Kang Dayun, Choi Jungsoon
Department of Applied Statistics, Hanyang University, Seoul.
Geospat Health. 2018 Nov 9;13(2). doi: 10.4081/gh.2018.665.
Scrub typhus, a bacterial, febrile disease commonly occurring in the autumn, can easily be cured if diagnosed early. However, it can develop serious complications and even lead to death. For this reason, it is an important issue to find the risk factors and thus be able to prevent outbreaks. We analyzed the monthly scrub typhus data over the entire areas of South Korea from 2010 through 2014. A 2-stage hierarchical framework was considered since weather data are covariates and the scrub typhus data have different spatial resolutions. At the first stage, we obtained the administrative-level estimates for weather data using a spatial model; in the second, we applied a Bayesian zero-inflated spatio-temporal model since the scrub typhus data include excess zero counts. We found that the zero-inflated model considering the spatio-temporal interaction terms improves fitting and prediction performance. This study found that low humidity and a high proportion of elderly people are significantly associated with scrub typhus incidence.
恙虫病是一种常见于秋季的细菌性发热疾病，如果早期诊断，很容易治愈。然而，它可能会引发严重并发症，甚至导致死亡。因此，找出风险因素并从而能够预防疫情爆发是一个重要问题。我们分析了2010年至2014年韩国全境每月的恙虫病数据。由于气象数据是协变量且恙虫病数据具有不同的空间分辨率，所以考虑了一个两阶段分层框架。在第一阶段，我们使用空间模型获得气象数据的行政级别估计值；在第二阶段，由于恙虫病数据包含过多的零计数，我们应用了贝叶斯零膨胀时空模型。我们发现，考虑时空交互项的零膨胀模型提高了拟合和预测性能。本研究发现，低湿度和高比例的老年人与恙虫病发病率显著相关。
