Progress in researches on effects of heavy rainfall and flood on bacillary dysentery incidence
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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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表 1 既往研究暴雨洪涝与细菌性痢疾关系的重点文献回顾
研究区域 研究时间 统计方法 主要结果 中国青岛[25] 2005 — 2011 泊松回归 暴雨洪涝增加了该研究区域细菌性痢疾发病风险，最佳滞后期为2周 中国大连[26] 2004 — 2010 广义相加模型（GAM） 暴雨洪涝增加了该研究区域细菌性痢疾发病风险，存在2周的滞后效应 中国南宁[21] 2004 — 2011 广义相加模型（GAM） 暴雨洪涝增加了该研究区域细菌性痢疾发病风险 中国新乡[16] 2004 — 2010 泊松回归 暴雨洪涝增加了该研究区域细菌性痢疾发病风险，且重涝对于痢疾发病的影响大于一般涝 中国怀化[29] 2005 — 2011 分布滞后非线性模型DLNM 洪水增加了该地细菌性痢疾的风险，存在3周影响，其中女性、农民和15～64岁人群患细菌性痢疾的风险较高 中国广西[23] 2004 — 2010 混合广义相加模型（MGAM） 与中度洪水相比，重度洪水导致细菌性痢疾发病率的风险较高；洪水持续时间与细菌性痢疾的发病率呈负相关 中国广西[24] 2006 — 2010 对数线性混合效应回归模型 在滞后2 d时，洪水导致细菌性痢疾发病风险显著增加，但伤寒和副伤寒无明显变化 中国百色[22] 2004 — 2012 混合广义相加模型（MGAM） 与中度洪水相比，重度洪水导致细菌性痢疾发病率风险较高；与长期洪水相比，短期洪水对细菌性痢疾发病率的影响更大 中国淄博[30] 2007 对称双向病例交叉研究 暴雨洪涝增加了该研究区域细菌性痢疾发病风险，女性和儿童是高危人群 中国河南[17] 2004 — 2009 广义相加模型（GAM） 回归分析显示，暴雨洪涝增加了该研究区域细菌性痢疾发病风险 中国辽宁[18] 2004 — 2010 Panel Poisson回归 洪水对细菌性痢疾发病率存在影响，但未发现滞后效应 中国郑州[31] 2005 — 2009 时间序列泊松回归 洪水对整个研究人群细菌性痢疾发病均存在影响，其中男性、女性、 ≤ 14岁人群发病风险上升 中国重庆[28] 2005 — 2016 分布滞后非线性模型DLNM 在一定的时间尺度内，洪水会增加重庆主城区细菌性痢疾的发病风险，重点人群包括男性、＜5岁、学生、工人和儿童 中国成都[27] 2009 — 2011 Poisson分布U 检验 洪水事件与细菌性痢疾的发生呈正相关，成都等5市有4个不同的最佳滞后期 中国安徽[19] 2015 Geodetector模型，生态系统服务
与权衡综合评价（INVEST）3种主要水文因素（quick flow, base flow and local recharge）与医务人员数量、农业用地占比、人口等之间的交互作用，共同影响细菌性痢疾发病 中国湖南[20] 2004 — 2010 分布滞后非线性模型DLNM 暴雨洪涝增加细菌性痢疾的发病风险，存在至少2周的滞后效应；经济发展水平较低的地区较为脆弱（RR = 1.43，95 % CI = 1.02～2.02） 秘鲁[13] 2011 — 2012 中断时间序列分析 暴雨洪涝对肠道菌群中志贺菌发病影响最大。与非洪水期相比，洪水后期细菌性痢疾发病风险几乎增加了2倍（RR = 2.86，95 % CI = 1.81～4.52） 韩国[11] 2001 — 2009 多变量 Poisson 回归模型 暴雨洪涝增加了该研究区域志贺菌病发病风险，志贺菌病的发生率灾后第2周达到峰值 孟加拉国[12] 1994 — 1998 奇异谱分析（SSA），Spearman
等级相关志贺菌病秋季暴发严重程度的年际变化与年度季风洪水的区域范围密切相关，季风洪水和季风后疾病暴发都与前一个冬天的厄尔尼诺（ENSO）活动显著相关 印度[9] 2010 — 2014 混合效应二项式回归模型 洪水时，随着降雨量增加，明渠附近地区的儿童细菌性肠道感染的概率增加 尼泊尔[10] 2003 — 2013 分布滞后非线性模型DLNM 洪水时，儿童细菌性腹泻与降雨量增加之间存在显著关联（P ＜ 0.05） 美国[14] 2015.7 — 2016.6 泊松回归 强降雨可能增加了俄勒冈州流浪者人群志贺菌病的发病风险 越南[15] 1999 — 2013 负二项式回归模型 暴雨同志贺菌病呈正相关关系，月降水量每增加100 mm，细菌性痢疾发病率增加4 % 
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