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Meteorological Factors for Dengue Fever Control and Prevention in South China

View Article: PubMed Central - PubMed

ABSTRACT

Dengue fever (DF) is endemic in Guangzhou and has been circulating for decades, causing significant economic loss. DF prevention mainly relies on mosquito control and change in lifestyle. However, alert fatigue may partially limit the success of these countermeasures. This study investigated the delayed effect of meteorological factors, as well as the relationships between five climatic variables and the risk for DF by boosted regression trees (BRT) over the period of 2005–2011, to determine the best timing and strategy for adapting such preventive measures. The most important meteorological factor was daily average temperature. We used BRT to investigate the lagged relationship between dengue clinical burden and climatic variables, with the 58 and 62 day lag models attaining the largest area under the curve. The climatic factors presented similar patterns between these two lag models, which can be used as references for DF prevention in the early stage. Our results facilitate the development of the Mosquito Breeding Risk Index for early warning systems. The availability of meteorological data and modeling methods enables the extension of the application to other vector-borne diseases endemic in tropical and subtropical countries.

No MeSH data available.


Related in: MedlinePlus

The partial dependency plots for five meteorological factors and the joint partial dependency plot for daily average temperature and daily average humidity. (A) The relationship between daily average temperature and the risk for DF epidemic; (B) The relationship between daily average relative humidity and the risk for DF epidemic; (C) The relationship between daily precipitation and the risk for DF epidemic; (D) The relationship between daily sunshine duration and the risk for DF epidemic; (E) The relationship between daily average wind speed and the risk for DF epidemic; (F) The interaction between daily average temperature and daily average relative humidity.
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ijerph-13-00867-f004: The partial dependency plots for five meteorological factors and the joint partial dependency plot for daily average temperature and daily average humidity. (A) The relationship between daily average temperature and the risk for DF epidemic; (B) The relationship between daily average relative humidity and the risk for DF epidemic; (C) The relationship between daily precipitation and the risk for DF epidemic; (D) The relationship between daily sunshine duration and the risk for DF epidemic; (E) The relationship between daily average wind speed and the risk for DF epidemic; (F) The interaction between daily average temperature and daily average relative humidity.

Mentions: Daily average temperature contributed most strongly to the risk for DF in Guangzhou. Two positive relationships with temperature were observed in the lag-58 and lag-62 models (Figure 4A). The risk for DF increased steeply as the daily average temperature increased from 13 °C to 28 °C. However, the risk values in the lag-62 model seem to be more sensitive to high temperature, that is, a noticeable difference for the lag-62 model having higher risk values can be observed when temperature ranged from 20 °C to 30 °C.


Meteorological Factors for Dengue Fever Control and Prevention in South China
The partial dependency plots for five meteorological factors and the joint partial dependency plot for daily average temperature and daily average humidity. (A) The relationship between daily average temperature and the risk for DF epidemic; (B) The relationship between daily average relative humidity and the risk for DF epidemic; (C) The relationship between daily precipitation and the risk for DF epidemic; (D) The relationship between daily sunshine duration and the risk for DF epidemic; (E) The relationship between daily average wind speed and the risk for DF epidemic; (F) The interaction between daily average temperature and daily average relative humidity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036700&req=5

ijerph-13-00867-f004: The partial dependency plots for five meteorological factors and the joint partial dependency plot for daily average temperature and daily average humidity. (A) The relationship between daily average temperature and the risk for DF epidemic; (B) The relationship between daily average relative humidity and the risk for DF epidemic; (C) The relationship between daily precipitation and the risk for DF epidemic; (D) The relationship between daily sunshine duration and the risk for DF epidemic; (E) The relationship between daily average wind speed and the risk for DF epidemic; (F) The interaction between daily average temperature and daily average relative humidity.
Mentions: Daily average temperature contributed most strongly to the risk for DF in Guangzhou. Two positive relationships with temperature were observed in the lag-58 and lag-62 models (Figure 4A). The risk for DF increased steeply as the daily average temperature increased from 13 °C to 28 °C. However, the risk values in the lag-62 model seem to be more sensitive to high temperature, that is, a noticeable difference for the lag-62 model having higher risk values can be observed when temperature ranged from 20 °C to 30 °C.

View Article: PubMed Central - PubMed

ABSTRACT

Dengue fever (DF) is endemic in Guangzhou and has been circulating for decades, causing significant economic loss. DF prevention mainly relies on mosquito control and change in lifestyle. However, alert fatigue may partially limit the success of these countermeasures. This study investigated the delayed effect of meteorological factors, as well as the relationships between five climatic variables and the risk for DF by boosted regression trees (BRT) over the period of 2005–2011, to determine the best timing and strategy for adapting such preventive measures. The most important meteorological factor was daily average temperature. We used BRT to investigate the lagged relationship between dengue clinical burden and climatic variables, with the 58 and 62 day lag models attaining the largest area under the curve. The climatic factors presented similar patterns between these two lag models, which can be used as references for DF prevention in the early stage. Our results facilitate the development of the Mosquito Breeding Risk Index for early warning systems. The availability of meteorological data and modeling methods enables the extension of the application to other vector-borne diseases endemic in tropical and subtropical countries.

No MeSH data available.


Related in: MedlinePlus