State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
Sci Total Environ. 2020 Apr 20;714:136702. doi: 10.1016/j.scitotenv.2020.136702. Epub 2020 Jan 15.
Dysentery is water-borne and food-borne infectious disease and its incidence is sensitive to climate change. Although the impact of climate change on dysentery is being studied in specific areas, a systematic review is lacking. We searched the worldwide literature using three sets of keywords and six databases. We identified and selected 98 studies during 1866-2019 and reviewed the relevant findings. Climate change, including long-term variations in factors, such as temperature, precipitation, and humidity, and short-term variations in extreme weather events, such as floods and drought, mostly had a harmful impact on dysentery incidence. However, some uncertainty over the exact effects of climate factors exists, specifically in the different indexes for the same climate factor, various determinant indexes for different dysentery burdens, and divergent effects for different population groups. These complicate the accurate quantification of such impacts. We generalized two types of methods: sensitivity analysis, used to detect the sensitivity of dysentery to climate change, including Pearson's and Spearman's correlations; and mathematical models, which quantify the impact of climate on dysentery, and include models that examine the associations (including negative binomial regression models) and quantify correlations (including single generalized additive models and mixed models). Projection studies mostly predict disease risks, and some predict disease incidence based on climate models under RCP 4.5. Since some geographic heterogeneity exists in the climate-dysentery relationship, modeling and projection of dysentery incidence on a national or global scale remain challenging. The reviewed results have implications for the present and future. Current research should be extended to select appropriate and robust climate-dysentery models, reasonable disease burden measure, and appropriate climate models and scenarios. We recommend future studies focus on qualitative investigation of the mechanism involved in the impact of climate on dysentery, and accurate projection of dysentery incidence, aided by advancing accuracy of extreme weather forecasting.
痢疾是一种水媒和食媒传染病,其发病率对气候变化敏感。虽然气候变化对痢疾的影响在特定地区正在研究中,但缺乏系统评价。我们使用三组关键词和六个数据库搜索了全球文献。我们在 1866 年至 2019 年期间确定并选择了 98 项研究,并审查了相关发现。气候变化,包括温度、降水和湿度等因素的长期变化以及洪水和干旱等极端天气事件的短期变化,大多对痢疾发病率产生了有害影响。然而,气候因素的确切影响存在一些不确定性,特别是在同一气候因素的不同指标、不同痢疾负担的不同决定因素指标以及不同人群组的不同影响方面。这使得准确量化此类影响变得复杂。我们概括了两种类型的方法:用于检测痢疾对气候变化的敏感性的敏感性分析,包括 Pearson 和 Spearman 相关性;以及量化气候对痢疾影响的数学模型,包括检查关联的模型(包括负二项式回归模型)和量化相关性的模型(包括单广义加性模型和混合模型)。预测研究主要预测疾病风险,一些研究根据 RCP4.5 下的气候模型预测疾病发病率。由于气候与痢疾之间存在一些地理异质性,因此在国家或全球范围内对痢疾发病率进行建模和预测仍然具有挑战性。综述结果对当前和未来具有影响。目前的研究应扩展到选择适当和稳健的气候-痢疾模型、合理的疾病负担衡量标准以及适当的气候模型和情景。我们建议未来的研究重点关注定性研究气候变化对痢疾影响的机制,并借助极端天气预报准确性的提高,准确预测痢疾发病率。