Sirisena Pdnn, Noordeen Faseeha, Kurukulasuriya Harithra, Romesh Thanuja Alar, Fernando LakKumar
Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka.
Department of Earth Sciences, Postgraduate Institute of Science, University of Peradeniya, Peradeniya, Sri Lanka.
PLoS One. 2017 Jan 9;12(1):e0166806. doi: 10.1371/journal.pone.0166806. eCollection 2017.
Dengue is one of the major hurdles to the public health in Sri Lanka, causing high morbidity and mortality. The present study focuses on the use of geographical information systems (GIS) to map and evaluate the spatial and temporal distribution of dengue in Sri Lanka from 2009 to 2014 and to elucidate the association of climatic factors with dengue incidence. Epidemiological, population and meteorological data were collected from the Epidemiology Unit, Department of Census and Statistics and the Department of Meteorology of Sri Lanka. Data were analyzed using SPSS (Version 20, 2011) and R studio (2012) and the maps were generated using Arc GIS 10.2. The dengue incidence showed a significant positive correlation with rainfall (p<0.0001). No positive correlation was observed between dengue incidence and temperature (p = 0.107) or humidity (p = 0.084). Rainfall prior to 2 and 5 months and a rise in the temperature prior to 9 months positively correlated with dengue incidence as based on the auto-correlation values. A rise in humidity prior to 1 month had a mild positive correlation with dengue incidence. However, a rise in humidity prior to 9 months had a significant negative correlation with dengue incidence based on the auto-correlation values. Remote sensing and GIS technologies give near real time utility of climatic data together with the past dengue incidence for the prediction of dengue outbreaks. In that regard, GIS will be applicable in outbreak predictions including prompt identification of locations with dengue incidence and forecasting future risks and thus direct control measures to minimize major outbreaks.
登革热是斯里兰卡公共卫生面临的主要障碍之一，会导致高发病率和高死亡率。本研究重点在于利用地理信息系统（GIS）绘制并评估2009年至2014年期间斯里兰卡登革热的时空分布，并阐明气候因素与登革热发病率之间的关联。从斯里兰卡人口普查与统计局的流行病学部门以及气象部门收集了流行病学、人口和气象数据。使用SPSS（2011版，版本20）和R studio（2012）对数据进行分析，并使用Arc GIS 10.2生成地图。登革热发病率与降雨量呈显著正相关（p<0.0001）。未观察到登革热发病率与温度（p = 0.107）或湿度（p = 0.084）之间存在正相关。根据自相关值，2个月和5个月前的降雨量以及9个月前温度的升高与登革热发病率呈正相关。1个月前湿度的升高与登革热发病率呈轻度正相关。然而，根据自相关值，9个月前湿度的升高与登革热发病率呈显著负相关。遥感和GIS技术可结合过去的登革热发病率近乎实时地利用气候数据来预测登革热疫情。在这方面，GIS将适用于疫情预测，包括迅速识别登革热发病地点、预测未来风险，从而指导控制措施以尽量减少重大疫情的发生。
