Environmental research · 2018
Association between floods and typhoid fever in Yongzhou, China: Effects and vulnerable groups.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Liu Zhidong, Lao Jiahui, Zhang Ying, Liu Yanyu, Zhang Jing, Wang Hui, Jiang Baofa
Аннотация
BACKGROUND: Little information about the effects of floods on typhoid fever is available in previous studies. This study aimed to examine the relationships between floods and typhoid fever and to identify the vulnerable groups in Yongzhou, China.
METHODS: Weekly typhoid fever data, flood data and meteorological data during the flood season (April to September) from 2005 to 2012 were collected for this study. A Poisson generalized linear model combined with a distributed lag non-linear model was conducted to quantify the lagged and cumulative effects of floods on typhoid fever, considering the confounding effects of long-term trend, seasonality, and meteorological variables. The model was also used to calculate risk ratios of floods for weekly typhoid fever cases among various subpopulations.
RESULTS: After adjusting for long-term trend, seasonality, and meteorological variables, floods were associated with an increased number of typhoid fever cases with a risk ratio of 1.46 (95% CI: 1.10-1.92) at 1-week lag and a cumulative risk ratio of 1.76 (95% CI: 1.21-2.57) at lag 0-1 weeks. Males, people aged 0-4 years old, people aged 15-64 years old, farmers, and children appeared to be more vulnerable than the others.
CONCLUSIONS: Our study indicates that floods could significantly increase the risks of typhoid fever with lag effects of 1 week in the study areas. Precautionary measures should be taken with a focus on the identified vulnerable groups in order to control the transmission of typhoid fever associated with floods.
METHODS: Weekly typhoid fever data, flood data and meteorological data during the flood season (April to September) from 2005 to 2012 were collected for this study. A Poisson generalized linear model combined with a distributed lag non-linear model was conducted to quantify the lagged and cumulative effects of floods on typhoid fever, considering the confounding effects of long-term trend, seasonality, and meteorological variables. The model was also used to calculate risk ratios of floods for weekly typhoid fever cases among various subpopulations.
RESULTS: After adjusting for long-term trend, seasonality, and meteorological variables, floods were associated with an increased number of typhoid fever cases with a risk ratio of 1.46 (95% CI: 1.10-1.92) at 1-week lag and a cumulative risk ratio of 1.76 (95% CI: 1.21-2.57) at lag 0-1 weeks. Males, people aged 0-4 years old, people aged 15-64 years old, farmers, and children appeared to be more vulnerable than the others.
CONCLUSIONS: Our study indicates that floods could significantly increase the risks of typhoid fever with lag effects of 1 week in the study areas. Precautionary measures should be taken with a focus on the identified vulnerable groups in order to control the transmission of typhoid fever associated with floods.