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刘雨晨, 李伟彬, 刘立, 石林, 曾颖超, 黄绮娴, 黄存瑞, 杨廉平. 暴雨洪涝对细菌性痢疾发病影响研究进展[J]. 中国公共卫生, 2023, 39(1): 127-131. DOI: 10.11847/zgggws1138144
引用本文: 刘雨晨, 李伟彬, 刘立, 石林, 曾颖超, 黄绮娴, 黄存瑞, 杨廉平. 暴雨洪涝对细菌性痢疾发病影响研究进展[J]. 中国公共卫生, 2023, 39(1): 127-131. DOI: 10.11847/zgggws1138144
LIU Yu-chen, LI Wei-bin, LIU Li, . Progress in researches on effects of heavy rainfall and flood on bacillary dysentery incidence[J]. Chinese Journal of Public Health, 2023, 39(1): 127-131. DOI: 10.11847/zgggws1138144
Citation: LIU Yu-chen, LI Wei-bin, LIU Li, . Progress in researches on effects of heavy rainfall and flood on bacillary dysentery incidence[J]. Chinese Journal of Public Health, 2023, 39(1): 127-131. DOI: 10.11847/zgggws1138144

暴雨洪涝对细菌性痢疾发病影响研究进展

Progress in researches on effects of heavy rainfall and flood on bacillary dysentery incidence

  • 摘要: 气候变化背景下暴雨洪涝频发,对东南亚季风区域的发展中国家影响相对较大,可能会改变细菌性痢疾的发病规律或地区差异。本综述梳理了暴雨洪涝与细菌性痢疾发病的相关研究进展,包括流行病学关联分析、影响机制路径探究、环境 – 社会因素归纳和主要研究模型汇总等。较多研究表明暴雨洪涝会显著增加人群细菌性痢疾的发病风险;相关环境 – 社会影响因素包括环境影响因素,如基础设施过载和地理景观格局等,以及社会影响因素,如经济发展水平、城乡差异和医务人员数量;不同地区、不同性别、年龄和职业类型人群的发病风险也存在差异。当前研究分析模型多为广义相加模型、分布滞后非线性模型和泊松回归模型。未来亟待开展关于暴雨洪涝导致细菌性疾病发病的环境 – 社会影响因素和机制路径的深入研究。

     

    Abstract: Under the background of climate change, frequent heavy rainfall and floods have a great influence on the developing countries in the monsoon region in Southeast Asia, which may change the incidence pattern or regional difference of bacillary dysentery. In the review, we summarize the progress in researches on associations of rainstorm and flood on bacillary dysentery, mechanism and path of the influence, related environmental-social factors, and main models in the studies. Many studies have shown that rainstorm and flooding significantly increase the risk of bacillary dysentery; a number of studies also have dealt with relevant environmental-social factors such as infrastructure overload, geographic landscape pattern, economic development, urban and rural difference, and medical staff allocation. The results of the studies indicated that the heavy rainfall and floods-induced risk of bacillary dysentery incidence varied among populations of different gender, age, occupation, and living regions. The analytical models adopted by the studies include generalized additive model, distributed lag nonlinear model, and Poisson regression model. Further studies are warrented to explore the mechanism path of the influece of heavy rainfall and floods on bacillary dysentery incidence.

     

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