Impact of climate change on dysentery: Scientific evidences, uncertainty, modeling and projections

被引:19
作者
Wu, Xiaoxu [1 ]
Liu, Jianing [1 ]
Li, Chenlu [1 ]
Yin, Jie [1 ]
机构
[1] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
关键词
Climate change; Dysentery; Impact; Uncertainty; Modeling; Projection; TIME-SERIES ANALYSIS; BACILLARY DYSENTERY; AMBIENT-TEMPERATURE; HEALTH IMPACTS; METEOROLOGICAL FACTORS; INFECTIOUS DIARRHEA; EL-NINO; CHINA; DISEASE; WEATHER;
D O I
10.1016/j.scitotenv.2020.136702
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 longterm 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. (C) 2020 The Authors. Published by Elsevier B.V.
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页数:14
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