scholarly journals Statistics of Dangerous Cargo Accidents during Highway Transportation

CONVERTER ◽  
2021 ◽  
pp. 53-63
Author(s):  
Xiao Li, Et al.
Keyword(s):  
Spatial Distribution ◽  
Prevention And Control ◽  
Present Situation ◽  
Transportation System ◽  
Common Type ◽  
Transportation Safety ◽  
Highway Transportation ◽  
Accident Consequence ◽  
Annual Scale ◽  
And Control

Research on present situation and trends of accidents takes an important role on prevention and control on dangerous cargo accidents during highway transportation. According to the current situation of highway transportation for dangerous cargo, the characteristics of highway transportation system for dangerous cargo are put forward. Statistical analysis of dangerous cargo in China from 2013 to 2019 related to characteristics and consequences are discussed in this study. The different time volatility, spatial distribution and accident consequence features are revealed. Results show that the dangerous cargo of highway transportation system presents a multiple spots, long lines, broad coverage, and high risk features. The annual scale of dangerous cargo accidents shows irregular ‘M’ distribution since 2013. December is the month with the most accidents. Wednesday is the day with the most accidents. Fifth period is the most accidents. Shandong is the province with the most accidents. Normal section is the section with the most accidents. The liquid is the type with the most accidents. Leakage is the most common type of accident. Countermeasures focusing on improving highway transportation safety for dangerous cargo accidents are recommended.

scholarly journals Prevalence and spatial distribution characteristics of human echinococcosis in China

2021 ◽  
Vol 15 (12) ◽  
pp. e0009996
Author(s):  
Li-Ying Wang ◽  
Min Qin ◽  
Ze-Hang Liu ◽  
Wei-Ping Wu ◽  
Ning Xiao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Autocorrelation ◽  
Prevention And Control ◽  
Disease Prevalence ◽  
Tibet Plateau ◽  
Spatial Clusters ◽  
Autonomous Region ◽  
And Control ◽  
Qinghai Tibet Plateau ◽  
Human Echinococcosis

Background Echinococcosis is a zoonotic parasitic disease caused by larval stages of cestodes belonging to the genus Echinococcus. The infection affects people’s health and safety as well as agropastoral sector. In China, human echinococcosis is a major public health burden, especially in western China. Echinococcosis affects people health as well as agricultural and pastoral economy. Therefore, it is important to understand the prevalence status and spatial distribution of human echinococcosis in order to advance our knowledge of basic information for prevention and control measures reinforcement. Methods Report data on echinococcosis were collected in 370 counties in China in 2018 and were used to assess prevalence and spatial distribution. SPSS 21.0 was used to obtain the prevalence rate for CE and AE. For statistical analyses and mapping, all data were processed using SPSS 21.0 and ArcGIS 10.4, respectively. Chi-square test and Exact probability method were used to assess spatial autocorrelation and spatial clustering. Results A total of 47,278 cases of echinococcosis were recorded in 2018 in 370 endemic counties in China. The prevalence rate of human echinococcosis was 10.57 per 10,000. Analysis of the disease prevalence showed obvious spatial positive autocorrelation in globle spatial autocorrelation with two aggregation modes in local spatial autocorrelation, namely high-high and low-high aggregation areas. The high-high gathering areas were mainly concentrated in northern Tibet, western Qinghai, and Ganzi in the Tibetan Autonomous Region and in Sichuan. The low-high clusters were concentrated in Gamba, Kangma and Yadong counties of Tibet. In addition, spatial scanning analysis revealed two spatial clusters. One type of spatial clusters included 71 counties in Tibet Autonomous Region, 22 counties in Qinghai, 11 counties in Sichuan, three counties in Xinjiang Uygur Autonomous Region, two counties in Yunnan, and one county in Gansu. In the second category, six types of spatial clusters were observed in the counties of Xinjiang Uygur Autonomous Region, and the Qinghai, Gansu, and Sichuan Provinces. Conclusion This study showed a serious prevalence of human echinococcosis with obvious spatial aggregation of the disease prevalence in China. The Qinghai-Tibet Plateau is the "hot spot" area of human echinococcosis in China. Findings from this study indicate that there is an urgent need of joint strategies to strengthen efforts for the prevention and control of echinococcosis in China, especially in the Qinghai-Tibet Plateau.

scholarly journals Characteristics and Temporal-Spatial Analysis of Overseas Imported Dengue Fever Cases in Outbreak Provinces of China, 2005-2019

2021 ◽  
Author(s):  
Xinchang Lun ◽  
Yiguan Wang ◽  
Chunchun Zhao ◽  
Haixia Wu ◽  
Caiying Zhu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Dengue Fever ◽  
Prevention And Control ◽  
Mainland China ◽  
Information Management System ◽  
Northern Region ◽  
Business Services ◽  
Imported Cases ◽  
And Control ◽  
Epidemiological Characteristics

Abstract (1) Background: Overseas imported dengue fever is an important factor in the local epidemic of dengue fever in mainland China. Therefore, in order to effectively prevent and control the local epidemic of dengue fever in mainland China, the epidemiological characteristics and temporal-spatial distribution of overseas imported dengue fever cases in provinces where dengue fever is endemic in mainland China are explored. (2) Methods: Through the infectious disease report information management system of the Chinese Disease Prevention and Control Information System, we sorted out overseas imported dengue fever cases in local outbreaks of dengue fever in mainland China from 2005 to 2019. Using Excel 2016 to sort out the data and draw the epidemic curve and population characteristic distribution of overseas imported cases in each province. Using ArcGIS 10.7 and SaTScan 9.5, we analyzed the temporal-spatial distribution of dengue fever in provinces where dengue fever is outbreak in mainland China. (3) Results: A total of 11407 imported cases, mainly from Southeast Asia, were recorded from 2005 to 2019 in 13 provinces, of which 62.08% were imported into Yunnan and Guangdong provinces. Among the imported cases, there were more males than females, mainly from 21-50 age group. 59.18% of the cases were farmers, businessmen, housework or unemployed. The hot spots were concentrated in parts of Yunnan and Guangdong provinces. Meanwhile,we found the clustered areas were expanding northward. (4) Conclusions: Focus on the publicity and education of dengue fever prevention knowledge among men, 21-50 years old, farmers, business services, housework or unemployed professionals. Further improve the awareness of the prevention and control of imported cases in border areas and economically developed cities. At the same time, the northern region cannot relax its vigilance.

scholarly journals Temporal-spatial distribution characteristics of leprosy: A new challenge for leprosy prevention and control in Zhejiang, China

2021 ◽  
Vol 15 (1) ◽  
pp. e0008956
Author(s):  
Limei Wu ◽  
Yunliang Shen ◽  
Qiang Yao ◽  
Xudong Sang ◽  
Lijuan Fei ◽  
...  
Keyword(s):  
Information System ◽  
Spatial Distribution ◽  
Prevention And Control ◽  
Zhejiang Province ◽  
Floating Population ◽  
Distribution Characteristics ◽  
Spatial Distribution Characteristics ◽  
Control And Prevention ◽  
And Control ◽  
Leprosy Control

Background After the elimination of leprosy in 1995, there were 10–30 newly detected leprosy cases every year in Zhejiang Province, and the epidemiological characteristics of the newly detected leprosy cases have changed. While most of the newly detected cases came from other provinces in China, not Zhejiang, it brought a new challenge for leprosy prevention and control in post- elimination era in Zhejiang, China. This study was aimed to understand the temporal-spatial distribution characteristics of newly detected leprosy cases, and provide the scientific rationales for the development of leprosy control strategy. Methods Data on the demographic of Zhejiang Province from 2011 to 2019 were obtained from the China Information System for Disease Control and Prevention, and the epidemiological data on leprosy cases newly detected in Zhejiang Province from 2011 to 2019 were obtained from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and temporal-spatial distributions were described. The geographic information system software—ArcGIS 10.4 was used to draw the statistical maps, and Geoda 1.14.0 was used for local spatial autocorrelation analysis (local Getis coefficient method). Ridley-Jopling classification was used to classify the clinical types into I, TT, BT, BB, BL or LL. Two-group classification system developed by the World Health Organization (WHO) was used and cases were classified into multibacillary (MB) type or paucibacillary (PB) type. Results A total of 167 leprosy cases were reported in Zhejiang Province during 2011–2019, including 107 cases in males and 60 in females. The mean age at diagnosis was 37.99±14.81 years, and 94.01% of the cases were detected through the examination at skin-clinics. The number of workers, MB cases, G2D cases were 81 (48.50%), 159 (94.01%), 24 (14.37%) respectively, and the rate of early detection increased from 45.16% in 2011 to 90.91% in 2019. Leprosy cases were reported in all the prefectures of Zhejiang except Zhoushan City. The cases in local population accounted for 23.35% (39 cases), and the cases in floating population (especially coming from high epidemic provinces in China) accounted for 76.65% (128 cases). The annual number of newly detected cases showed a decreasing trend, from 31 cases in 2011 to 11 in 2019. Time of the floating population living in Zhejiang Province ranged from several months to more than 10 years. The annual proportion of new cases with G2D declined from 22.58% in 2011 to 9.09% in 2019. The results of local indicators of autocorrelation (LISA) analysis showed that the high-high areas were mainly concentrated in the middle and northeast of Zhejiang Province, while the low-low areas were in the east and southwest. Conclusion A few scattered cases still can be seen in post-elimination era, and there was a spatial clustering of the newly detected leprosy cases in Zhejiang Province. Most of the cases in Zhejiang Province were from other high epidemic provinces in China, which brought a new challenge for leprosy control and prevention in post- elimination era in Zhejiang, and it is also necessary to strengthen the early detection and standard management of the leprosy cases in floating population in Zhejiang.

scholarly journals The state of the leprosy epidemic in Yunnan, China 2011–2020: A spatial and spatiotemporal analysis, highlighting areas for intervention

2021 ◽  
Vol 15 (10) ◽  
pp. e0009783
Author(s):  
Xiaohua Chen ◽  
Tie-Jun Shui
Keyword(s):  
Public Health ◽  
Information System ◽  
Spatial Distribution ◽  
Spatial Autocorrelation ◽  
Prevention And Control ◽  
Public Health Problem ◽  
Distribution Analysis ◽  
Important Public Health Problem ◽  
And Control ◽  
Epidemiological Characteristics

Background Despite public health efforts to reduce the leprosy burden in Yunnan, China, leprosy remains an important public health problem in some specific areas. We analyzed the epidemiological characteristics and spatial distribution of leprosy in Yunnan, China, and provide data to guide disease prevention and control efforts. Methodology/principal findings The surveillance data of newly detected leprosy cases in Yunnan, China, during 2011–2020 were extracted from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and spatial distribution analysis, spatial autocorrelation analysis, and spatiotemporal scanning were performed with ArcGIS 10.6.1, GeoDa 1.8.8, and SaTScan 9.4.3 software, respectively. A total of 1907 newly detected leprosy cases were reported in Yunnan, China, during 2011–2020. The new case detection rate (NCDR) decreased from 0.62 in 2011 to 0.25 in 2020, with an annual incidence of 0.41/100,000 population. The proportions of multibacillary (MB) cases, cases in female patients, cases causing grade 2 physical disability (G2D), and cases in pediatric patients were 67.07%, 33.93%, 17.99%, and 2.83%, respectively. The number of counties with an incidence above 1/100,000 population decreased from 30 in 2011 to 8 in 2020. The Moran’s I of leprosy in Yunnan, China, during 2011–2020 ranged from 0.076 to 0.260, indicating the presence of spatial clusters. Local spatial autocorrelation (LSA) analysis showed that high-high cluster areas (hot spots) were mainly distributed in the southeastern, northern, and northwestern regions. Spatiotemporal scanning showed three clusters with high NCDRs. The probably primary clusters, occurring during January 1, 2011–December 31, 2015, covered 11 counties in the southeastern region (RR = 5.046515, LRR = 271.749664, P = 0.000). Conclusion The number of leprosy cases in Yunnan decreased overall, although some high-NCDR regions remained. Geographic information system (GIS) analysis coupled with spatial analysis indicated regions with leprosy clusters. Continuous leprosy prevention and control strategies in Yunnan Province should be established, and interventions in high-risk regions should be prioritized and further strengthened.

scholarly journals Spatial Distribution and Population Estimation of Dogs in Thailand: Implications for Rabies Prevention and Control

2021 ◽  
Vol 8 ◽  
Author(s):  
Weerapong Thanapongtharm ◽  
Suwicha Kasemsuwan ◽  
Vilaiporn Wongphruksasoong ◽  
Khemmapat Boonyo ◽  
Tanu Pinyopummintr ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Prevention And Control ◽  
Population Management ◽  
Community Factors ◽  
Control Programs ◽  
Canine Rabies ◽  
Related Data ◽  
Random Forest Models ◽  
And Control ◽  
Rabies Prevention

Poor management of dog populations causes many problems in different countries, including rabies. To strategically design a dog population management, certain sets of data are required, such as the population size and spatial distribution of dogs. However, these data are rarely available or incomplete. Hence, this study aimed to describe the characteristics of dog populations in Thailand, explore their spatial distribution and relevant factors, and estimate the number of dogs in the whole country. First, four districts were selected as representatives of each region. Each district was partitioned into grids with a 300-m resolution. The selected grids were then surveyed, and the number of dogs and related data were collected. Random forest models with a two-part approach were used to quantify the association between the surveyed dog population and predictor variables. The spatial distribution of dog populations was then predicted. A total of 1,750 grids were surveyed (945 grids with dog presence and 805 grids with dog absence). Among the surveyed dogs, 86.6% (12,027/13,895) were owned. Of these, 51% were classified as independent, followed by confined (25%), semi-independent (21%), and unidentified dogs (3%). Seventy-two percent (1,348/1,868) of the ownerless dogs were feral, and the rest were community dogs. The spatial pattern of the dog populations was highly distributed in big cities such as Bangkok and its suburbs. In owned dogs, it was linked to household demographics, whereas it was related to community factors in ownerless dogs. The number of estimated dogs in the entire country was 12.8 million heads including 11.2 million owned dogs (21.7 heads/km2) and 1.6 million ownerless dogs (3.2 heads/km2). The methods developed here are extrapolatable to a larger area and use much less budget and manpower compared to the present practices. Our results are helpful for canine rabies prevention and control programs, such as dog population management and control and rabies vaccine allocation.

scholarly journals Analysis of Spatial Distribution Characteristics of Human Echinococcosis at the Township Level in Sichuan Province, China

2021 ◽  
Author(s):  
Wei He ◽  
Wen-jie Yu ◽  
Guang-jia Zhang ◽  
Sha Liao ◽  
Qi Wang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Prevention And Control ◽  
Control Strategies ◽  
Sichuan Province ◽  
Distribution Map ◽  
Trend Surface Analysis ◽  
Spatial Distribution Characteristics ◽  
And Control ◽  
Spatial Distribution Map ◽  
Human Echinococcosis

Abstract BackgroundEchinococcosis is a global zoonotic parasitic disease caused by the larvae of Echinococcus, which affects both humans and animals. In China, this disease is highly endemic in Sichuan Province. In this study, we investigated the prevalence and spatial distribution characteristics of human echinococcosis at the township level in Sichuan province, so as to provide a reference for the development of precise prevention and control strategies in the future.MethodsWe explored the prevalence of echinococcosis using the B-ultrasonography diagnostic method in Sichuan province between 2016 and 2019, where patients and transmission conditions had been identified in the past. All data were inputted using Epi-Info software, while SPSS software was used for statistical analysis. We then employed ArcGIS software to draw the spatial distribution map and perform trend surface analysis. Finally, Geoda software was used to analyze spatial autocorrelation and draw Lisa clustering map.ResultsA total of 2 542 135 people from 649 towns in 35 counties of Sichuan province were screened for echinococcosis, of which 11 743 echinococcosis patients were detected. The prevalence of echinococcosis in humans was 0.462%, among which the occurrence of cystic echinococcosis [CE] was 0.221%, while that of alveolar echinococcosis [AE] was 0.244%. We also observed that the predominance of echinococcosis in humans decreased gradually from west to east and from north to south based on the results of the spatial distribution map and trend surface analysis. The Global Moran's I index was 0.77 (Z = 32.07, P < 0.05), which indicated that the prevalence of echinococcosis in humans was spatially clustered, exhibiting a significant spatial positive correlation. Further, the findings of local spatial autocorrelation analysis revealed that the “high-high” concentration areas were primarily located in some townships in the northwest of Sichuan province. On the other hand, the “low-low” concentration areas were predominantly located in some townships in the southeast of Sichuan province. ConclusionOur findings demonstrated that the prevalence of echinococcosis in humans of Sichuan province is following a downward trend, implying that the current prevention and control work has achieved some substantial outcomes. However, the prevalence in humans at the township level is widely distributed and differs greatly, with a clear clustering in space. Therefore in the future, precise prevention and control strategies should be formulated for clusters, particularly strengthening the “high-high” clusters at the township level.

scholarly journals Prevalence and spatial distribution patterns of human echinococcosis at the township level in Sichuan Province, China

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Wei He ◽  
Li-Ying Wang ◽  
Wen-Jie Yu ◽  
Guang-Jia Zhang ◽  
Bo Zhong ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Autocorrelation ◽  
Prevention And Control ◽  
Control Strategies ◽  
Sichuan Province ◽  
Distribution Map ◽  
Distribution Features ◽  
And Control ◽  
Spatial Distribution Map ◽  
Human Echinococcosis

Abstract Background Echinococcosis is a global zoonotic parasitic disease caused by Echinococcus larvae. This disease is highly endemic in Sichuan Province, China. This study investigates the prevalence and spatial distribution characteristics of human echinococcosis at the township level in Sichuan Province, geared towards providing a future reference for the development of precise prevention and control strategies. Methods Human prevalence of echinococcosis was evaluated using the B-ultrasonography diagnostic method in Sichuan Province between 2016 and 2019. All data were collected, collated, and analyzed. A spatial distribution map was drawn to intuitively analyze the spatial distribution features. Eventually, the spatial autocorrelation was specified and local indicators of spatial association (LISA) clustering map was drawn to investigate the spatial aggregation of echinococcosis at the township level in Sichuan Province. Results The prevalence of echinococcosis in humans of Sichuan Province was 0.462%, among which the occurrence of cystic echinococcosis (CE) was 0.221%, while that of alveolar echinococcosis (AE) was 0.244%. Based on the results of the spatial distribution map, a predominance of echinococcosis in humans decreased gradually from west to east and from north to south. The Global Moran’s I index was 0.77 (Z = 32.07, P < 0.05), indicating that the prevalence of echinococcosis in humans was spatially clustered, exhibiting a significant spatial positive correlation. Further, the findings of local spatial autocorrelation analysis revealed that the “high–high” concentration areas were primarily located in some townships in the northwest of Sichuan Province. However, the “low–low” concentration areas were predominantly located in some townships in the southeast of Sichuan Province. Conclusions Our findings demonstrated that the prevalence of echinococcosis in humans of Sichuan Province follows a downward trend, suggesting that the current prevention and control work has achieved substantial outcomes. Nevertheless, the prevalence in humans at the township level is widely distributed and differs significantly, with a clear clustering in space. Therefore, precise prevention and control strategies should be formulated for clusters, specifically strengthening the “high–high” clusters at the township level. Graphic Abstract

scholarly journals The present situation and towards the prevention and control of neurocysticercosis on the tropical island, Bali, Indonesia

2015 ◽  
Vol 8 (1) ◽  
pp. 148 ◽  
Author(s):  
Toni Wandra ◽  
Kadek Swastika ◽  
Nyoman S Dharmawan ◽  
Ivan Purba ◽  
I Sudarmaja ◽  
...  
Keyword(s):  
Prevention And Control ◽  
Present Situation ◽  
Tropical Island ◽  
And Control
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