scholarly journals Spatiotemporal distribution of human brucellosis in Inner Mongolia, China, in 2010–2015, and influencing factors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Danyan Liang ◽  
Dan Liu ◽  
Min Yang ◽  
Xuemei Wang ◽  
Yunpeng Li ◽  
...  
Keyword(s):  
High Risk ◽  
Inner Mongolia ◽  
Human Brucellosis ◽  
Brucella Species ◽  
Factors Affecting ◽  
Spatiotemporal Trends ◽  
Animal Populations ◽  
Hospital Beds ◽  
Risk Areas ◽  
Per Capita

AbstractHuman brucellosis is caused by Brucella species and remains a major burden in both human and domesticated animal populations, especially in Inner Mongolia, China. The aims of this study were to analyze the spatiotemporal trends in human brucellosis in Inner Mongolia during 2010 to 2015, to explore the factors affecting the incidence of brucellosis. The results showed that the annual incidence was 29.68–77.67 per 100,000, and peaked from March to June. The majority of human brucellosis was male farmers and herdsmen, aged 40–59 years. The high-risk areas were mainly Xilin Gol League and Hulunbeier City. The incidence of human brucellosis in Inner Mongolia decreased during 2010 to 2015, although the middle and eastern regions were still high-risk areas. The regions with larger number of sheep and cattle, lower GDP per capita, less number of hospital beds, higher wind speed, lower mean temperature more likely to become high-risk areas of human brucellosis.

scholarly journals Epidemiological features of human brucellosis in Tongliao City, Inner Mongolia province, China: a cross-sectional study over an 11-year period (2007–2017)

BMJ Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. e031206 ◽  
Author(s):  
Di Li ◽  
Lifei Li ◽  
Jingbo Zhai ◽  
Lingzhan Wang ◽  
Bin Zhang
Keyword(s):  
High Risk ◽  
Inner Mongolia ◽  
Cross Sectional Study ◽  
Human Brucellosis ◽  
Sectional Study ◽  
Cross Sectional ◽  
North West ◽  
The Past ◽  
The North ◽  
Risk Areas

ObjectivesTo describe the epidemiology of human brucellosis in the past decade and provide evidence of disease control in Tongliao city, which is one of the highest-risk areas of human brucellosis in Inner Mongolia province, China.DesignCross-sectional study.ParticipantsClinically and bacteriologically confirmed human brucellosis cases.Primary and secondary outcome measuresAn analysis of the reported cases of human brucellosis during 2007–2017 was carried out to describe the age, sex and occupational distributions of the cases. The time series analysis model and the geographical information system were explored to describe the seasonality and spatiotemporal distribution, respectively, at the county level.ResultsA total of 13 938 cases of human brucellosis was collected in Tongliao from 2007 to 2017; the majority was aged 25 years to 59 years (85.4%) and the male-to-female ratio was 2.64:1; most of them were agriculturalists (81.9%) and pastoralists (12.4%). The incidence rates increased dramatically from 9.22/100 000 in 2007 to 69.16/100 000 in 2011 with an annual increase of 14.99%. They decreased during 2012–2016 (annual decrease of 8.37%) and rose again in 2017 (44.32/100 000). The disease peaked during March–July, with a clear periodicity and trend of monthly anterior displacement since 2012. Jarud Banner, the region located in the north-west of Tongliao, had the highest accumulated incidence rate (130.1/100 000) compared with other counties. The high-risk regions were spread from the north-west to the south and east of Tongliao during the past decade.ConclusionsThe prevalence of human brucellosis in Tongliao was aggravated during the past decade and peaked during March–July. High-risk areas were mainly concentrated in the counties with extensive prairies and livestock.

scholarly journals An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Assessment Model ◽  
Risk Assessments ◽  
Risk Assessment Model ◽  
Risk Area ◽  
The North ◽  
Coastal Cities ◽  
Risk Areas ◽  
The City

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

Esophageal cancer in high-risk areas of China: research progress and challenges

2017 ◽  
Vol 27 (3) ◽  
pp. 215-221 ◽  
Author(s):  
Yingsong Lin ◽  
Yukari Totsuka ◽  
Baoen Shan ◽  
Chaochen Wang ◽  
Wenqiang Wei ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
High Risk ◽  
Research Progress ◽  
Risk Areas

Small-Area Analysis: Targeting High-Risk Areas for Adolescent Pregnancy Prevention Programs

1998 ◽  
Vol 30 (4) ◽  
pp. 173 ◽  
Author(s):  
Jeffrey B. Gould ◽  
Beate Herrchen ◽  
Tanya Pham ◽  
Stephan Bera ◽  
Claire Brindis
Keyword(s):  
High Risk ◽  
Adolescent Pregnancy ◽  
Small Area ◽  
Prevention Programs ◽  
Pregnancy Prevention ◽  
Small Area Analysis ◽  
Adolescent Pregnancy Prevention ◽  
Risk Areas

scholarly journals Identifying high-risk areas for sporadic measles outbreaks: lessons from South Africa

2013 ◽  
Vol 91 (3) ◽  
pp. 174-183 ◽  
Author(s):  
Benn Sartorius ◽  
C Cohen ◽  
T Chirwa ◽  
G Ntshoe ◽  
A Puren ◽  
...  
Keyword(s):  
South Africa ◽  
High Risk ◽  
Risk Areas ◽  
Measles Outbreaks

Factors affecting pediatric residents' intentions to screen for high risk behaviors

1995 ◽  
Vol 17 (2) ◽  
pp. 106-112 ◽  
Author(s):  
Amy B. Middleman ◽  
Helen J. Binns ◽  
Robert H. Durant
Keyword(s):  
High Risk ◽  
Risk Behaviors ◽  
High Risk Behaviors ◽  
Pediatric Residents ◽  
Factors Affecting

Political Finance and Participation in Congressional Elections

1976 ◽  
Vol 425 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Paul A. Dawson ◽  
James E. Zinser
Keyword(s):  
Income Inequality ◽  
Political Parties ◽  
Capita Income ◽  
Congressional Elections ◽  
Campaign Contributions ◽  
Factors Affecting ◽  
Political Finance ◽  
Per Capita ◽  
Registered Voters ◽  
Campaign Expenditures

Citizens participate in the electoral process both to enjoy intrinsic benefits and in the hope of future bene fits. Factors affecting the strength of these consumption and investment motives therefore will affect registration and turnout rates, levels of campaign contributions, and electoral margins. To some extent, the strength of these motives is fixed by relatively static factors: levels of district per capita income, the degree of income inequality, the partisan division of registered voters. However, both motives also are affected by factors more apt to vary: for example, statutory arrangements, the activities of political parties, levels and types of campaign expenditures. In particular, statutory arrangements and the activities of parties which reduce costs can increase participation. Moreover, substan tial efforts to alter the partisan division of registered voters can increase campaign contributions. Also, campaign expenditures channel motivations in partisan directions, stim ulate partisan turnout, and affect electoral margins. Results reported here suggest the likelihood of bipartisan support for policies facilitating registration and voting, challenge assumptions about the effects of incumbency on campaign contributions, raise doubts about legislated ceilings on cam paign expenditures, and weaken the case for public financing of congressional elections.

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