference between Tianjin's method and Hawaii's method for the detection of enteric viruses, such as NoV GII, EoV, and AdV (n = 36, p < 0.001). The enteric viruses showed no significant positive correlation with bacteria indicators (n = 36, p > 0.05). These data stress the need for additional indicators when establishing water quality systems, and the possibility of using enteric viruses as water quality indicators. It has become essential to improve shortcomings in order to search for an adequate method to detect enteric viruses in water and to implement such method in water quality monitoring.
Collapse
Affiliation(s)
- Xiaotong Wen
- School of Public Health, Nanchang University, Nanchang, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang 330006, China.
| | - Huilie Zheng
- School of Public Health, Nanchang University, Nanchang, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang 330006, China.
| | - Fang Yuan
- Office of Public Health Studies, University of Hawaii at Mānoa, Honolulu, HI 96822, USA.
| | - Hui Zhu
- School of Public Health, Nanchang University, Nanchang, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang 330006, China.
| | - Duyi Kuang
- Office of Public Health Studies, University of Hawaii at Mānoa, Honolulu, HI 96822, USA.
| | - Zhiqiang Shen
- Tianjin Institute of Health and Environmental Medicine, Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin 300050, China.
| | - Yuanan Lu
- School of Public Health, Nanchang University, Nanchang, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang 330006, China.
- Office of Public Health Studies, University of Hawaii at Mānoa, Honolulu, HI 96822, USA.
| | - Zhaokang Yuan
- School of Public Health, Nanchang University, Nanchang, Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang 330006, China.
| |
Collapse
|
21
|
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: 15] [Impact Index Per Article: 3.0] [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.
Collapse
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
| |
Collapse
|
22
|
Liu L, Zhong Y, Ao S, Wu H. Exploring the Relevance of Green Space and Epidemic Diseases Based on Panel Data in China from 2007 to 2016. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E2551. [PMID: 31319532 PMCID: PMC6679052 DOI: 10.3390/ijerph16142551] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 07/13/2019] [Accepted: 07/15/2019] [Indexed: 12/12/2022]
Abstract
Urban green space has been proven effective in improving public health in the contemporary background of planetary urbanization. There is a growing body of literature investigating the relationship between non-communicable diseases (NCDs) and green space, whereas seldom has the correlation been explored between green space and epidemics, such as dysentery, tuberculosis, and malaria, which still threaten the worldwide situation of public health. Meanwhile, most studies explored healthy issues with the general green space, public green space, and green space coverage, respectively, among which the different relevance has been rarely explored. This study aimed to examine and compare the relevance between these three kinds of green space and incidences of the three types of epidemic diseases based on the Panel Data Model (PDM) with the time series data of 31 Chinese provinces from 2007 to 2016. The results indicated that there exists different, or even opposite, relevance between various kinds of green space and epidemic diseases, which might be associated with the process of urban sprawl in rapid urbanization in China. This paper provides a reference for re-thinking the indices of green space in building healthier and greener cities.
Collapse
Affiliation(s)
- Lingbo Liu
- Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
| | - Yuni Zhong
- Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
| | - Siya Ao
- Department of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China.
| | - Hao Wu
- Department of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China
| |
Collapse
|
23
|
Abstract
Dengue fever (DF) has been a growing public-health concern in China since its emergence in Guangdong Province in 1978. Of all the regions that have experienced dengue outbreaks in mainland China, the city of Guangzhou is the most affected. This study aims to investigate the potential risk factors for dengue virus (DENV) transmission in Guangzhou, China, from 2006 to 2014. The impact of risk factors on DENV transmission was qualified by the q-values calculated using a novel spatial-temporal method, the GeoDetector model. Both climatic and socioeconomic factors were considered. The impacts on DF incidence of each single factor and the interaction of two factors were analysed. The results show that the number of days with rainfall of the month before last has the highest determinant power, with a q-value of 0.898 (P < 0.01); the q-values of the other factors related to temperature and precipitation were around 0.38–0.50. Integrating a Pearson correlation analysis, nonlinear associations were found between the DF incidence in Guangzhou and the climatic factors considered. The coupled impact of the different variables considered was enhanced compared with their individual effects. In addition, an increased number of tourists in the city were associated with a high incidence of DF. This study demonstrates that the number of rain days in a month has great influence on the DF incidence of the month after next; the temperature and precipitation have nonlinear impacts on the DF incidence in Guangzhou; both the domestic and overseas tourists coming to the city increase the risk of DENV transmission. These findings are useful in the risk assessment of DENV transmission, to predict DF outbreaks and to implement preventive DF reduction strategies.
Collapse
|
24
|
Phung D, Chu C, Tran DN, Huang C. Spatial variation of heat-related morbidity: A hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 637-638:1559-1565. [PMID: 29801249 DOI: 10.1016/j.scitotenv.2018.05.131] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 05/10/2018] [Accepted: 05/10/2018] [Indexed: 06/08/2023]
Abstract
This study examined spatial variability of heat-related morbidity in multiple districts of the Mekong Delta Region (MDR), Vietnam. It was conducted in 132 district/cities of the MDR. We used a series of hierarchical Bayesian models to examine the region-wide and district-specific association between temperatures and hospitalizations during the period of 2010-2013. The potential effects of seasonality, long-term trends, day of the week and holidays were controlled in the models. We also examined influences of socio-demographic factors on the temperature-hospitalization relationship. The results indicate that an increase of 5 °C in average temperature was associated with a 6.1% increase (95%CI: 5.9, 6.2) in region-wide hospital admissions. However, the district-level risks ranged from a 55.2% decrease {95%CI: (-54), (-56)} to a 24.4% increase (24.3-24.6) in admissions per 5 °C increase in average temperature. This reflects the heterogeneous magnitudes of temperature-hospitalization risk across districts. The results also indicate that temperature-hospitalization risk increased by 1.3% (95%CI: 1.2-1.4), for each increase of 1000 persons/km2 in population density, 2.1% (95%CI: 2.04-2.11) for each 1% increase in percent of females, and 2.7% (95%CI: 2.6-2.8) for each 1% increase in percent of pre-school students. In contrast, the temperature-related hospitalization risk decreased up to 6.8% {(95%CI: (-6.6)-(-6.9)} for each 1% increase in rural population. Public health intervention measures for both short-term and long-term effects of heat-related health risk should be developed with consideration of the use of city/district scale for the factors rather than the province scale. The province scale of factors does not accurately represent the variability of health risk due to exposure to high temperatures.
Collapse
Affiliation(s)
- Dung Phung
- Department of Health Policy & Management, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Cordia Chu
- Centre for Environment and Population Health, Griffith University, Queensland, Australia
| | - Dang Ngoc Tran
- Faculty of Public Health, University of Medicine and Pharmacy, Ho Chi Minh City, Viet Nam
| | - Cunrui Huang
- Department of Health Policy & Management, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| |
Collapse
|