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8 results on '"Bao, Changjun"'

3. Clinical Characteristics and Risk Factors of an Outbreak with Scrub Typhus in Previously Unrecognized Areas, Jiangsu Province, China 2013

Author

Hu, Jianli, primary, Tan, Zhongming, additional, Ren, Dafei, additional, Zhang, Xiang, additional, He, Yilin, additional, Bao, Changjun, additional, Liu, Dapeng, additional, Yi, Qianhua, additional, Qian, Weijuan, additional, Yin, Jun, additional, Xu, Zhen, additional, Yu, Chunxia, additional, Wang, Shenjiao, additional, Wu, Bin, additional, Yang, Haiyu, additional, Yue, Ming, additional, Zhang, Yun, additional, Liu, Wendong, additional, Zhu, Yefei, additional, Zhou, Minghao, additional, and Tang, Fenyang, additional

Published
2015
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5. The Spatial Analysis on Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China Based on Geographic Information System

Author

Bao, Changjun, primary, Liu, Wanwan, additional, Zhu, Yefei, additional, Liu, Wendong, additional, Hu, Jianli, additional, Liang, Qi, additional, Cheng, Yuejia, additional, Wu, Ying, additional, Yu, Rongbin, additional, Zhou, Minghao, additional, Shen, Hongbing, additional, Chen, Feng, additional, Tang, Fenyang, additional, and Peng, Zhihang, additional

Published
2014
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8. Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China.

Author

Tang, Fenyang, Cheng, Yuejia, Bao, Changjun, Hu, Jianli, Liu, Wendong, Liang, Qi, Wu, Ying, Norris, Jessie, Peng, Zhihang, Yu, Rongbin, Shen, Hongbing, and Chen, Feng

Subjects
SHIGELLA, INFECTIOUS disease transmission, PATHOGENIC microorganisms, POPULATION biology, GRAM-negative bacteria, FOODBORNE diseases
Abstract

Objective: This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods: County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results: The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion: Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. [ABSTRACT FROM AUTHOR]

Published
2014
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