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2015 年至 2018 年德里登革热环境预测因素的回顾性研究:广义线性模型。

A retrospective study of environmental predictors of dengue in Delhi from 2015 to 2018 using the generalized linear model.

机构信息

University School of Medicine and Paramedical Health Sciences, Guru Gobind Singh Indraprastha University, New Delhi, 110075, India.

ICMR-National Institute of Medical Statistics, Indian Council of Medical Research, Ansari Nagar, New Delhi, 110 029, India.

出版信息

Sci Rep. 2022 May 16;12(1):8109. doi: 10.1038/s41598-022-12164-x.

DOI:10.1038/s41598-022-12164-x
PMID:35577838
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9109956/
Abstract

Dengue fever is a mosquito-borne infection with a rising trend, expected to increase further with the rise in global temperature. The study aimed to use the environmental and dengue data 2015-2018 to examine the seasonal variation and establish a probabilistic model of environmental predictors of dengue using the generalized linear model (GLM). In Delhi, dengue cases started emerging in the monsoon season, peaked in the post-monsoon, and thereafter, declined in early winter. The annual trend of dengue cases declined, but the seasonal pattern remained alike (2015-18). The Spearman correlation coefficient of dengue was significantly high with the maximum and minimum temperature at 2 months lag, but it was negatively correlated with the difference of average minimum and maximum temperature at lag 1 and 2. The GLM estimated β coefficients of environmental predictors such as temperature difference, cumulative rainfall, relative humidity and maximum temperature were significant (p < 0.01) at different lag (0 to 2), and maximum temperature at lag 2 was having the highest effect (IRR 1.198). The increasing temperature of two previous months and cumulative rainfall are the best predictors of dengue incidence. The vector control should be implemented at least 2 months ahead of disease transmission (August-November).

摘要

登革热是一种由蚊子传播的感染病,呈上升趋势,随着全球气温的升高,预计这一趋势还将进一步加剧。本研究旨在利用 2015-2018 年的环境和登革热数据,通过广义线性模型(GLM)来研究季节性变化,并建立环境预测因子对登革热的概率模型。在德里,登革热病例在季风季节开始出现,在季风后期达到高峰,然后在初冬下降。登革热病例的年趋势呈下降趋势,但季节性模式保持不变(2015-18 年)。登革热与 2 个月滞后的最高和最低温度的斯皮尔曼相关系数显著较高,但与 1 个月和 2 个月滞后的平均最低和最高温度之间的差异呈负相关。GLM 估计的环境预测因子的 β 系数,如温差、累积降雨量、相对湿度和最大温度,在不同的滞后(0 到 2)时均有显著意义(p < 0.01),而滞后 2 的最大温度的影响最大(IRR 1.198)。前两个月的气温升高和累积降雨量是登革热发病率的最佳预测因子。应在疾病传播前至少提前 2 个月(8 月至 11 月)进行病媒控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e029/9110349/56c46008c061/41598_2022_12164_Fig6_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e029/9110349/1587e9871233/41598_2022_12164_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e029/9110349/3c8e8fabc740/41598_2022_12164_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e029/9110349/765c404b09f8/41598_2022_12164_Fig4_HTML.jpg
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