Yang Li-Ping, Liang Si-Yuan, Wang Xian-Jun, Li Xiu-Jun, Wu Yan-Ling, Ma Wei
Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan, Shandong, People's Republic of China.
Shandong Center for Disease Control and Prevention, Jinan, Shandong, People's Republic of China.
PLoS Negl Trop Dis. 2015 Jan 8;9(1):e3420. doi: 10.1371/journal.pntd.0003420. eCollection 2015 Jan.
Laiwu District is recognized as a hyper-endemic region for scrub typhus in Shandong Province, but the seriousness of this problem has been neglected in public health circles.
METHODOLOGY/PRINCIPAL FINDINGS: A disability-adjusted life years (DALYs) approach was adopted to measure the burden of scrub typhus in Laiwu, China during the period 2006 to 2012. A multiple seasonal autoregressive integrated moving average model (SARIMA) was used to identify the most suitable forecasting model for scrub typhus in Laiwu. Results showed that the disease burden of scrub typhus is increasing yearly in Laiwu, and which is higher in females than males. For both females and males, DALY rates were highest for the 60-69 age group. Of all the SARIMA models tested, the SARIMA(2,1,0)(0,1,0)12 model was the best fit for scrub typhus cases in Laiwu. Human infections occurred mainly in autumn with peaks in October.
CONCLUSIONS/SIGNIFICANCE: Females, especially those of 60 to 69 years of age, were at highest risk of developing scrub typhus in Laiwu, China. The SARIMA (2,1,0)(0,1,0)12 model was the best fit forecasting model for scrub typhus in Laiwu, China. These data are useful for developing public health education and intervention programs to reduce disease.
莱城区被认为是山东省恙虫病的高度流行区，但这一问题的严重性在公共卫生领域一直被忽视。
方法/主要发现：采用伤残调整生命年（DALYs）方法来衡量2006年至2012年期间中国莱芜市恙虫病的负担。使用多重季节性自回归积分滑动平均模型（SARIMA）来确定莱芜市恙虫病最合适的预测模型。结果显示，莱芜市恙虫病的疾病负担逐年增加，女性高于男性。对于女性和男性来说，60 - 69岁年龄组的DALY率最高。在所有测试的SARIMA模型中，SARIMA(2,1,0)(0,1,0)12模型最适合莱芜市的恙虫病病例。人类感染主要发生在秋季，10月达到高峰。
结论/意义：在中国莱芜市，女性，尤其是60至69岁的女性，患恙虫病的风险最高。SARIMA(2,1,0)(0,1,0)12模型是中国莱芜市恙虫病的最佳拟合预测模型。这些数据有助于制定公共卫生教育和干预计划以减少疾病发生。
