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基于气候因素的印度加尔各答登革热发生的建模与预测。

Modeling and prediction of dengue occurrences in Kolkata, India, based on climate factors.

机构信息

Institute for Meteorology, Free University of Berlin, Berlin, Germany.

Department of Physics, Swami Vivekananda Institute of Science & Technology, Kolkata, India.

出版信息

Int J Biometeorol. 2020 Aug;64(8):1379-1391. doi: 10.1007/s00484-020-01918-9. Epub 2020 Apr 23.

Abstract

Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.

摘要

登革热是印度最严重的虫媒传染病之一,尤其是在加尔各答及其周边地区。自 2012 年以来,加尔各答的一些市民感染了登革热病毒,而且每年都在增加。早期研究表明,某些气象变量和气候变化在全球不同地区登革热感染的传播和加剧中起着重要作用。在这项研究中,我们的主要目标是确定导致加尔各答登革热发生的潜在驱动因素的相对贡献,并预测未来气候变化下的登革热发病率。该回归模型是基于统计学上显著的互相关系数值,使用最高温度、最低温度、相对湿度和降雨量等关键气象因素来开发的,以预测登革热病例。最后,将南亚区域协调区域气候降尺度试验(CORDEX)的气候变量输入到统计模型中,以预测不同气候情景(如代表性浓度路径 4.5 和 8.5)下登革热感染的发生情况。据估计,从 2020 年到 2100 年,9 月至 11 月的登革热病例将会增加,在 RCP8.5 下(每年 872 例)比 RCP4.5 下(每年 531 例)更多。本研究还进一步得出结论,从 12 月到 2 月,RCP8.5 导致更适合的温暖天气条件,这对登革热病原体的生存和繁殖至关重要,导致 RCP8.5 下的登革热病例比 RCP4.5 下多两倍以上。此外,获得的结果将有助于开发早期预警系统,并为登革热控制政策制定和公共卫生干预提供重要证据。

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