首页> 外文期刊>Frontiers in Applied Mathematics and Statistics >A Space-Time Study of Hemorrhagic Fever with Renal Syndrome (HFRS) and Its Climatic Associations in Heilongjiang Province, China
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A Space-Time Study of Hemorrhagic Fever with Renal Syndrome (HFRS) and Its Climatic Associations in Heilongjiang Province, China

机译:黑龙江省出血热伴肾综合征(HFRS)及其气候协会的时空研究

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Background: Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in China, especially in Heilongjiang province (90% of all reported HFRS cases worldwide occur in China). The dynamic identification of high HFRS incidence spatiotemporal regions and the quantitative assessment of HFRS associations with climate change in Heilongjiang province can provide valuable guidance for HFRS monitoring, preventing and control. Yet, so far there exist very few and of limited scope quantitative studies of the spatiotemporal HFRS spread and its climatic associations in Heilongjiang province. Method: To address this need, the well-known Bayesian maximum entropy (BME) method of space-time modeling and mapping together with its recent proposed variant, the projected BME (P-BME) method, were employed in this work to perform a composite space-time analysis and mapping of HFRS incidence in Heilongjiang province during the years 2005-2013. Also, using multivariate El Niño-Southern Oscillation index as a proxy, we employed Hilbert-Huang transform and wavelet analysis to study the a??HFRS incidence-climate changea?? associations. Results: We identified three core areas with high spatially distributed HFRS incidences and biomodal temporal patterns in the eastern, western and southern parts of Heilongjiang province. Furthermore, it was found that there exists a considerable association between HFRS incidence and climate change, particularly, an approximately 6 months period coherency was clearly detected. Conclusions: The combination of modern space-time modeling and mapping techniques (P-BME theory, Hilbert-Huang spectrum analysis and wavelet analysis) used in this work led to valuable quantitative findings concerning the spatiotemporal spread of HFRS incidence in Heilongjiang province and its association with climate change. Our findings include the identification of three core areas with high HFRS incidences in Heilongjiang province, and evidence was also found that HFRS incidence is closely related to climate change.
机译:背景:肾综合征出血热(HFRS)在中国非常流行,尤其是在黑龙江省(全世界报道的所有HFRS病例中有90%发生在中国)。黑龙江省HFRS高发时空区域的动态识别以及HFRS与气候变化的关联性定量评估可以为HFRS的监测,预防和控制提供有价值的指导。但是,到目前为止,黑龙江省时空HFRS传播及其气候联系的定量研究很少,而且范围有限。方法:为了满足这一需求,这项工作采用了著名的时空建模和映射的贝叶斯最大熵(BME)方法及其最近提出的变体投影BME(P-BME)方法来执行2005-2013年黑龙江省HFRS发病率的复合时空分析和绘图。另外,以多元厄尔尼诺-南方涛动指数为代理,我们使用希尔伯特-黄变换和小波分析研究了HFRS的发病率-气候变化a?协会。结果:我们在黑龙江省的东部,西部和南部地区确定了三个HFRS发病率空间分布较高且生物模式时态模式较高的核心地区。此外,发现HFRS发生率与气候变化之间存在相当大的关联,尤其是清楚地检测到大约6个月的时间一致性。结论:这项工作中使用的现代时空建模和制图技术(P-BME理论,希尔伯特-黄谱分析和小波分析)相结合,得出了关于黑龙江省HFRS发病率时空分布及其关联的有价值的定量发现。随着气候变化。我们的发现包括确定黑龙江省HFRS发生率高的三个核心地区,并且还发现有证据表明HFRS发生率与气候变化密切相关。

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