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Climate Variability and Dengue Hemorrhagic Fever in Hanoi, Viet Nam, During 2008 to 2015
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Dengue fever/dengue hemorrhagic fever (DF/DHF) has been an important public health challenge in Viet Nam and worldwide. This study was implemented in 2016-2017 using retrospective secondary data to explore associations between monthly DF/DHF cases and climate variables during 2008 to 2015. There were 48 175 DF/DHF cases reported, and the highest number of cases occurred in November. There were significant correlations between monthly DF/DHF cases with monthly mean of evaporation ( r = 0.236, P < .05), monthly relative humidity ( r = −0.358, P < .05), and monthly total hours of sunshine ( r = 0.389, P < .05). The results showed significant correlation in lag models but did not find direct correlations between monthly DF/DHF cases and monthly average rainfall and temperature. The study recommended that health staff in Hanoi should monitor DF/DHF cases at the beginning of epidemic period, starting from May, and apply timely prevention and intervention measures to avoid the spreading of the disease in the following months. A larger scale study for a longer period of time and adjusting for other potential influencing factors could better describe the correlations, modelling/projection, and developing an early warning system for the disease, which is important under the impacts of climate change and climate variability.
Title: Climate Variability and Dengue Hemorrhagic Fever in Hanoi, Viet Nam, During 2008 to 2015
Description:
Dengue fever/dengue hemorrhagic fever (DF/DHF) has been an important public health challenge in Viet Nam and worldwide.
This study was implemented in 2016-2017 using retrospective secondary data to explore associations between monthly DF/DHF cases and climate variables during 2008 to 2015.
There were 48 175 DF/DHF cases reported, and the highest number of cases occurred in November.
There were significant correlations between monthly DF/DHF cases with monthly mean of evaporation ( r = 0.
236, P < .
05), monthly relative humidity ( r = −0.
358, P < .
05), and monthly total hours of sunshine ( r = 0.
389, P < .
05).
The results showed significant correlation in lag models but did not find direct correlations between monthly DF/DHF cases and monthly average rainfall and temperature.
The study recommended that health staff in Hanoi should monitor DF/DHF cases at the beginning of epidemic period, starting from May, and apply timely prevention and intervention measures to avoid the spreading of the disease in the following months.
A larger scale study for a longer period of time and adjusting for other potential influencing factors could better describe the correlations, modelling/projection, and developing an early warning system for the disease, which is important under the impacts of climate change and climate variability.
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