Lover Andrew A, Buchy Philippe, Rachline Anne, Moniboth Duch, Huy Rekol, Meng Chour Y, Leo Yee Sin, Yuvatha Kdan, Sophal Ung, Chantha Ngan, Y Bunthin, Duong Veasna, Goyet Sophie, Brett Jeremy L, Tarantola Arnaud, Cavailler Philippe
Infectious Diseases Programme, Saw Swee Hock School of Public Health, National University of Singapore, MD3, 16 Medical Drive, Singapore 117597, Singapore.
BMC Public Health. 2014 Jun 28;14:658. doi: 10.1186/1471-2458-14-658.
Dengue is a major contributor to morbidity in children aged twelve and below throughout Cambodia; the 2012 epidemic season was the most severe in the country since 2007, with more than 42,000 reported (suspect or confirmed) cases.
We report basic epidemiological characteristics in a series of 701 patients at the National Paediatric Hospital in Cambodia, recruited during a prospective clinical study (2011-2012). To more fully explore this cohort, we examined climatic factors using multivariate negative binomial models and spatial clustering of cases using spatial scan statistics to place the clinical study within a larger epidemiological framework.
We identify statistically significant spatial clusters at the urban village scale, and find that the key climatic predictors of increasing cases are weekly minimum temperature, median relative humidity, but find a negative association with rainfall maximum, all at lag times of 1-6 weeks, with significant effects extending to 10 weeks.
Our results identify clustering of infections at the neighbourhood scale, suggesting points for targeted interventions, and we find that the complex interactions of vectors and climatic conditions in this setting may be best captured by rising minimum temperature, and median (as opposed to mean) relative humidity, with complex and limited effects from rainfall. These results suggest that real-time cluster detection during epidemics should be considered in Cambodia, and that improvements in weather data reporting could benefit national control programs by allow greater prioritization of limited health resources to both vulnerable populations and time periods of greatest risk. Finally, these results add to the increasing body of knowledge suggesting complex interactions between climate and dengue cases that require further targeted research.
在柬埔寨，登革热是12岁及以下儿童发病的主要原因；2012年流行季节是该国自2007年以来最严重的，报告的（疑似或确诊）病例超过42000例。
我们报告了柬埔寨国家儿童医院701例患者的基本流行病学特征，这些患者是在一项前瞻性临床研究（2011 - 2012年）期间招募的。为了更全面地研究这个队列，我们使用多元负二项式模型检查气候因素，并使用空间扫描统计方法对病例进行空间聚类，以便将临床研究置于更大的流行病学框架内。
我们在城中村尺度上确定了具有统计学意义的空间聚类，并发现病例增加的关键气候预测因素是每周最低温度、中位数相对湿度，但发现与最大降雨量呈负相关，所有这些都在滞后1 - 6周时出现，显著影响延伸至10周。
我们的结果确定了邻里尺度上感染的聚类，为有针对性的干预提供了要点，并且我们发现，在这种情况下，病媒与气候条件的复杂相互作用可能最好通过最低温度上升和中位数（而非平均值）相对湿度来体现，降雨的影响复杂且有限。这些结果表明，柬埔寨应考虑在疫情期间进行实时聚类检测，并且改善天气数据报告可能会使国家防控计划受益，因为这样可以将有限的卫生资源更优先地分配给弱势群体和风险最大的时间段。最后，这些结果增加了越来越多的知识体系，表明气候与登革热病例之间存在复杂的相互作用，需要进一步开展有针对性的研究。
