Temperature variability and spatial hotspots of dengue fever occurrence in Taiwan
Journal
Epidemiology
Journal Volume
17
Journal Issue
6
Pages
S485-S485
Date Issued
2006
Author(s)
Abstract
P-667 Abstract: Increasing global warming has resulted in elevated temperatures, rising numbers of extreme weather events, as well as predicted effects on the frequency and distribution of vector borne infectious diseases through changing ecological systems of vectors, changing transmission dynamics of vectors and pathogens, and changing the sociological patterns of human activities and adaptations. Dengue fever has been the most dominant vector borne infectious diseases in Taiwan, and a significant inter-annual variability of dengue fever incidence could be observed. Our study therefore conducted a spatial autocorrelation analysis to detect the changes in incidence across space and time and further evaluate the linkage between annual changes of temperature on the changes of spatial cluster of dengue fever. Computerized database containing daily registration of dengue fever cases in Taiwan for the period of 1998- 2004 were obtained from Taiwan CDC. Annual incidence rate of dengue fever in every township was then calculated. Geographic information system (ArcGIS 9.1) was applied to estimate and demonstrate the spatial patterns of dengue fever incidence. Spatial autocorrelation was examined by GeoDa0.9.5 and Moran's I value was used to identify spatial cluster of disease occurrence. Moran Significance Map was plotted to characterize the annual hotspot clusters of dengue fever. Significant Moran's I statistics could be observed in the year of 1998 (I= 0.1195), 2000 (I= 0.0157), 2001(I=0.0428), 2002 (I=0.4329), 2003 (I=0.1458), and 2004 (I=0.0656). Preliminary data distribution appeared to suggest that annual hotspot clusters with high incidence rate of dengue fever were all located in southern Taiwan. Those hotspots were mostly scattered along the paths of water channels and rivers. In addition, annual average temperature was also found to be associated with Moran's I value with marginal significance examined by Spearman's correlation test (r=0.679, p=0.094). Hotspot identification for dengue fever in our study is hoped to to assist in decision-making for preventive measures to prioritize areas of urgency, for vector control, environmental interventions, and personal protection promotion. Our analyses have suggested that increase of annual temperature seemed to be linked with spatial clusters of dengue fever, and areas along the rivers and water channels were often of greater urgency for taking prompt preventions. Further study should be conducted to analyze the relationship between weather variability and clusters of dengue fever distribution to evaluate the impacts of climate change on dengue fever distribution in Taiwan.
SDGs
Type
journal article