Lagged temperature effect with mosquito transmission potential explains dengue variability in southern Taiwan: Insights from a statistical analysis

被引:111
作者
Chen, Szu-Chieh [2 ,3 ]
Liao, Chung-Min [1 ]
Chio, Chia-Pin [1 ]
Chou, Hsiao-Han [2 ]
You, Shu-Han [2 ]
Cheng, Yi-Hsien [1 ]
机构
[1] Natl Taiwan Univ, Dept Bioenvironm Syst Engn, Taipei 10617, Taiwan
[2] Chung Shan Med Univ, Dept Publ Hlth, Taichung 40242, Taiwan
[3] Chung Shan Med Univ Hosp, Dept Family & Community Med, Taichung 40242, Taiwan
关键词
Aedes aegypti; Dengue; Temperature; Humidity; Rainfall; Mosquito; Poisson regression; AEDES-AEGYPTI; HEMORRHAGIC-FEVER; CLIMATE; VECTOR; WEATHER; VIRUS; EPIDEMIOLOGY; ENCEPHALITIS; POPULATION; RESURGENCE;
D O I
10.1016/j.scitotenv.2010.05.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The purpose of this study was to link meteorological factors and mosquito (Aedes aegypti) abundance to examine the potential effects of climate variations on patterns of dengue epidemiology in Taiwan during 2001-2008. Spearman's rank correlation tests with and without time-lag were performed to investigate the overall correlation between dengue incidence rates and meteorological variables (i.e., minimum, mean, and maximum temperatures, relative humidity (RH), and rainfall) and percentage Breteau index (BI) level >2 in Taipei and Kaohsiung of northern and southern Taiwan, respectively. A Poisson regression analysis was performed by using a generalized estimating equations (GEE) approach. The most parsimonious model was selected based on the quasi-likelihood based information criterion (QICu). Spearman's rank correlation tests revealed marginally positive trends in the weekly mean (rho= 0.28, p<0.0001), maximum (rho= 0.26, p<0.0001), and minimum (rho=-0.30, p <0.0001) temperatures in Taipei. However, in Kaohsiung, all negative trends were found in the weekly mean (rho=-0.32, p<0.0001), maximum (rho=-0.30, p<0.0001), and minimum (rho=-0.32, p<0.0001) temperatures. This study concluded that based on the GEE approach, rainfall, minimum temperature, and RH, all with 3-month lag, and 1-month lag of percentage BI level >2 are the significant predictors of dengue incidence in Kaohsiung (QICu = 277.77). This study suggested that warmer temperature with 3-month lag, elevated humidity with high mosquito density increased the transmission rate of human dengue fever infection in southern Taiwan. (c) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:4069 / 4075
页数:7
相关论文
共 44 条
[31]   Dengue reborn - Widespread resurgence of a resilient vector [J].
Phillips, Melissa Lee .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2008, 116 (09) :A382-A388
[32]  
Potter S., 2008, The Sting of Climate Change: Malaria and Dengue Fever in Maritime Southeast Asia and the Pacific Islands
[33]  
Promprou S, 2005, WALAILAK J SCI TECH, V2, P59
[34]  
Rohani A, 2009, SE ASIAN J TROP MED, V40, P942
[35]  
Su GLS, 2008, AMBIO, V37, P292, DOI 10.1579/0044-7447(2008)37[292:COCFAD]2.0.CO
[36]  
2
[37]   Environmental factors and incidence of dengue fever and dengue haemorrhagic fever in an urban area, Southern Thailand [J].
Thammapalo, S. ;
Chongsuvivatwong, V. ;
Geater, A. ;
Dueravee, M. .
EPIDEMIOLOGY AND INFECTION, 2008, 136 (01) :135-143
[38]   Effects of temperature and larval diet on development rates and survival of the dengue vector Aedes aegypti in north Queensland, Australia [J].
Tun-Lin, W ;
Burkot, TR ;
Kay, BH .
MEDICAL AND VETERINARY ENTOMOLOGY, 2000, 14 (01) :31-37
[39]  
*WHO, WORLD HLTH ORG DENG
[40]   Predicting Ross River virus epidemics from regional weather data [J].
Woodruff, RE ;
Guest, CS ;
Garner, MG ;
Becker, N ;
Lindesay, J ;
Carvan, T ;
Ebi, K .
EPIDEMIOLOGY, 2002, 13 (04) :384-393