Characteristics and statistical analysis of university accidents in China from 2017 to 2021
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PROVIDER: S-EPMC10590799 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
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Project description:Background: Construction activities not only provide the necessary conditions for citizens to live, but also cause fatal accidents. Methods: This study aimed to reveal the characteristics of fatal accidents in the construction industry in China based on statistical data. From 2010 to 2019, there were 6005 fatal accidents in China's construction industry causing 7275 deaths. The important features of these fatal accidents, such as the type, time of occurrence, site location, severity, and geographical region of the accident, were carefully analyzed. Results: There were 258 major and severe construction accidents causing 1037 deaths, accounting for 4.3% and 14.25% of the total number of construction accidents and deaths in this period, respectively. As an important finding, more deaths occurred in August and on Mondays. The greatest number of construction accidents took place along openings and edges, accounting for 22.9% of all fatal accidents. Taking into account their economic development level and number of employees, Qinghai and Hainan experienced a higher mortality rate than Jiangsu. Falls from a high place were the dominant type of construction accident, accounting for 51.66% of all accidents. However, collapses were the primary type of major and severe construction accident, accounting for 60.09% of such accidents. The predicted number of construction deaths in 2020 is 887 according to the GM(1,1) model. Corresponding safety measures should be adopted to improve the working environment of the construction industry. Implications: The implications of these results with respect to the characteristics of construction accidents can be regarded as the foundation for accident prevention in practice.
| S-EPMC7926821 | biostudies-literature
Project description:The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.
| S-EPMC7312879 | biostudies-literature
Project description:Porcine reproductive and respiratory syndrome virus (PRRSV) remains a major threat to the swine industry in China and has caused enormous losses every year. To monitor the epidemiological and genetic characteristics of PRRSV in South China, 6,795 clinical samples from diseased pigs were collected between 2017 and 2021, and 1,279 (18.82%) of them were positive for PRRSV by RT-PCR detecting the ORF5 gene. Phylogenetic analysis based on 479 ORF5 sequences revealed that a large proportion of them were highly-pathogenic PRRSVs (409, 85.39%) and PRRSV NADC30-like strains (66, 13.78%). Furthermore, 93.15% of these highly-pathogenic strains were found to be MLV-derived. We next recovered 11 PRRSV isolates from the positive samples and generated the whole genome sequences of them. Bioinformatic analysis showed that seven isolates were MLV-derived. Besides, six isolates were found to be recombinant strains. These eleven isolates contained different types of amino acid mutations in their GP5 and Nsp2 proteins compared to those of the PRRSVs with genome sequences publicly available in GenBank. Taken together, our findings contribute to understanding the prevalent status of PRRSV in South China and provide useful information for PRRS control especially the use of PRRSV MLV vaccines.
| S-EPMC9024240 | biostudies-literature
Project description:BackgroundRespiratory infectious diseases (RIDs) remain a pressing public health concern, posing a significant threat to the well-being and lives of individuals. This study delves into the incidence of seven primary RIDs during the period 2017-2021, aiming to gain deeper insights into their epidemiological characteristics for the purpose of enhancing control and prevention strategies.MethodsData pertaining to seven notifiable RIDs, namely, seasonal influenza, pulmonary tuberculosis (PTB), mumps, scarlet fever, pertussis, rubella and measles, in the mainland of China between 2017 and 2021 were obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression software was utilized to analyze temporal trends, while SaTScan software with a Poisson probability model was used to assess seasonal and spatial patterns.ResultsA total of 11,963,886 cases of the seven RIDs were reported during 2017-2021, and yielding a five-year average incidence rate of 170.73 per 100,000 individuals. Among these RIDs, seasonal influenza exhibited the highest average incidence rate (94.14 per 100,000), followed by PTB (55.52 per 100,000), mumps (15.16 per 100,000), scarlet fever (4.02 per 100,000), pertussis (1.10 per 100,000), rubella (0.59 per 100,000), and measles (0.21 per 100,000). Males experienced higher incidence rates across all seven RIDs. PTB incidence was notably elevated among farmers and individuals aged over 65, whereas the other RIDs primarily affected children and students under 15 years of age. The incidences of PTB and measles exhibited a declining trend from 2017 to 2021 (APC = -7.53%, P = 0.009; APC = -40.87%, P = 0.02), while the other five RIDs peaked in 2019. Concerning seasonal and spatial distribution, the seven RIDs displayed distinct characteristics, with variations observed for the same RIDs across different regions. The proportion of laboratory-confirmed cases fluctuated among the seven RIDs from 2017 to 2021, with measles and rubella exhibiting higher proportions and mumps and scarlet fever showing lower proportions.ConclusionsThe incidence of PTB and measles demonstrated a decrease in the mainland of China between 2017 and 2021, while the remaining five RIDs reached a peak in 2019. Overall, RIDs continue to pose a significant public health challenge. Urgent action is required to bolster capacity-building efforts and enhance control and prevention strategies for RIDs, taking into account regional disparities and epidemiological nuances. With the rapid advancement of high-tech solutions, the development and effective implementation of a digital/intelligent RIDs control and prevention system are imperative to facilitate precise surveillance, early warnings, and swift responses.
| S-EPMC10642048 | biostudies-literature
Project description:ObjectiveCarbapenem-resistant Klebsiella pneumoniae (CRKP) is spreading worldwide, becoming a serious threat to public health. The present study aimed to analyze the molecular epidemiology and drug resistance mechanism of CRKP isolated from neonatal patients in Sichuan, Southwest China.MethodsCRKP isolates were collected from neonatal patients of West China Second University Hospital from June 2017 to June 2021. Antimicrobial susceptibility testing was performed using broth microdilution. Whole-genome sequencing of all isolates were performed to determine the antimicrobial resistance genes, sequence typing, phylogenetic relationships.ResultsIn total, 41 nonduplicate CRKP isolates were collected. All isolates were highly resistant to the cephalosporins and carbapenems, however, they were all susceptible to amikacin, tigecycline, ciprofloxacin, and colistin. Various resistance genes were detected, blaNDM-5 (n = 35, 85.4%) was the predominant carbapenemase genes. The most common replicon type was IncX3, which was harbored by 36 (87.8%) isolates, followed by IncFIB (n = 34, 82.9%), and IncFII (n = 32, 78.0%). The 41 CRKP isolates belonged to 8 sequence types (STs) and ST789 (n = 29, all had blaNDM-5) was the dominant sequence type.ConclusionThe study revealed that blaNDM was the most dominant carbapenemase resistance gene. ST789 CRKP strains carrying blaNDM-5 were a tremendous menace to neonates in this hospital. Therefore, effectively implement prevention and control measures need to be taken for the prevention and treatment of CRKP infection in the neonatal ward.
| S-EPMC10590067 | biostudies-literature
Project description:BackgroundIn the past decades, extremely serious road accidents with a death toll over ten in each have become a severe public health problem in China. This study investigates risk factors contributing to extremely serious road accidents, which will be crucial for accident prevention.MethodsCollecting data from The Road Accident Statistical Annual Report openly issued by China's Traffic Management Bureau of the Public Security Ministry for the time period 2004-2015, we used the monthly case number of extreme serious road accidents as the dependent variable. We then selected ten risk factors as primary independent variables: professional driver, driving under influence (alcohol or drug), fatigue, vehicle type, overload, brake problem, weather, road classification, terrain, and region. The method of negative binominal regression was implemented to investigate the association between these risk factors and extremely serious road accidents.ResultsA total of 346 extremely serious road accidents were included in our analysis. On a national scale, we found that professional driver [incidence rate ratio (IRR): 1.10, 95% CI: 1.02-1.19], fatigue (IRR: 1.15, 95% CI: 1.03-1.29), large vehicle type (IRR: 1.11, 95% CI: 1.03-1.21), overload (IRR: 1.09, 95% CI: 1.03-1.16), and terrain (IRR: 1.09, 95% CI: 1.01-1.18) were significantly associated with extremely serious road accidents. Besides, separate analyses on western and non-western region indicated that both regions had shared risk factors as well as distinct factors.ConclusionsOur study identifies professional driver, fatigue, large vehicle type, overload, and terrain as significant risk factors of extremely serious road accidents in China, and targeted and preventative measures could be taken based on our findings.
| S-EPMC6070265 | biostudies-literature
Project description:Porcine respiratory diseases complex (PRDC) is a highly serious threat to the pig industry. In the present study, we investigated and analyzed the etiology associated with PRDC and explored the role of viruses in respiratory bacterial infections. From 2017 to 2021, clinical samples were collected from 1,307 pigs with typical respiratory symptoms in 269 farms in China and screened for pathogens related to PRDC by PCR and bacterial isolation. The results indicated that PRRSV (41.16%, 95%CI: 38.49~43.83%), PCV2 (21.58%,95%CI: 19.35~23.81%), S. suis (63.50%, 95%CI: 60.89~66.11%), and G. parasuis (28.54%, 95%CI: 26.09~30.99%) were the most commonly detected pathogens in pigs with PRDC in China. The dominant epidemic serotypes (serogroups) of S. suis, G. parasuis, and P. multocida were serotype 2, serotype 1, and capsular serogroups D, respectively. Pigs of different ages exhibited different susceptibilities to these pathogens, e.g., PRRSV, PCV2, and G. parasuis had the highest detection rates in nursery pigs, whereas fattening pigs had the highest detection rates of P. multocida and A. pleuropneumoniae. Among the 1,307 pigs, the detection rates of S. suis, G. parasuis, P. multocida, and B. bronchiseptica were higher in virus-positive pigs, especially G. parasuis and P. multocida were significantly (p < 0.01) higher than in virus-negative pigs. In addition, a strong positive correlation was found between coinfection by PRRSV and G. parasuis (OR = 2.33, 95%CI: 1.12~2.14), PRRSV and P. multocida (OR = 1.55, 95%CI: 1.12~2.14), PCV2 and P. multocida (OR = 2.27, 95%CI: 1.33~3.87), PRRSV-PCV2 and S. suis (OR = 1.83, 95%CI: 1.29~2.60), PRRSV-PCV2 and G. parasuis (OR = 3.39, 95%CI: 2.42~4.74), and PRRSV-PCV2 and P. multocida (OR = 2.09, 95%CI: 1.46~3.00). In summary, PRRSV, PCV2, S. suis, and G. parasuis were the major pathogens in pigs with PRDC, and coinfections of two or more PRDC-related pathogens with strong positive correlations were common in China, such as PRRSV and G. parasuis, PRRSV and P. multocida, PCV2 and P. multocida, and also PRRSV-PCV2 and G. parasuis and PRRSV-PCV2 and P. multocida.
| S-EPMC9592729 | biostudies-literature
Project description:In recent years, the prevalence of pseudorabies virus (PRV) has caused huge economic losses to the Chinese pig industry. Meanwhile, PRV infection in humans also sounded the alarm about its cross-species transmission from pigs to humans. To study the regional PRV epidemic, serological and epidemiological investigations of PRV in pig populations from Yunnan Province during 2017-2021 were performed. The results showed that 31.37% (6324/20,158, 95% CI 30.73-32.01) of serum samples were positive for PRV glycoprotein E (gE)-specific antibodies via enzyme-linked immunosorbent assay (ELISA). The risk factors, including the breeding scale and development stage, were significantly associated with PRV seroprevalence among pigs in Yunnan Province. Of the 416 tissue samples collected from PRV-suspected pigs in Yunnan Province, 43 (10.33%, 95% CI 7.41-13.26) samples were positive for PRV-gE nucleic acid in which 15 novel PRV strains from these PRV-positive samples were isolated, whose gC and gE sequences were analyzed. Phylogenetic analysis showed that all 15 isolates obtained in this study belonged to the genotype II. Additionally, the gC gene of one isolate (YuN-YL-2017) was genetically closer to variant PRV strains compared with others, while the gE gene was in the same clade with other classical PRV strains, indicating that this isolate might be a recombinant strain generated from the classical and variant strains. The results revealed the severe PRV epidemic in Yunnan Province and indicated that PRV variants are the major genotypes threatening the pig industry development.
| S-EPMC9146497 | biostudies-literature
Project description:China contributed nearly one-fifth of the world maize production over the past few years. Mapping the distributions of maize cropland in China is crucial to ensure global food security. Nonetheless, 10 m maize cropland maps in China are still unavailable, restricting the promotion of sustainable agriculture. In this paper, we collect numerous samples to produce annual 10-m maize cropland maps in China from 2017 to 2021 with a machine learning based classification framework. To overcome the temporal variations of plants, the proposed framework takes Sentinel-2 sequence images as input and utilizes deep neural networks and random forest as classifiers to map maize in a zone-specific way. The generated maps have an overall accuracy (OA) spanning from 0.87 to 0.95 and the maize-cultivated areas estimated by the maps are highly consistent with the records in statistical yearbooks (R2 varying from 0.83 to 0.95). To the best of our knowledge, this is the first annual 10-m maize maps across China, which largely facilitates the sustainable agriculture development in China dominated by smallholder farmlands.
| S-EPMC10625519 | biostudies-literature
Project description:The objective of this work is to advance the understanding of helicopter accidents by examining and quantifying the association between helicopter-specific configurations (number of main rotor blades, number of engines, rotor diameter, and takeoff weight) and the likelihood of accidents. We leverage a dataset of 8,338 turboshaft helicopters in the U.S. civil fleet and 825 accidents from 2005 to 2015. We use the dataset to develop a logistic regression model using the method of purposeful selection, which we exploit for inferential purposes and highlight the novel insights it reveals. For example, one important question for the design and acquisition of helicopters is whether twin-engine turboshaft helicopters exhibit a smaller likelihood of accidents than their single-engine counterparts, all else being equal. The evidence-based result we derive indicates that the answer is contingent on other covariates, and that a tipping point exists in terms of the rotor diameter beyond which the likelihood of accidents of twin-engines is higher (worse) than that of their single-engine counterparts. Another important result derived here is the association between the number of main rotor blades and likelihood of accidents. We found that for single-engine turboshaft helicopters, the four-bladed ones are associated with the lowest likelihood of accidents. We also identified a clear coupling between the number of engines and the rotor diameter in terms of likelihood of accidents. In summary, we establish important relationships between the different helicopter configurations here considered and the likelihood of accident, but these are associations, not causal in nature. The causal pathway, if it exists, may be confounded or mediated by other variables not accounted for here. The results provided here lend themselves to a rich set of interpretive possibilities, and because of their significant safety implications they deserve careful attention from the rotorcraft community.
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