Journal of Shandong University (Health Sciences) ›› 2018, Vol. 56 ›› Issue (8): 37-42.doi: 10.6040/j.issn.1671-7554.0.2017.1200

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Lag effect and vulnerable areas of floods on bacillary dysentery in Hunan Province

LIU Zhidong1, LAO Jiahui1, LIU Yanyu1, ZHANG Jing1, JIANG Baofa1,2   

  1. 1. Department of Epidemiology, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
  • Published:2022-09-27

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Abstract: Objective To study the lag effect and vulnerable areas of floods on bacillary dysentery in Hunan Province. Methods The meteorological data and weekly data of bacillary dysentery in 2004-2011 were obtained. The two-stage model was conducted. Firstly, a distributed lag non-linear model was developed to assess the relationship between floods and bacillary dysentery. Secondly, a hierarchical linear model was used to find the vulnerable areas. Results A total of 53 439 cases of bacillary dysentery were notified over the study period. At the province level, the cumulative effect of floods on bacillary dysentery at lag 0-1 week was statistically significant(RR=1.19, 95%CI: 1.05-1.36), and the effect reached maximum at lag 1 week(RR=1.12, 95%CI: 1.05-1.20). Western Hunan(RR=1.66, 95%CI: 1.09-2.55)and regions with low level of economic development(RR=1.43, 95%CI: 1.02-2.02)were more vulnerable than other areas. Conclusion Floods have significantly increased the risk of bacillary dysentery in study area. The intervention measures should be last at least two weeks. Disaster relief work must be intensified especially in regions with low level of economic development to control a potential risk of bacillary dysentery after floods.

Key words: Hunan Province, Floods, Bacillary dysentery, Two-stage model, Vulnerable areas

CLC Number: 

  • R181.3
[1] Guo X, Huang J, Luo Y, et al. Projection of precipitation extremes for eight global warming targets by 17 CMIP5 models[J]. Natural Hazards, 2016, 84(3): 2299-2319.
[2] 董文杰. 中国气象灾害年鉴(2005)[M]. 北京: 气象出版社, 2005: 45-53.
[3] 董文杰. 中国气象灾害年鉴(2006)[M]. 北京: 气象出版社, 2006: 19-31.
[4] 董文杰. 中国气象灾害年鉴(2007)[M]. 北京: 气象出版社, 2007: 22-31.
[5] 肖子牛. 中国气象灾害年鉴(2008)[M]. 北京: 气象出版社, 2008: 18-30.
[6] 肖子牛. 中国气象灾害年鉴(2009)[M]. 北京: 气象出版社, 2009: 17-26.
[7] 宋连春. 中国气象灾害年鉴(2010)[M]. 北京: 气象出版社, 2010: 21-25.
[8] 宋连春. 中国气象灾害年鉴(2011)[M]. 北京: 气象出版社, 2011: 16-23.
[9] 宋连春. 中国气象灾害年鉴(2012)[M]. 北京: 气象出版社, 2012: 17-23.
[10] Alderman K, Turner LR, Tong S. Floods and human health: a systematic review[J]. Environ Int, 2012, 47: 37-47. doi: 10.1016/j.envint.2012.06.003.
[11] Ahern M, Kovats RS, Wilkinson P, et al. Global health impacts of floods: epidemiologic evidence[J]. Epidemiol Rev, 2005, 27(1): 36-46.
[12] Ni W, Ding G, Li Y, et al. Effects of the floods on dysentery in north central region of Henan Province, China from 2004 to 2009[J]. J Infect, 2014, 69(5): 430-439.
[13] Liu Z, Li J, Zhang Y, et al. Distributed lag effects and vulnerable groups of floods on bacillary dysentery in Huaihua, China[J]. Sci Rep, 2016, 6: 29456. doi: 10.1038/srep29456.
[14] Liu Z, Ding G, Zhang Y, et al. Analysis of risk and burden of dysentery associated with floods from 2004 to 2010 in Nanning, China[J]. Am J Trop Med Hyg, 2015, 93(5): 925-930.
[15] Liu Z, Zhang F, Zhang Y, et al. Association between floods and infectious diarrhea and their effect modifiers in Hunan province, China: a two-stage model[J]. Sci Total Environ, 2018, 626: 630-637. doi: 10.1016/j.scitotenv.2018.01.130.
[16] Bell ML, Mcdermott A, Zeger SL, et al. Ozone and short-term mortality in 95 US urban communities, 1987-2000[J]. JAMA, 2004, 292(19): 2372-2378.
[17] Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models[J]. Stat Med, 2010, 29(21): 2224-2234.
[18] Cheng J, Wu J, Xu Z, et al. Associations between extreme precipitation and childhood hand, foot and mouth disease in urban and rural areas in Hefei, China[J]. Sci Total Environ, 2014, 497-498: 484-490. doi: 10.1016/j.scitotenv.2014.08.006.
[19] Bhaskaran K, Gasparrini A, Hajat S, et al. Time series regression studies in environmental epidemiology[J]. Int J Epidemiol, 2013, 42(4): 1187-1195.
[20] Witte JS, Greenland S, Haile RW, et al. Hierarchical regression analysis applied to a study of multiple dietary exposures and breast cancer[J]. Epidemiology, 1994, 5(6): 612-621.
[21] Gasparrini A. Distributed lag linear and non-linear models in R: the package dlnm[J]. J Stat Softw, 2011, 43(8): 1-20.
[22] Ding G, Zhang Y, Gao L, et al. Quantitative analysis of burden of infectious diarrhea associated with floods in northwest of Anhui Province, China: a mixed method evaluation[J]. PLoS One, 2013, 8(6): e65112. doi: 10.1371/journal.pone.0065112.
[23] Hodge J, Chang HH, Boisson S, et al. Assessing the association between thermotolerant coliforms in drinking water and diarrhea: an analysis of individual-level data from multiple studies[J]. Environ Health Perspect, 2016, 124(10): 1560-1567.
[24] de Man H, van den Berg HH, Leenen EJ, et al. Quantitative assessment of infection risk from exposure to waterborne pathogens in urban floodwater[J]. Water Res, 2014, 48(1): 90-99.
[25] Khan FA, Ali J, Ullah R, et al. Bacteriological quality assessment of drinking water available at the flood affected areas of Peshawar[J]. Toxico Enviro Chem, 2013, 8(95): 1448-1454.
[26] Schwartz BS, Harris JB, Khan AI, et al. Diarrheal epidemics in Dhaka, Bangladesh, during three consecutive floods: 1988, 1998, and 2004[J]. Am J Trop Med Hyg, 2006, 74(6): 1067-1073.
[27] Carroll B, Balogh R, Morbey H, et al. Health and social impacts of a flood disaster: responding to needs and implications for practice[J]. Disasters, 2010, 34(4): 1045-1063.
[1] JIANG Baofa, DING Guoyong, LIU Xuena. Research progress on the relationship between floods and human health [J]. Journal of Shandong University (Health Sciences), 2018, 56(8): 21-28.
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