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Huang F, Bello ST. Spatiotemporal analysis of regional and age differences in tuberculosis prevalence in mainland China. Trop Med Int Health 2024; 29:833-841. [PMID: 39044660 DOI: 10.1111/tmi.14037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024]
Abstract
Globally, tuberculosis is a leading cause of infectious disease deaths. China ranks third among the 30 high-burden countries for tuberculosis and accounts for approximately 7.4% of the cases reported worldwide. Since very few studies have investigated the age difference in tuberculosis prevalence in mainland China, therefore, the preliminary characterisation of age differences in tuberculosis patients is not well understood. The data of reported sputum smear-positive, tuberculosis and sputum smear-negative cases in 340 prefectures from mainland China were extracted from the China Information System for Disease Control and Prevention from January 2009 to December 2018. Multiple statistical analysis and GIS techniques were used to investigate the temporal trend and identify the spatial distribution of sputum smear-positive, tuberculosis and sputum smear-negative cases in the study area. The results showed that the incidence of sputum smear-positive and tuberculosis has dropped to a stable level, while sputum smear-negative exhibited a rising trend. Additionally, sputum smear-positive, tuberculosis and sputum smear-negative are still highly prevalent in northwestern and southwestern regions of China. Interestingly, the young adult group (20-50 age) and elder group (>50 age) are more susceptible to being infected with tuberculosis, while lower infection levels were recorded in the juvenile group (<20 age). The present study investigated the temporal-spatial distribution of sputum smear-positive, tuberculosis and sputum smear-negative cases in mainland China before the COVID-19 pandemic breakout, which would help the government agency establish an effective mechanism of tuberculosis prevention in high-risk periods and high-risk areas in the study region.
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Affiliation(s)
- Fengwen Huang
- Department of Neuroscience, City University of Hong Kong, Kowloon Tong, China
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China
| | - Stephen Temitayo Bello
- Department of Neuroscience, City University of Hong Kong, Kowloon Tong, China
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China
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2
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Xu Z, Feng J, Xing S, Liu Y, Chen Y, Li J, Feng Y. Global trends and spatial drivers of diabetes mellitus mortality, 1990-2019: a systematic geographical analysis. Front Endocrinol (Lausanne) 2024; 15:1370489. [PMID: 38681766 PMCID: PMC11045957 DOI: 10.3389/fendo.2024.1370489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 03/27/2024] [Indexed: 05/01/2024] Open
Abstract
Objective Diabetes mellitus is the leading cause of death worldwide, and multiple risk factors associated with diabetes mortality. Methods Employing spatial statistics, we characterized the spatial distribution and patterns of diabetes mortality, and revealed the spatial relationship between diabetes mortality and 11 socioeconomic and environmental risk factors at the country level, from 1990 to 2019. Results Globally, significantly high rates of diabetes mortality were primarily clustered in countries with limited land areas or located on islands, such as Fiji, Kiribati, Eswatini, and Trinidad and Tobago. Countries with weaker economic independence are more likely to have higher diabetes mortality rates. In addition, the impact of socioeconomic and environmental factors was significant at the country level, involving health expenditure, number of physicians, household and ambient air pollution, smoking, and alcohol consumption. Notably, the spatial relationship between diabetes mortality and ambient air pollution, as well as alcohol consumption, showed negative correlations. Countries with high diabetes mortality rates generally had lower levels of ambient air pollution and alcohol consumption. Conclusion The study highlights the spatial clustering of diabetes mortality and its substantial variation. While many risk factors can influence diabetes mortality, it's also essential to consider the level of these factors at the country level. Tailoring appropriate interventions based on specific national circumstances holds the potential to more effectively mitigate the burden of diabetes mortality.
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Affiliation(s)
- Zejia Xu
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Jianheng Feng
- Faculty of Innovation and Design, City University of Macau, Macao, Macao SAR, China
| | - Siyi Xing
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Yin Liu
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Yuting Chen
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Jie Li
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, China
- Key Laboratory of Philosophy and Social Sciences in Guangdong Province of Maritime Silk Road of Guangzhou University (GD22TWCXGC15), Guangzhou, China
| | - Yunhui Feng
- Center for Interdisciplinary Health Management Studies, School of Physical Education & Sports Science, Guangzhou University, Guangzhou, China
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Li J, Xu Z, Wang H, Li L, Zhu H. Geospatial analysis of spatial distribution, patterns, and relationships of health status in the belt and road initiative. Sci Rep 2024; 14:204. [PMID: 38168550 PMCID: PMC10761736 DOI: 10.1038/s41598-023-50663-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 12/22/2023] [Indexed: 01/05/2024] Open
Abstract
The Health Silk Road plays a crucial role in the Belt and Road Initiative, and comprehending the health status within the participating countries is fundamental for fostering cooperation in public health. This paper collected five health indicators to represent the health status of the Belt and Road countries. Employing spatial statistics, the spatial patterns of health indicators and the associations with influencing factors were investigated. The utilized spatial statistics encompass spatial autocorrelation methods, geographical detector and spatial lag model. The results revealed obvious disparities and significant positive spatial autocorrelation of health indicators within the Belt and Road countries. Specifically, countries in Sub-Saharan Africa exhibited significant clustering of limited health indicators, while countries in Europe and Central Asia demonstrated significant clustering of robust health indicators. Furthermore, the health indicators exhibited significant spatial heterogeneity and association with the influencing factors. Universal health coverage, household air pollution, and the prevalence of undernourishment emerge as influential factors affecting health indicators. Overall, our findings highlighted complex influencing factors that contributed to the profound health inequalities across the Belt and Road countries. These factors should be duly considered in public health collaborations within the Belt and Road Initiative.
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Affiliation(s)
- Jie Li
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, 510006, China
- Key Laboratory of Philosophy and Social Sciences in Guangdong Province of Maritime Silk Road of Guangzhou University (GD22TWCXGC15), Guangzhou, 510006, China
| | - Zejia Xu
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, 510006, China
| | - Hongxi Wang
- Guangdong Federation of Social Sciences, Guangzhou, 510000, China
| | - Lingling Li
- Guangdong Federation of Social Sciences, Guangzhou, 510000, China
| | - Hong Zhu
- School of Geographical Sciences and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.
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Liu Y, Xu Y, Li Y, Wei H. Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China. GEOHEALTH 2023; 7:e2023GH000794. [PMID: 37275567 PMCID: PMC10234758 DOI: 10.1029/2023gh000794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/30/2023] [Accepted: 04/26/2023] [Indexed: 06/07/2023]
Abstract
Lung cancer has become one of the most prevalent cancers in the last several decades. Studies have documented that most cases of lung cancer are caused by inhaling environmental carcinogens while how external environmental factors lead to individual lung cancer is still an open issue as the pathogenesis may come from the combined action of multiple environmental factors, and such pathogenic mechanism may vary from region to region. Based on the data of lung cancer cases from hospitals at the county level in Henan from 2016 to 2020, we analyzed the response relationship between lung cancer incidence and physical ambient factors (air quality, meteorological conditions, soil vegetation) and socioeconomic factors (occupational environment, medical level, heating mode, smoking behavior). We used a Bayesian spatio-temporal interaction model to evaluate the relative risk of disease in different regions. The results showed that smoking was still the primary determinant of lung cancer, but the influence of air quality was increasing year by year, with meteorological conditions and occupational environment playing a synergistic role in this process. The high-risk areas were concentrated in the plains of East and Central Henan and the basin of South Henan, while the low-risk areas were concentrated in the hilly areas of North and West Henan, which were related to the topography of Henan. Our study provides a better understanding of the environmental determinants of lung cancer which will help refine existing prevention strategies and recognize the areas where actions are required to prevent environment and occupation related lung cancer.
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Affiliation(s)
- Yan Liu
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Yanqing Xu
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Yuchen Li
- MRC Epidemiology UnitSchool of Clinical MedicineUniversity of CambridgeCambridgeUK
| | - Haitao Wei
- The School of the Geo‐Science & TechnologyZhengzhou UniversityZhengzhouChina
- Joint Laboratory of Eco‐MeteorologyZhengzhou UniversityZhengzhouChina
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Li CH, Mao JJ, Wu YJ, Zhang B, Zhuang X, Qin G, Liu HM. Combined impacts of environmental and socioeconomic covariates on HFMD risk in China: A spatiotemporal heterogeneous perspective. PLoS Negl Trop Dis 2023; 17:e0011286. [PMID: 37205641 DOI: 10.1371/journal.pntd.0011286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/05/2023] [Indexed: 05/21/2023] Open
Abstract
BACKGROUND Understanding geospatial impacts of multi-sourced influencing factors on the epidemic of hand-foot-and-mouth disease (HFMD) is of great significance for formulating disease control policies tailored to regional-specific needs, yet the knowledge is very limited. We aim to identify and further quantify the spatiotemporal heterogeneous effects of environmental and socioeconomic factors on HFMD dynamics. METHODS We collected monthly province-level HFMD incidence and related environmental and socioeconomic data in China during 2009-2018. Hierarchical Bayesian models were constructed to investigate the spatiotemporal relationships between regional HFMD and various covariates: linear and nonlinear effects for environmental covariates, and linear effects for socioeconomic covariates. RESULTS The spatiotemporal distribution of HFMD cases was highly heterogeneous, indicated by the Lorenz curves and the corresponding Gini indices. The peak time (R2 = 0.65, P = 0.009), annual amplitude (R2 = 0.94, P<0.001), and semi-annual periodicity contribution (R2 = 0.88, P<0.001) displayed marked latitudinal gradients in Central China region. The most likely cluster areas for HFMD were located in south China (Guangdong, Guangxi, Hunan, Hainan) from April 2013 to October 2017. The Bayesian models achieved the best predictive performance (R2 = 0.87, P<0.001). We found significant nonlinear associations between monthly average temperature, relative humidity, normalized difference vegetation index and HFMD transmission. Besides, population density (RR = 1.261; 95%CI, 1.169-1.353), birth rate (RR = 1.058; 95%CI, 1.025-1.090), real GDP per capita (RR = 1.163; 95%CI, 1.033-1.310) and school vacation (RR = 0.507; 95%CI, 0.459-0.559) were identified to have positive or negative effects on HFMD respectively. Our model could successfully predict months with HFMD outbreaks versus non-outbreaks in provinces of China from Jan 2009 to Dec 2018. CONCLUSIONS Our study highlights the importance of refined spatial and temporal data, as well as environmental and socioeconomic information, on HFMD transmission dynamics. The spatiotemporal analysis framework may provide insights into adjusting regional interventions to local conditions and temporal variations in broader natural and social sciences.
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Affiliation(s)
- Chun-Hu Li
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
| | - Jun-Jie Mao
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
| | - You-Jia Wu
- Department of Pediatrics, Affiliated Hospital of Nantong University, Nantong, China
| | - Bin Zhang
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong, China
| | - Xun Zhuang
- Department of Epidemiology and Biostatistics, School of Public Health of Nantong University, Nantong, China
| | - Gang Qin
- Joint Division of Clinical Epidemiology, Affiliated Hospital of Nantong University, School of Public Health of Nantong University, Nantong, China
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong, China
| | - Hong-Mei Liu
- School of Transportation and Civil Engineering of Nantong University, Nantong, China
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Zhao D, Zhang H, Zhang R, He S. Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China. BMC Public Health 2023; 23:619. [PMID: 37003988 PMCID: PMC10064964 DOI: 10.1186/s12889-023-15543-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
BACKGROUND This study aimed to construct a more accurate model to forecast the incidence of hand, foot, and mouth disease (HFMD) in mainland China from January 2008 to December 2019 and to provide a reference for the surveillance and early warning of HFMD. METHODS We collected data on the incidence of HFMD in mainland China between January 2008 and December 2019. The SARIMA, SARIMA-BPNN, and SARIMA-PSO-BPNN hybrid models were used to predict the incidence of HFMD. The prediction performance was compared using the mean absolute error(MAE), mean squared error(MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation analysis. RESULTS The incidence of HFMD in mainland China from January 2008 to December 2019 showed fluctuating downward trends with clear seasonality and periodicity. The optimal SARIMA model was SARIMA(1,0,1)(2,1,2)[12], with Akaike information criterion (AIC) and Bayesian Schwarz information criterion (BIC) values of this model were 638.72, 661.02, respectively. The optimal SARIMA-BPNN hybrid model was a 3-layer BPNN neural network with nodes of 1, 10, and 1 in the input, hidden, and output layers, and the R-squared, MAE, and RMSE values were 0.78, 3.30, and 4.15, respectively. For the optimal SARIMA-PSO-BPNN hybrid model, the number of particles is 10, the acceleration coefficients c1 and c2 are both 1, the inertia weight is 1, the probability of change is 0.95, and the values of R-squared, MAE, and RMSE are 0.86, 2.89, and 3.57, respectively. CONCLUSIONS Compared with the SARIMA and SARIMA-BPNN hybrid models, the SARIMA-PSO-BPNN model can effectively forecast the change in observed HFMD incidence, which can serve as a reference for the prevention and control of HFMD.
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Affiliation(s)
- Daren Zhao
- Department of Medical Administration, Sichuan Provincial Orthopedics Hospital, Chengdu, Sichuan, People's Republic of China
| | - Huiwu Zhang
- Department of Medical Administration, Sichuan Provincial Orthopedics Hospital, Chengdu, Sichuan, People's Republic of China.
| | - Ruihua Zhang
- School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
- General Practitioners Training Center of Sichuan Province, Chengdu, Sichuan, People's Republic of China.
| | - Sizhang He
- Department of Information and Statistics, The Affiliated Hospital of Southwest Medical University, Luzhou, 64600, Sichuan, China
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Spatiotemporal cluster patterns of hand, foot, and mouth disease at the province level in mainland China, 2011–2018. PLoS One 2022; 17:e0270061. [PMID: 35994464 PMCID: PMC9394824 DOI: 10.1371/journal.pone.0270061] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 06/03/2022] [Indexed: 11/19/2022] Open
Abstract
Although three monovalent EV-A71 vaccines have been launched in mainland China since 2016, hand, foot, and mouth disease (HFMD) still causes a considerable disease burden in China. Vaccines’ use may change the epidemiological characters of HFMD. Spatial autocorrelation analysis and space-time scan statistics analysis were used to explore the spatiotemporal distribution pattern of this disease at the provincial level in mainland China. The effects of meteorological factors, socio-economic factors, and health resources on HFMD incidence were analyzed using Geodetector. Interrupted time series (ITS) was used to analyze the impact of the EV-A71 vaccine on the incidence of HFMD. This study found that the median annual incidence of HFMD was 153.78 per 100,000 (ranging from 120.79 to 205.06) in mainland China from 2011 to 2018. Two peaks of infections were observed per year. Children 5 years and under were the main morbid population. The spatial distribution of HFMD was presented a significant clustering pattern in each year (P<0.001). The distribution of HFMD cases was clustered in time and space. The range of cluster time was between April and October. The most likely cluster appeared in the southern coastal provinces (Guangxi, Guangdong, Hainan) from 2011 to 2017 and in the eastern coastal provinces (Shanghai, Jiangsu, Zhejiang) in 2018. The spatial heterogeneity of HFMD incidence could be attributed to meteorological factors, socioeconomic factors, and health resource. After introducing the EV-A71 vaccine, the instantaneous level of HFMD incidence decreased at the national level, and HFMD incidence trended downward in the southern coastal provinces and increased in the eastern coastal provinces. The prevention and control policies of HFMD should be adapted to local conditions in different provinces. It is necessary to advance the EV-A71 vaccination plan, expand the vaccine coverage and develop multivalent HFMD vaccines as soon as possible.
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Liu Y, Tian Z, He X, Wang X, Wei H. Short-term effects of indoor and outdoor air pollution on the lung cancer morbidity in Henan Province, Central China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2022; 44:2711-2731. [PMID: 34403047 DOI: 10.1007/s10653-021-01072-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 08/09/2021] [Indexed: 06/13/2023]
Abstract
Lung cancer is one of the most common cancer types and a major cause of death. The relationship between lung cancer morbidity and exposure to air pollutants is of particular concern. However, the relationship and difference in lung cancer morbidity between indoor and outdoor air pollution effects remain unclear. In this paper, the aim was to comprehensively investigate the spatial relationships between the lung cancer morbidity and indoor-outdoor air pollution in Henan based on the standard deviation ellipse, spatial autocorrelation analysis and GeoDetector. The results indicated that (1) the spatial distribution of lung cancer morbidity was related to the geomorphology, while high-morbidity areas were concentrated in the plains and basins of Central, Eastern and Southern Henan. (2) Among the selected outdoor air pollutants, PM2.5, NO2, SO2, O3 and CO were significantly correlated with the lung cancer morbidity. The degree of indoor air pollution was measured by the use of heating energy, and the proportions of coal-heating households, households with coal/biomass stoves and households with heated kangs were highly decisive in regard to the lung cancer morbidity. (3) The interaction between two factors was more notable than a single factor in explaining the lung cancer morbidity. Moreover, the interaction type was mainly nonlinear enhancement, and the proportion of households with coal/biomass stoves imposed the strongest interaction effect on the other factors.
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Affiliation(s)
- Yan Liu
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450000, China
- Joint Laboratory of Ecological Meteorology, Chinese Academy of Meteorological Sciences and Zhengzhou University, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Zhihui Tian
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450000, China
- Joint Laboratory of Ecological Meteorology, Chinese Academy of Meteorological Sciences and Zhengzhou University, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaohui He
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450000, China
- Joint Laboratory of Ecological Meteorology, Chinese Academy of Meteorological Sciences and Zhengzhou University, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaolei Wang
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450000, China
- Joint Laboratory of Ecological Meteorology, Chinese Academy of Meteorological Sciences and Zhengzhou University, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Haitao Wei
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450000, China.
- Joint Laboratory of Ecological Meteorology, Chinese Academy of Meteorological Sciences and Zhengzhou University, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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Yang R, Ren F, Xu W, Ma X, Zhang H, He W. China's ecosystem service value in 1992-2018: Pattern and anthropogenic driving factors detection using Bayesian spatiotemporal hierarchy model. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 302:114089. [PMID: 34775337 DOI: 10.1016/j.jenvman.2021.114089] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 09/30/2021] [Accepted: 11/08/2021] [Indexed: 06/13/2023]
Abstract
Maintaining ecosystem services (ESs) and reducing ecosystem degradation are important goals for achieving sustainable development. However, under the influence of various anthropogenic factors, the total ecosystem service value (ESV) of China continues to decline, and the detailed processes involved in this decline are unclear. In this paper, a new long-term annual land cover dataset (the Climate Change Initiative Land Cover or CCI-LC dataset) with a spatial resolution of 300 m was employed to estimate the ESV of China, and Bayesian spatiotemporal hierarchy models were built to examine the detailed patterns and anthropogenic driving factors. From 1992 to 2018, the total ESV of China fluctuated and decreased from 3265.3 to 3253.29 billion US$ at an average rate of 0.55 billion US$ per year. Furthermore, the model revealed the spatiotemporal variations in the ESV pattern, and simultaneously detected the influences of 9 variables related to economic factors, population, infrastructure, energy, agriculture and ecological restoration, providing a convenient and effective method for ESV spatiotemporal analysis. The results enrich our understanding of the detailed spatiotemporal variation and anthropogenic driving factors underlying the declining ESV in China. These findings have substantial guiding implications for adjusting ecological regulation policies.
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Affiliation(s)
- Renfei Yang
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China.
| | - Fu Ren
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China; Key Laboratory of GIS, Ministry of Education, Wuhan University, Wuhan, 430079, China.
| | - Wenxuan Xu
- School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210023, China.
| | - Xiangyuan Ma
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China.
| | - Hongwei Zhang
- Electronic Information School, Wuhan University, Wuhan, 430079, China.
| | - Wenwen He
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China.
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Laor P, Apidechkul T, Khunthason S, Keawdounglek V, Sudsandee S, Fakkaew K, Siriratruengsuk W. Association of environmental factors and high HFMD occurrence in northern Thailand. BMC Public Health 2020; 20:1829. [PMID: 33256665 PMCID: PMC7706220 DOI: 10.1186/s12889-020-09905-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 11/17/2020] [Indexed: 02/02/2023] Open
Abstract
Background The major population vulnerable to hand, foot and mouth disease (HFMD) is children aged less than 5 years, particularly those who are cared for at day care centers (DCCs). This study aimed to assess the associations of environmental and sanitation factors with high HFMD occurrence rates in DCCs of northern Thailand. Methods A case-control study was used to gather information from caregivers and local government administrative officers. DCCs in areas with high and low HFMD occurrence rates were the settings for this study. A validated questionnaire was used to collect environmental and sanitation information from the DCCs. In-depth interviews were used to collect information from selected participants who were working at DCCs and from local government administrative officers on the HFMD capacity and prevention and control strategies in DCCs. Logistic regression analysis was used to determine the associations between many environmental factors and HFMD at the α = 0.05 significance level while the content analysis was used to extract information from the interviews. Results Two variables were found to be associated with a high rate of HFMD occurrence: the number of sinks available in restrooms and the DCC size. Children attending DCCs that did not meet the standard in terms of the number of sinks in restrooms had a greater chance of contracting HFMD than children who were attending DCCs that met the standard (AOR = 4.21; 95% CI = 1.13–15.04). Children who were attending a large-sized DCC had a greater chance of contracting HFMD than those attending a small-sized DCC (AOR = 3.28; 95% CI = 1.21–5.18). The yearly budget allocation and the strategies for HFMD control and prevention, including collaborations among stakeholders for HFMD control and prevention in DCCs, were associated with the effectiveness of HFMD control and prevention. Conclusions The number of sinks in restrooms and DCC size are major concerns for HFMD outbreaks. Sufficient budget allocation and good collaboration contribute to effective strategies for preventing and controlling HFMD in DCCs.
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Affiliation(s)
- Pussadee Laor
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand.
| | - Tawatchai Apidechkul
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand. .,Center of Excellence for the Hill tribe Health Research, Mae Fah Luang University, Muang Chiang Rai, Thailand.
| | - Siriyaporn Khunthason
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand.,Center of Excellence for the Hill tribe Health Research, Mae Fah Luang University, Muang Chiang Rai, Thailand
| | - Vivat Keawdounglek
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Suntorn Sudsandee
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Krailak Fakkaew
- School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
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11
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Zhang X, Gu X, Cheng C, Yang D. Spatiotemporal heterogeneity of PM 2.5 and its relationship with urbanization in North China from 2000 to 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 744:140925. [PMID: 32688000 DOI: 10.1016/j.scitotenv.2020.140925] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/25/2020] [Accepted: 07/10/2020] [Indexed: 05/13/2023]
Abstract
Fine particulate matter (PM2.5) pollution is becoming an increasing global concern due to rapid urbanization and socioeconomic development, especially in North China. Although North China experiences poor air quality and high PM2.5 concentrations, their spatial heterogeneity and relationship with the relative spatial risks of air pollution have not been explored. Therefore, in this study, the temporal variation trends (slope values) of the PM2.5 concentrations in North China from 2000 to 2017 were first quantified using the unitary linear regression model, and the Bayesian space-time hierarchy model was introduced to characterize their spatiotemporal heterogeneity. The spatial lag model was then used to examine the determinant power of urbanization and other socioeconomic factors. Additionally, the correlation between the spatial relative risks (probability of a region becoming more/less polluted relative to the average PM2.5 concentrations of the study area), and the temporal variation trends of the PM2.5 concentrations were quantified using the bivariate local indicators of spatial association model. The results showed that the PM2.5 concentrations increased during 2000-2017, and peaked in 2007 and 2013. Spatially, the cities at high risk of PM2.5 pollution were mainly clustered in southeastern Hebei, northern Henan, and western Shandong where the slope values were low, as demonstrated by the value of Moran's I (-0.56). Moreover, urbanization and road density were both positively correlated with PM2.5 pollution, while the proportion of tertiary industry was negatively correlated. Furthermore, a notable increasing trend was observed in some cities, such as Tianjin, Zaozhuang, Qingdao, and Xinyang. These findings can contribute to the development of effective policies from the perspective of rapid urbanization to relieve and reduce PM2.5 pollution.
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Affiliation(s)
- Xiangxue Zhang
- Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
| | - Xinchen Gu
- College of Water & Architectural Engineering, Shihezi University, Shihezi 832003, China
| | - Changxiu Cheng
- Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; National Tibetan Plateau Data Center, Beijing 100101, China.
| | - Dongyang Yang
- Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475004, China.
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12
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Abstract
To examine the effects of temperature on the daily cases of hand, foot, and mouth disease (HFMD).Data on the daily cases of HFMD in Lanzhou from 2008 to 2015 were obtained, and meteorological data from the same period were collected. A distributed lag nonlinear model was fitted to reveal the relationship between the daily mean temperature and the daily cases of HFMD.From 2008 to 2015, 25,644 cases were reported, of which children under 5 years of age accounted for 78.68% of cases. The highest peak of HFMD cases was usually reported between April to July each year. An inverse V-shaped relationship was observed between daily mean temperature and HFMD cases; a temperature of 18°C was associated with a maximum risk of HFMD. The relative risk (RR) was 1.57 (95% confidence interval: 1.23-1.23), and boys and children aged 3 to 5 years were populations with the highest risk. The cumulative risks of high temperature (20.2°C and 25.2°C) in the total, age-specific, and gender-specific groups peaked on lag 14 days; RR was higher in girls than in boys and in children aged 1 to 2 years than in other age groups. However, the effects of low temperature (-5.3°C, 2.0°C, and 12.8°C) were not significant for both gender-specific and age-specific patients.High temperature may increase the risk of HFMD, and boys and children aged 3 to 5 years were at higher risks on lag 0 day; however, the cumulative risks in girls and children aged 1 to 2 years increased with the increasing number of lag days.
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Affiliation(s)
- Jinyu Wang
- School of Basic Medical Science, Lanzhou University
| | - Sheng Li
- The First People's Hospital of Lanzhou City, Lanzhou, PR China
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13
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Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17218017. [PMID: 33143315 PMCID: PMC7663009 DOI: 10.3390/ijerph17218017] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 10/25/2020] [Accepted: 10/27/2020] [Indexed: 12/17/2022]
Abstract
(1) Background: Inconsistencies were observed in studies on the relationship between short-term exposure to meteorological factors and the risk of hand, foot, and mouth disease (HFMD). This systematic review and meta-analysis was aimed to assess the overall effects of meteorological factors on the incidence of HFMD to help clarify these inconsistencies and serve as a piece of evidence for policy makers to determine relevant risk factors. (2) Methods: Articles published as of 24 October 2020, were searched in the four databases, namely, PubMed, Web of Science, Embase, and MEDLINE. We applied a meta-analysis to assess the impact of ambient temperature, relative humidity, rainfall, wind speed, and sunshine duration on the incidence of HFMD. We conducted subgroup analyses by exposure metrics, exposure time resolution, regional climate, national income level, gender, and age as a way to seek the source of heterogeneity. (3) Results: Screening by the given inclusion and exclusion criteria, a total of 28 studies were included in the analysis. We observed that the incidence of HFMD based on the single-day lag model is significantly associated with ambient temperature, relative humidity, rainfall, and wind speed. In the cumulative lag model, ambient temperature and relative humidity significantly increased the incidence of HFMD as well. Subgroup analysis showed that extremely high temperature and relative humidity significantly increased the risk of HFMD. Temperate regions, high-income countries, and children under five years old are major risk factors for HFMD. (4) Conclusions: Our results suggest that various meteorological factors can increase the incidence of HFMD. Therefore, the general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance.
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Ghanbari B. A fractional system of delay differential equation with nonsingular kernels in modeling hand-foot-mouth disease. ADVANCES IN DIFFERENCE EQUATIONS 2020; 2020:536. [PMID: 33014026 PMCID: PMC7523494 DOI: 10.1186/s13662-020-02993-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 09/22/2020] [Indexed: 06/11/2023]
Abstract
In this article, we examine a computational model to explore the prevalence of a viral infectious disease, namely hand-foot-mouth disease, which is more common in infants and children. The structure of this model consists of six sub-populations along with two delay parameters. Besides, by taking advantage of the Atangana-Baleanu fractional derivative, the ability of the model to justify different situations for the system has been improved. Discussions about the existence of the solution and its uniqueness are also included in the article. Subsequently, an effective numerical scheme has been employed to obtain several meaningful approximate solutions in various scenarios imposed on the problem. The sensitivity analysis of some existing parameters in the model has also been investigated through several numerical simulations. One of the advantages of the fractional derivative used in the model is the use of the concept of memory in maintaining the substantial properties of the understudied phenomena from the origin of time to the desired time. It seems that the tools used in this model are very powerful and can effectively simulate the expected theoretical conditions in the problem, and can also be recommended in modeling other computational models in infectious diseases.
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Affiliation(s)
- Behzad Ghanbari
- Department of Engineering Science, Kermanshah University of Technology, Kermanshah, Iran
- Department of Mathematics, Faculty of Engineering and Natural Sciences, Bahçeşehir University, 34349 Istanbul, Turkey
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15
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Hu B, Qiu W, Xu C, Wang J. Integration of a Kalman filter in the geographically weighted regression for modeling the transmission of hand, foot and mouth disease. BMC Public Health 2020; 20:479. [PMID: 32276607 PMCID: PMC7146977 DOI: 10.1186/s12889-020-08607-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 03/27/2020] [Indexed: 01/16/2023] Open
Abstract
Background Hand, foot and mouth disease (HFMD) is a common infectious disease whose mechanism of transmission continues to remain a puzzle for researchers. The measurement and prediction of the HFMD incidence can be combined to improve the estimation accuracy, and provide a novel perspective to explore the spatiotemporal patterns and determinant factors of an HFMD epidemic. Methods In this study, we collected weekly HFMD incidence reports for a total of 138 districts in Shandong province, China, from May 2008 to March 2009. A Kalman filter was integrated with geographically weighted regression (GWR) to estimate the HFMD incidence. Spatiotemporal variation characteristics were explored and potential risk regions were identified, along with quantitatively evaluating the influence of meteorological and socioeconomic factors on the HFMD incidence. Results The results showed that the average error covariance of the estimated HFMD incidence by district was reduced from 0.3841 to 0.1846 compared to the measured incidence, indicating an overall improvement of over 50% in error reduction. Furthermore, three specific categories of potential risk regions of HFMD epidemics in Shandong were identified by the filter processing, with manifest filtering oscillations in the initial, local and long-term periods, respectively. Amongst meteorological and socioeconomic factors, the temperature and number of hospital beds per capita, respectively, were recognized as the dominant determinants that influence HFMD incidence variation. Conclusions The estimation accuracy of the HFMD incidence can be significantly improved by integrating a Kalman filter with GWR and the integration is effective for exploring spatiotemporal patterns and determinants of an HFMD epidemic. Our findings could help establish more accurate HFMD prevention and control strategies in Shandong. The present study demonstrates a novel approach to exploring spatiotemporal patterns and determinant factors of HFMD epidemics, and it can be easily extended to other regions and other infectious diseases similar to HFMD.
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Affiliation(s)
- Bisong Hu
- School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, 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
| | - Wenqing Qiu
- School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, 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
| | - 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.
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16
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Effects of temperature fluctuations on spatial-temporal transmission of hand, foot, and mouth disease. Sci Rep 2020; 10:2541. [PMID: 32054890 PMCID: PMC7018740 DOI: 10.1038/s41598-020-59265-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 01/27/2020] [Indexed: 11/08/2022] Open
Abstract
Hand, foot, and mouth disease (HFMD), predominantly occurs among infants and children. Previous studies have shown that suitable, stable temperatures favor HFMD virus reproduction; however, temperature fluctuations also affect virus transmission, and there are, so far, no studies concerning the association between such fluctuations and the incidence of HFMD. The objective of this study was to map the spatial-temporal distribution of HFMD incidence and quantify the long-term effects of temperature fluctuations on HFMD incidence in children. HFMD cases in children under five, from January 2009 to December 2013, in Beijing, Tianjin, and Hebei provinces of China, were used in this study. The GeoDetector and Bayesian space-time hierarchy models were employed to explore the spatial-temporal association between temperature fluctuations and HFMD incidence. The results indicate that HFMD incidence had significant spatial stratified heterogeneity (GeoDetector q-statistic = 0.83, p < 0.05), and that areas with higher risk mainly appeared in metropolises and their adjacent regions. HFMD transmission was negatively associated with temperature fluctuations. A 1 °C increase in the standard deviation of maximum and minimum temperatures was associated with decreases of 8.22% and 11.87% in the risk of HFMD incidence, respectively. The study suggests that large temperature fluctuations affect virus growth or multiplication, thereby inhibiting the activity of the virus and potentially even leading to its extinction, and consequently affecting the spatial-temporal distribution of HFMD. The findings can serve as a reference for the practical control of this disease and offer help in the rational allocation of medical resources.
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17
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A method for hand-foot-mouth disease prediction using GeoDetector and LSTM model in Guangxi, China. Sci Rep 2019; 9:17928. [PMID: 31784625 PMCID: PMC6884467 DOI: 10.1038/s41598-019-54495-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 11/14/2019] [Indexed: 12/14/2022] Open
Abstract
Hand-foot-mouth disease (HFMD) is a common infectious disease in children and is particularly severe in Guangxi, China. Meteorological conditions are known to play a pivotal role in the HFMD. Previous studies have reported numerous models to predict the incidence of HFMD. In this study, we proposed a new method for the HFMD prediction using GeoDetector and a Long Short-Term Memory neural network (LSTM). The daily meteorological factors and HFMD records in Guangxi during 2014–2015 were adopted. First, potential risk factors for the occurrence of HFMD were identified based on the GeoDetector. Then, region-specific prediction models were developed in 14 administrative regions of Guangxi, China using an optimized three-layer LSTM model. Prediction results (the R-square ranges from 0.39 to 0.71) showed that the model proposed in this study had a good performance in HFMD predictions. This model could provide support for the prevention and control of HFMD. Moreover, this model could also be extended to the time series prediction of other infectious diseases.
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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.
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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
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Li J, Zhang X, Wang L, Xu C, Xiao G, Wang R, Zheng F, Wang F. Spatial-temporal heterogeneity of hand, foot and mouth disease and impact of meteorological factors in arid/ semi-arid regions: a case study in Ningxia, China. BMC Public Health 2019; 19:1482. [PMID: 31703659 PMCID: PMC6839228 DOI: 10.1186/s12889-019-7758-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 10/02/2019] [Indexed: 01/08/2023] Open
Abstract
Background The incidence of hand, foot and mouth disease (HFMD) varies over space and time and this variability is related to climate and social-economic factors. Majority of studies on HFMD were carried out in humid regions while few have focused on the disease in arid/semi-arid regions, more research in such climates would potentially make the mechanism of HFMD transmission clearer under different climate conditions. Methods In this paper, we explore spatial-temporal distribution of HFMD in Ningxia province, which has an arid/semi-arid climate in northwest China. We first employed a Bayesian space-time hierarchy model (BSTHM) to assess the spatial-temporal heterogeneity of the HFMD cases and its relationship with meteorological factors in Ningxia from 2009 to 2013, then used a novel spatial statistical software package GeoDetector to test the spatial-temporal heterogeneity of HFMD risk. Results The results showed that the spatial relative risks in northern part of Ningxia were higher than those in the south. The highest temporal risk of HFMD incidence was in fall season, with a secondary peak in spring. Meteorological factors, such as average temperature, relative humidity, and wind speed played significant roles in the spatial-temporal distribution of HFMD risk. Conclusions The study provide valuable information on HFMD distribution in arid/semi-arid areas in northwest China and facilitate understanding of the concentration of HFMD.
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Affiliation(s)
- Jie Li
- Department of Resources and Environment, Ningxia University, Yinchuan, 750021, China.,Ningxia (China-Arab) Key Laboratory of Resource Assessment and Environmental Regulation in Arid Region, Ningxia University, Yinchuan, 750021, China
| | - Xiangxue Zhang
- 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, 11A, Datun Road, Beijing, 100101, 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, Kai Feng, 475001, China
| | - Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Beijing, 100101, China.
| | - Gexin Xiao
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China.
| | - Ran Wang
- Department of Resources and Environment, Ningxia University, Yinchuan, 750021, China
| | - Fang Zheng
- Department of Resources and Environment, Ningxia University, Yinchuan, 750021, China.,Ningxia (China-Arab) Key Laboratory of Resource Assessment and Environmental Regulation in Arid Region, Ningxia University, Yinchuan, 750021, China
| | - Fang Wang
- Department of Resources and Environment, Ningxia University, Yinchuan, 750021, China.,Ningxia (China-Arab) Key Laboratory of Resource Assessment and Environmental Regulation in Arid Region, Ningxia University, Yinchuan, 750021, China
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Merzel Šabović EK, Točkova O, Uršič T, Žgavec B, Dolenc-Voljč M. Atypical hand, foot, and mouth disease in an adult patient: a case report and literature review. ACTA DERMATOVENEROLOGICA ALPINA PANNONICA ET ADRIATICA 2019. [DOI: 10.15570/actaapa.2019.21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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21
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Spatiotemporal Distribution of Hand, Foot, and Mouth Disease in Guangdong Province, China and Potential Predictors, 2009⁻2012. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16071191. [PMID: 30987085 PMCID: PMC6480297 DOI: 10.3390/ijerph16071191] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 03/24/2019] [Accepted: 03/26/2019] [Indexed: 12/15/2022]
Abstract
Background: Hand, foot, and mouth disease (HFMD) is a common infectious disease among children. Guangdong Province is one of the most severely affected provinces in south China. This study aims to identify the spatiotemporal distribution characteristics and potential predictors of HFMD in Guangdong Province and provide a theoretical basis for the disease control and prevention. Methods: Case-based HFMD surveillance data from 2009 to 2012 was obtained from the China Center for Disease Control and Prevention (China CDC). The Bayesian spatiotemporal model was used to evaluate the spatiotemporal variations of HFMD and identify the potential association with meteorological and socioeconomic factors. Results: Spatially, areas with higher relative risk (RR) of HFMD tended to be clustered around the Pearl River Delta region (the mid-east of the province). Temporally, we observed that the risk of HFMD peaked from April to July and October to December each year and detected an upward trend between 2009 and 2012. There was positive nonlinear enhancement between spatial and temporal effects, and the distribution of relative risk in space was not fixed, which had an irregular fluctuating trend in each month. The risk of HFMD was significantly associated with monthly average relative humidity (RR: 1.015, 95% CI: 1.006–1.024), monthly average temperature (RR: 1.045, 95% CI: 1.021–1.069), and monthly average rainfall (RR: 1.004, 95% CI: 1.001–1.008), but not significantly associated with average GDP. Conclusions: The risk of HFMD in Guangdong showed significant spatiotemporal heterogeneity. There was spatiotemporal interaction in the relative risk of HFMD. Adding a spatiotemporal interaction term could well explain the change of spatial effect with time, thus increasing the goodness of fit of the model. Meteorological factors, such as monthly average relative humidity, monthly average temperature, and monthly average rainfall, might be the driving factors of HFMD.
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