Regional coordinated development of low-carbon sports industry in China.

This study develops a systematic modeling framework, comprising a prediction model, a super-SBM model, and a spatial autocorrelation analysis model, to explore the spatial-temporal evolution tendencies of development efficiency within China's 30 regions in the low-carbon sports industry from 2006 to 2025. This framework aims to provide theoretical insights for the formulation of more targeted policies. Based on the empirical findings, the main conclusions of this study are as follows: (1) The optimal buffer operator grey prediction model demonstrates the highest accuracy among the prediction models examined. (2) The development efficiency curves of the 30 regions exhibit a significant increasing trend from 2006 to 2021, with values generally peaking between 0.4 and 0.6. (3) Notably, the disparity in development efficiency between developed and less developed regions is expected to progressively widen. (4) The development efficiency of the low-carbon sports industry across the 30 regions typically displays high-high clustering and low-low clustering during China's four five-year plan periods. This underscores the importance and urgency of promoting regional coordinated development within the low-carbon sports industry.

Spatiotemporal analysis and seasonality of tuberculosis in Pudong New Area of Shanghai, China, 2014-2023.

BACKGROUND: Spatiotemporal analysis is a vital method that plays an indispensable role in monitoring epidemiological changes in diseases and identifying high-risk clusters. However, there is still a blank space in the spatial and temporal distribution of tuberculosis (TB) incidence rate in Pudong New Area, Shanghai. Consequently, it is crucial to comprehend the spatiotemporal distribution of TB in this district, this will guide the prevention and control of TB in the district. METHODS: Our research used Geographic Information System (GIS) visualization, spatial autocorrelation analysis, and space-time scan analysis to analyze the TB incidence reported in the Pudong New Area of Shanghai from 2014 to 2023, and described the spatiotemporal clustering and seasonal hot spot distribution of TB incidence. RESULTS: From 2014 to 2023, the incidence of TB in the Pudong New Area decreased, and the mortality was at a low level. The incidence of TB in different towns/streets has declined. The spatial autocorrelation analysis revealed that the incidence of TB was spatially clustered in 2014, 2016-2018, and 2022, with the highest clusters in 2014 and 2022. The high clustering area was mainly concentrated in the northeast. The space-time scan analysis indicated that the most likely cluster was located in 12 towns/streets, with a period of 2014-2018 and a radiation radius of 15.74 km. The heat map showed that there was a correlation between TB incidence and seasonal variations. CONCLUSIONS: From 2014 to 2023, the incidence of TB in the Pudong New Area of Shanghai declined, but there were spatiotemporal clusters and seasonal correlations in the incidence area. Local departments should formulate corresponding intervention measures, especially in high-clustering areas, to achieve accurate prevention and control of TB within the most effective time and scope.

Impacts of the Middle Route of China's South-to-North Water Diversion Project on the water network structure in the receiving basin.

The Middle Route of South-to-North Water Diversion Project (MRSNWD) is the main skeleton of China's National Water Network, its construction has changed the structure of the original water network, and analyzing the topological change of the water network in context with MRSNWD is significant for water network planning and management. In this study, the overall network characteristics of the water network in 2010 and 2020 were analyzed based on the small-world and scale-free characteristics of complex network theory. The topological changes of the water network from a node perspective were examined using three network centrality indexes: degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC), while assessing the important nodes of the water network and recognizing functional areas of cold-hot spots. The results show that the water network's centrality in the study area improved after the project construction, with the average degree of the water network increasing from 2.39 to 2.42 and the average path length decreasing from 111.81 to 97.08. The propagation efficiency and network stability also increased, with a rise in important node proportion from 9.8 to 14.4%. The nodes in the DC hotspot zone along the project route have increased by 1.5%, implying an increase in the connectivity of the water network, while MRSNWD optimizes its north-south hub propagation path. "Small-worldness" indicates that most nodes of a network can be accessed and connected over shorter paths. The water network has a significant "small-worldness" and has been enhanced by the MRSNWD's construction. Approximating the water network as a scale-free network can impact its security by identifying critical nodes. The results of this research can provide the necessary technical support and reference significance for China's National Water Network.

Spatial Analysis of Home and Community-Based Services and Number of Deaths Among Older Adults in Taiwan.

This study examined the geographical distribution of home- and community-based services (HCBS) resources in Taiwan's Long-Term Care 2.0 policy and explored its association with the number of deaths among older adults. The main outcome of the study was determination of the number of deaths among older adults in townships (N = 346) in 2021. The results showed that home-based HCBS had a significant positive association with mortality among older adults; moreover, community-based and complementary services, which are highly clustered within a township and among its neighbors, exert a significant protective effect on mortality among older adults. Stratified analyses showed a significantly lower mortality among older adults using adult foster care and transportation services, but a significantly higher mortality among older adults using home-based professional care and respite care services, after considering the sociodemographic characteristics of older adults, urbanization, and the number of long-term care resources in the spatial analysis.

[Spatial distribution of Oncomelania hupensis spread in Hubei Province from 2020 to 2022].

OBJECTIVE: To identify the spatial distribution pattern of Oncomelania hupensis spread in Hubei Province, so as to provide insights into precision O. hupensis snail control in the province. METHODS: Data pertaining to emerging and reemerging snails were collected from Hubei Province from 2020 to 2022 to build a spatial database of O. hupensis snail spread. The spatial clustering of O. hupensis snail spread was identified using global and local spatial autocorrelation analyses, and the hot spots of snail spread were identified using kernel density estimation. In addition, the correlation between environments with snail spread and the distance from the Yangtze River was evaluated using nearest-neighbor analysis and Spearman correlation analysis. RESULTS: O. hupensis snail spread mainly occurred along the Yangtze River and Jianghan Plain in Hubei Province from 2020 to 2022, with a total spread area of 4 320.63 hm2, including 1 230.77 hm2 emerging snail habitats and 3 089.87 hm2 reemerging snail habitats. Global spatial autocorrelation analysis showed spatial autocorrelation in the O. hupensis snail spread in Hubei Province in 2020 and 2021, appearing a spatial clustering pattern (Moran's I = 0.003 593 and 0.060 973, both P values < 0.05), and the mean density of spread snails showed spatial aggregation in Hubei Province in 2020 (Moran's I = 0.512 856, P < 0.05). Local spatial autocorrelation analysis showed that the high-high clustering areas of spread snails were mainly distributed in 50 settings of 10 counties (districts) in Hubei Province from 2020 to 2022, and the high-high clustering areas of the mean density of spread snails were predominantly found in 219 snail habitats in four counties of Jiangling, Honghu, Yangxin and Gong'an. Kernel density estimation showed that there were high-, secondary high- and medium-density hot spots in snail spread areas in Hubei Province from 2020 to 2022, which were distributed in Jingzhou District, Wuxue District, Honghu County and Huangzhou District, respectively. There were high- and medium-density hot spots in the mean density of spread snails, which were located in Jiangling County, Honghu County and Yangxin County, respectively. In addition, the snail spread areas negatively correlated with the distance from the Yangtze River (r = -0.108 9, P < 0.05). CONCLUSIONS: There was spatial clustering of O. hupensis snail spread in Hubei Province from 2020 to 2022. The monitoring and control of O. hupensis snails require to be reinforced in the clustering areas, notably in inner embankments to prevent reemerging schistosomiasis.

Global incidence and death estimates of chronic kidney disease due to hypertension from 1990 to 2019, an ecological analysis of the global burden of diseases 2019 study.

BACKGROUND: The intricate relationship between hypertension and chronic kidney disease (CKD) presents a global challenge for prevention of hypertension-related CKD. This study's objective is to analyze age, gender, regional disparities, and evolving trends in the disease burden of hypertension-related CKD. We aim to estimate changing spatial and temporal trends in incidence and mortality rates, considering the socio-demographic index (SDI), to inform health strategies effectively. METHOD: Age-standardized incidence rates (ASIR) and death rates (ASDR) were collected from the GBD 2019. Trend analysis was conducted by Joinpoint regression of ASRs from 1990 to 2019. Spatial autocorrelation analysis was performed to obtain spatial patterns. The association between SDI and burden of CKD due to hypertension was estimated using a Pearson correlation analysis. RESULTS: The global ASIR and ASDR due to hypertension-related CKD were 19.45 (95% CI, 17.85 to 21.09) and 5.88 (95% CI, 4.95 to 6.82) per 100 K population in 2019, representing increases of 17.89% and 13.29% compared to 1990, respectively. The elderly population and males were found the highest ASIR and ASDR. The high SDI region had the highest ASIRs, while low SDI regions experienced the highest ASDRs. Joinpoint regression found both global ASIR and ASDR showed increasing trends, with the highest increases observed in middle- and high-SDI regions, respectively. The SDI exhibited a positive association with ASIRs but displayed an inverse V-shaped correlation with the average annual percentage change (AAPC) of ASIRs. Spatial autocorrelation analysis revel significant positive spatial autocorrelation for the AAPC of ASDRs and ASIRs, from 1990 to 2019. CONCLUSIONS: Results met the objectives, and demonstrated a rising global burden of hypertension-related CKD. Factors such as aging, gender, and regional variations should be considered when designing control measures and developing healthcare systems to effectively address the burden of this complex condition.

Spatiotemporally Comparative Analysis of HIV, Pulmonary Tuberculosis, HIV-Pulmonary Tuberculosis Coinfection in Jiangsu Province, China.

Purpose: Pulmonary tuberculosis (PTB) is a severe chronic communicable disease that causes a heavy disease burden in China. Human Immunodeficiency Virus (HIV) and PTB coinfection dramatically increases the risk of death. This study analyzes the spatiotemporal dynamics of HIV, PTB and HIV-PTB coinfection in Jiangsu Province, China, and explores the impact of socioeconomic determinants. Patients and Methods: The data on all notified HIV, PTB and HIV-PTB coinfection cases were extracted from Jiangsu Provincial Center for Disease Control and Prevention. We applied the seasonal index to identify high-risk periods of the disease. Time trend, spatial autocorrelation and SaTScan were used to analyze temporal trends, hotspots and spatiotemporal clusters of diseases. The Bayesian space-time model was conducted to examine the socioeconomic determinants. Results: The case notification rate (CNR) of PTB decreased from 2011 to 2019 in Jiangsu Province, but the CNR of HIV and HIV-PTB coinfection had an upward trend. The seasonal index of PTB was the highest in March, and its hotspots were mainly distributed in the central and northern parts, such as Xuzhou, Suqian, Lianyungang and Taizhou. HIV had the highest seasonal index in July and HIV-PTB coinfection had the highest seasonal index in June, with their hotspots mainly distributed in southern Jiangsu, involving Nanjing, Suzhou, Wuxi and Changzhou. The Bayesian space-time interaction model showed that socioeconomic factor and population density were negatively correlated with the CNR of PTB, and positively associated with the CNR of HIV and HIV-PTB coinfection. Conclusion: The spatial heterogeneity and spatiotemporal clusters of PTB, HIV and HIV-PTB coinfection are exhibited obviously in Jiangsu. More comprehensive interventions should be applied to target TB in the northern part. While in southern Jiangsu, where the economic level is well-developed and the population density is high, we should strengthen the prevention and control of HIV and HIV-PTB coinfection.

Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models.

Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, and 2020. We assessed the features of land utilization conversion and forecasted land utilization under three development patterns in 2030 on the basis of the Patch-generating Land Use Simulation (PLUS) model. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to estimate changes in carbon storage trends under three development scenarios in 2000, 2010, 2020, and 2030 and the impact of socioeconomic and natural factors on carbon storage. The results of the study indicated that (1) carbon storage is intimately associated with land utilization practices. Carbon storage in Kunming in 2000, 2010, and 2020 was 1.146 × 108 t, 1.139 × 108 t, and 1.120 × 108 t, respectively. During the 20 years, forest land decreased by 142.28 km2, and the decrease in forest land area caused a loss of carbon storage. (2) Carbon storage in 2030 was predicted to be 1.102 × 108 t, 1.136 × 108 t, and 1.105 × 108 t, respectively, under the trend continuation scenario, eco-friendly scenario, and comprehensive development scenario, indicating that implementing ecological protection and cultivated land protection measures can facilitate regional ecosystem carbon storage restoration. (3) Impervious surfaces and vegetation have the greatest influence on carbon storage for the study area. A spatial global and local negative correlation was found between impervious surface coverage and ecosystem carbon storage. A spatial global and local positive correlation was found between NDVI and ecosystem carbon storage. Therefore, ecological and farmland protection policies need to be strengthened, the expansion of impervious surfaces should be strictly controlled, and vegetation coverage should be improved.

Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China.

Objective: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries. Methods: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation. Results: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning. Conclusion: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low-low and low-high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.

Spatiotemporal dynamics of CO2 emissions: a case study of the "New Yangtze River Delta" in China.

Due to vast territory and disparate regional energy varieties and efficiency in China, the spatial and temporal distribution of CO2 emissions in regions is quite different. But the formulation of previous carbon reduction policies was mainly based on national or provincial emissions data, lacking of refined scale data. This paper first collected Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) night light datasets from 1992 to 2013 and constructed a CO2 emissions inversion estimation model. Then, the spatiotemporal dynamics were analyzed by global and local spatial autocorrelation methods. Findings are as follows: (1) Total CO2 emissions in the Yangtze River Delta showed an overall growth trend from 396 million tons in 1992 to 1.825 billion tons in 2013, with an average annual growth rate of 17.18%. (2) The relatively slow growth accounted for the highest proportion in five growth types of CO2 emissions and were mainly concentrated in the underdeveloped southwestern regions of the Yangtze River Delta. The rapid-growth were agglomerated in the eastern coast areas. (3) Hot spots and sub-hot spots were concentrated in Shanghai, Suzhou, and Ningbo. Cold spots and sub-cold spots included southwest part of Anhui and Zhejiang. The findings provided a decision-making basis for mitigating CO2 emissions more reasonably.

Ecosystem services, landscape pattern, and landscape ecological risk zoning in China.

Ecosystem services represent a bridge between natural ecosystems and human well-being and are closely associated with landscape ecological risk (LER). Delimiting reasonable LER areas is important for ecosystem protection, and it is essential to link ecosystem services to LER zoning. However, only a few studies have achieved this, and the zoning accuracy of LER remains poorly understood. Therefore, in this study, we evaluated the ecosystem service value (ESV) and LER index using the equivalent value method and landscape pattern index via the remote sensing of land use data at the county level in China in 2000-2015. We applied bivariate spatial autocorrelation as well as the grey correlation analysis model to analyse the ESV-LER spatial relationships and developed a general framework to improve the accuracy of LER zoning. We found that the average ESV increased from $761.42 thousand/km2 in 2000 to $766.16 thousand/km2 in 2015, while the LER index continuously decreased in China. We also discerned a significant negative correlation between ESV and LER (p < 0.001), whereas approximately 750 counties in China exhibited high ESV and low LER indices during the study period. The final LER zoning revealed that the high-LER areas in China were mainly located in the plain areas, and the proportion of counties with high LER levels increased from 17.97% in 2000 to 26.56% in 2015. Overall, our results have important implications for ecological security, future landscape planning and design, and ecologically sustainable development in China.

Temporal and spatial characteristics of green total factor productivity in energy-intensive industry in China.

China's energy-intensive industry (EII) is characterized by high pollution, high energy consumption, and high emissions. It is essential to boost this sector's green total factor productivity (GTFP) in order to support the sustainable development of the China's economy and help to achieve the objective of carbon neutrality. This work measures the evolution of GTFP in EII and its subsectors at provincial and regional level from 2001 to 2019, identifies the causes of these changes, and finally analyzes the particular spatial aggregation effect of GTFP in EII. It is discovered that the GTFP of China's EII has significantly improved throughout the sample period and exhibits a spatial structure of "high in the coastal areas and low in the west and center." The main driver of GTFP growth for China's EII and its subsectors was technological advance. Smelting and pressing of ferrous metals (SPFM) and smelting and pressing of non-ferrous metals (SPNM) were the industries with the most significant technological progress. Remarkable spatial correlations existed among the GTFP of EII at provincial level. The GTFP values of EII in coastal regions were relatively high and tend to benefit the adjacent provinces but there was a polarization effect in the Middle Reaches of Yellow River (YR). Finally, policy implications are provided for the sustainable development of China's EII.

A county-level spatial epidemiological study of hair selenium and Keshan disease.

Background: No spatial analysis of hair selenium and Keshan disease (KD) on a nationwide county-level has been performed. Selenium deficiency is a recognized environmental risk factor for KD. Hair selenium is one of the recognized biomarkers of selenium nutrition. This study aimed to perform a geographically precise and visualized assessment of the achievement of KD prevention and control at the level of selenium nutrition in terms of etiology. Methods: A spatial ecological study was conducted. The hair selenium content of the residents was assayed using an atomic fluorescence spectrometer. The spatial analysis was performed using ArcGIS. Results: The median of the hair selenium levels of the 3,028 participants in the 1,174 counties was 0.38 mg/kg, and the content of inhabitants in KD endemic counties was significantly lower than that in KD non-endemic counties (0.34 vs. 0.39 mg/kg, z = -10.03, P < 0.0001). The proportion of Se-deficient and Se-marginal counties in KD endemic counties was significantly higher than that in KD non-endemic counties (59.4 vs. 29.0%, z = -7.45, P < 0.0001). The global autocorrelation analysis was not statistically significant (Moran's I = 0.0005, P = 0.68). Local autocorrelation analysis identified 174 low-low clusters of hair selenium levels, 83 (47.7%) of which are KD endemic counties located in KD endemic provinces of Henan, Gansu, Shaanxi, Inner Mongolia, Jilin, and Heilongjiang. The hair selenium featured a positive correlation with per capita GDP (r s = 0.20, P < 0.0001). Conclusion: The median of the hair selenium levels of inhabitants living in KD endemic counties was significantly lower than that in KD non-endemic counties. All the 83 KD endemic counties with low-low clusters of hair selenium levels should be prioritized in KD precision prevention and control. These findings are geographically precise and visualized evidence of the assessment of the effectiveness of KD prevention and control at the level of selenium nutrition in terms of etiology.

Temporal and spatial characterization of myopia in China.

Purpose: The aim of this study was to characterize the temporal and spatial distribution of myopia among students aged 7-18 years, by analyzing the aggregation area and providing the basis for the prevention and control of myopia in China. Methods: A database for the spatial analysis of myopia in China during 1995-2014 was established using ArcGIS10.0 software as a platform for data management and presentation. A spatial autocorrelation analysis of myopia was undertaken, and a temporal and spatial scan analysis was performed using SaTScan9.5 software. Results: Our data demonstrated that the prevalence of myopia in China in 1995, 2000, 2005, 2010, and 2014 was 35.9, 41.5, 48.7, 57.3, and 57.1%, respectively, thus indicating a gradual upward trend. The prevalence of myopia was analyzed in various provinces (municipalities and autonomous regions), and the highest was found in Jiangsu Province, with an average Moran's I index of 0.244295 in China (P ≤ 0.05). According to the local Moran's I autocorrelation analysis, there was a spatial aggregation of myopia prevalence among students in the entire country, with Shandong, Jiangsu, Anhui, and Shanghai being classified as high-high aggregation areas, while Hainan and Guangxi were classified as low-low aggregation areas. In addition, the Getis-Ord General G results of the global hotspot analysis showed a countrywide myopia prevalence index of 0.035020 and a Z score of 1.7959 (P = 0.07251). Because the myopia prevalence correlation difference was not statistically significant, there were no "positive hotspots" or "negative hotspots." The local hotspot analysis shows that Shandong and Jiangsu belong to high-value aggregation areas, while Hainan and Guizhou belong to low-value aggregation areas. Further analysis using time-space scanning showed 15 aggregation regions in five stages, with four aggregation regions having statistically significant differences (P ≤ 0.05). However, the aggregation range has changed over time. Overall, from 1995 to 2014, the aggregation areas for the myopia prevalence in Chinese students have shifted from the northwest, north, and northeast regions to the southeast regions. Conclusion: Our data demonstrate that, from 1995 to 2014, the prevalence of myopia increased in students aged 7-18 years in China. In addition, the prevalence of myopia is randomly distributed in various provinces (municipalities and autonomous regions) and exhibits spatial aggregation. Also, the gathering area is gradually shifting to the southeast, with the existence of high-risk areas. It is, therefore, necessary to focus on this area and undertake targeted prevention and control measures.

[Spatio-temporal distribution characteristics of Oncomelania hupensis in Anhui Province from 2011 to 2020].

OBJECTIVE: To analyze the spatial-temporal distribution characteristics of Oncomelania hupensis snails in Anhui Province from 2011 to 2020, to provide insights into precision control of O. hupensis snails in Anhui Province. METHODS: O. hupensis snail distribution data were collected in Anhui Province from 2011 to 2020 and descriptively analyzed, including actual area of snail habitats, area of emerging snail habitats and area of Schistosoma japonicum-infected snails. The actual area of snail habitats and area of emerging snail habitats were subjected to spatial autocorrelation analysis, hotspot analysis, standard deviation ellipse analysis and space-time scanning analysis, and the clusters of snail distribution and settings at high risk of snail spread were identified in Anhui Province from 2011 to 2020. RESULTS: The actual area of snail habitats gradually decreased in Anhui Province from 2011 to 2020. The actual area of snail habitats were 26 238.85 hm2 in Anhui Province in 2020, which were mainly distributed in marshland and lake regions. There was a large fluctuation in the area of emerging snail habitats in Anhui Province during the period from 2011 to 2020, with the largest area seen in 2016 (1 287.65 hm2), and 1.96 hm2 emerging infected snail habitats were detected in Guichi District, Chizhou City in 2020. Spatial autocorrelation and hotspot analyses showed spatial clusters in the distribution of actual areas of snail habitats in Anhui Province from 2011 to 2020 (Z = 3.00 to 3.43, all P values < 0.01), and the hotspots were mainly concentrated in the marshland and lake regions and distributed along the south side of the Yangtze River, while the cold spots were mainly concentrated in the mountainous regions of southern Anhui Province. There were no overall spatial clusters in the distribution of areas of emerging snail habitats (Z = -2.20 to 1.71, all P values > 0.05), and a scattered distribution was found in local regions. Standard deviation ellipse analysis showed relatively stable distributions of the actual areas of snail habitats in Anhui Province from 2011 to 2020, which was consistent with the flow direction of the Yangtze River, and the focus of the distribution of areas of emerging snail habitats shifted from the lower reaches to upper reaches of Anhui section of the Yangtze River. Space-time scanning analysis identified two high-value clusters in the distribution of actual areas of snail habitats in lower and middle reaches of Anhui section of the Yangtze River from 2011 to 2020, and two high-value clusters in the distribution of areas of emerging snail habitats were identified in mountainous and hilly regions. CONCLUSIONS: There were spatial clusters in the distribution of O. hupensis snails in Anhui Province from 2011 to 2020, which appeared a tendency of aggregation towards the south side and upper reaches of the Yangtze River; however, the spread of O. hupensis snails could not be neglected in mountainous and hilly regions. Monitoring of emerging snail habitats should be reinforced in mountainous and hilly regions and along the Yangtze River basin.

Do underserved and socially vulnerable communities observe more crashes? A spatial examination of social vulnerability and crash risks in Texas.

Understanding the relationship between social vulnerability and traffic crashes is a cornerstone for promoting social justice in transportation planning and policymaking. However, few studies have examined the disparities in traffic crashes by systemically considering the influence of social vulnerability via spatial analysis approaches. This study puts forward a new approach to assess the inequity in transportation safety by spatially examining the relationships between crash risks and the social vulnerability index (SVI) established by the Centers for Disease Control and Prevention (CDC). We performed spatial autocorrelation analyses to identify the clusters of high-risk and high-vulnerable census tracts in Texas. Meanwhile, we innovatively applied the Multiscale Geographically Weighted Regression model (MGWR) to assess the impacts of CDC SVI on crash risks spatially and statistically. The results demonstrate that the crash rate and the social vulnerability are significantly correlated in the highly urbanized regions as well as the southern border along the Rio Grande in Texas. The MGWR results indicate the minority status of census tracts is strongly correlated with overall crashes in north-central and northeastern Texas, and the socioeconomic status is tightly correlated with fatal crashes across Texas. The outcomes from this study have significant implications for transportation planning and policymaking.

Epidemiological and Clinical Characteristics of Influenza Outbreaks Among Children in Chongqing, China.

Influenza is a global serious public health threat. Seasonal influenza among children in Chongqing has been a heavy health burden. To date, few studies have examined the spatial and temporal characteristics of influenza. This research sheds new light on correlating them with influenza outbreaks with data of over 5 years (2014-2018). All cluster outbreaks among preschool and school-age children reported in Chongqing were collected through the Public Health Emergency Management Information System. The demographical, epidemiological, and clinical data of the cases were analyzed. From 2014 to 2018, a total of 111 preschool- and school-based influenza-like illness outbreaks involving 3,549 cases were identified. Several clinical symptoms that were analyzed in this study showed significant contrast between influenza A and B. Spatial autocorrelation analysis over the 5-year data detected Xiushan district being the most likely cluster. The exploration of the spatial distribution and clinical characteristics of influenza cluster of children in Chongqing could help the effective implementation of health policies. Future studies should be conducted to monitor the outbreaks of influenza among children.

Spatial and temporal patterns of prostate cancer burden and their association with Socio-Demographic Index in Asia, 1990-2019.

BACKGROUND: Prostate cancer is the second most frequently diagnosed cancer for males worldwide, but the spatial and temporal trends of prostate cancer burden remain unknown in Asia. This study aimed to investigate the changing spatial and temporal trends of incidence, prevalence, mortality, disability-adjusted life year (DALY), and mortality-to-incidence ratio (MIR) of prostate cancer, and their association with the Socio-Demographic Index (SDI) in 48 Asian countries from 1990 to 2019. METHODS: Data were extracted from the Global Health Data Exchange query tool, covering 48 Asian countries from 1990 to 2019. The average annual percent change was calculated to evaluate temporal trends. Spatial autocorrelation analysis was used to obtain spatial patterns, and the association between SDI and prostate cancer burden was estimated using a spatial panel model. RESULTS: In Asia, the age-standardized incidence and prevalence of prostate cancer increased in almost all countries, and its mortality and DALY also increased in over half of the countries. Significantly regional disparities were found in Asia, and the hot spots for incidence, prevalence, mortality, and DALY were all located in Western Asia, the hot spots of percent change also occurred in Western Asia for incidence and DALY. Furthermore, SDI had a positive association with mortality (coef = 2.51, 95% confidence interval [CI]: 2.13-2.90) and negative association with DALY (coef = -14.99, 95% CI: -20.37 to -9.60) and MIR (coef = -0.95, 95%CI: -0.99 to -0.92). CONCLUSIONS: Prostate cancer burden increased rapidly throughout Asia and substantial disparities had persisted between countries. Geographically targeted interventions are needed to reduce the prostate cancer burden throughout Asia and in specific countries.

Temporal and Spatial Characteristics of Cataract Surgery Rates in China.

OBJECTIVE: The aim of the current study was to explore the spatial and temporal distribution characteristics of registered cases of cataract surgery in China from 2013 to 2017. METHODS: A database for spatial analysis of cataract surgery in China in 2013-2017 was established using ArcGIS10.0 software as a platform for data management and presentation. Spatial autocorrelation analysis of cataract surgery was undertaken, and temporal and spatial scan analysis was done using SaTScan 9.5 software. RESULTS: From 2013 to 2017, annual cataract surgery rates (CSRs) in China were 1200, 1400, 1782, 2070, and 2205 per 1 million population, indicating a gradually increasing trend. Local Moran's I autocorrelation analysis showed that there was spatial clustering of CSR in China, with Anhui being a low-high clustering region. Findings of global hotspot analysis Getis-Ord General G showed that General G index of national CSR was <0.01, Z = 1.12, P = 0.26. Findings of staged spatial-temporal scan analysis indicated that 18 areas of aggregation were found in 2 stages. Observed differences in each clustering area were statistically significant (P < 0.05). CONCLUSION: CSRs in China showed increasing trend year by year and were randomly distributed, with spatial clustering, and Anhui was reported as a low-high clustering region. However, high-risk areas still persist, requiring focused attention and targeted prevention and control measures.

Spatiotemporal analysis and seasonality of tuberculosis in Algeria.

Background: This study aimed to describe the spatiotemporal distribution, to build a forecasting model, and to determine the seasonal pattern of tuberculosis (TB) in Algeria. Methods: The Box-Jenkins methodology was used to develop predictive models and GeoDa software was used to perform spatial autocorrelation. Results: Between 1982 and 2019, the notification rate per 100,000 population of smear-positive pulmonary TB (SPPTB) has dropped 62.2%, while that of extrapulmonary TB (EPTB) has risen 91.3%. For the last decade, the mean detection rate of PTB was 82.6%. At around, 2% of PTB cases were yearly reported in children under 15 years old, a peak in notification rate was observed in the elderly aged 65 and over, and the sex ratio was in favor of men. Between 52% and 59% of EPTB cases were lymphadenitis TB and between 15% and 23% were pleural TB. About two-third of EPTB cases were females and around 10% were children under the age of 15. The time series analysis showed that (1,1, 2) × (1, 1, 0)4 (respectively (0, 1, 2) × (1, 1, 0)4, (3, 1, 0) × (1, 1, 0)4) offered the best forecasting model to quarterly TB (respectively EPTB, SPPTB) surveillance data. The most hit part was the Tell followed by high plateaus which accounted for 96.6% of notifications in 2017. Significant hot spots were identified in the central part for EPTB notification rate and in the northwestern part for SPPTB. Conclusions: There is a need to reframe the set objectives in the state strategy to combat TB taking into account seasonality and spatial clustering to ensure improved TB management through targeted and effective interventions.