Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand
Open Access
- 29 December 2010
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 8 (1) , 51-74
- https://doi.org/10.3390/ijerph8010051
Abstract
In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.Keywords
This publication has 39 references indexed in Scilit:
- Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006BMC Public Health, 2009
- Use of Mapping and Spatial and Space-Time Modeling Approaches in Operational Control of Aedes aegypti and DenguePLoS Neglected Tropical Diseases, 2009
- Spatial analysis of malaria incidence at the village level in areas with unstable transmission in EthiopiaInternational Journal of Health Geographics, 2009
- Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, ThailandInternational Journal of Health Geographics, 2009
- Spatio-temporal cluster analysis of the incidence of Campylobacter cases and patients with general diarrhea in a Danish county, 1995–2004International Journal of Health Geographics, 2009
- Relating increasing hantavirus incidences to the changing climate: the mast connectionInternational Journal of Health Geographics, 2009
- Describing the geographic spread of dengue disease by traveling wavesPublished by Elsevier ,2008
- Spatial and demographic patterns of Cholera in Ashanti region - GhanaInternational Journal of Health Geographics, 2008
- Empirical Bayes estimation smoothing of relative risks in disease mappingJournal of Statistical Planning and Inference, 2003
- Local Indicators of Spatial Association—LISAGeographical Analysis, 1995