Department of Physics, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand.
Université de Lyon, INRAE, VetAgro Sup, UMR EPIA, 69280, Marcy l'Etoile, France.
Sci Rep. 2022 Mar 24;12(1):5066. doi: 10.1038/s41598-022-09079-y.
Leptospirosis is a globally important zoonotic disease. The disease is particularly important in tropical and subtropical countries. Infections in humans can be caused by exposure to infected animals or contaminated soil or water, which are suitable for Leptospira. To explore the cluster area, the Global Moran's I index was calculated for incidences per 100,000 population at the province level during 2012-2018, using the monthly and annual data. The high-risk and low-risk provinces were identified using the local indicators of spatial association (LISA). The risk factors for leptospirosis were evaluated using a generalized linear mixed model (GLMM) with zero-inflation. We also added spatial and temporal correlation terms to take into account the spatial and temporal structures. The Global Moran's I index showed significant positive values. It did not demonstrate a random distribution throughout the period of study. The high-risk provinces were almost all in the lower north-east and south parts of Thailand. For yearly reported cases, the significant risk factors from the final best-fitted model were population density, elevation, and primary rice crop arable areas. Interestingly, our study showed that leptospirosis cases were associated with large areas of rice production but were less prevalent in areas of high rice productivity. For monthly reported cases, the model using temperature range was found to be a better fit than using percentage of flooded area. The significant risk factors from the model using temperature range were temporal correlation, average soil moisture, normalized difference vegetation index, and temperature range. Temperature range, which has strongly negative correlation to percentage of flooded area was a significant risk factor for monthly data. Flood exposure controls should be used to reduce the risk of leptospirosis infection. These results could be used to develop a leptospirosis warning system to support public health organizations in Thailand.
钩端螺旋体病是一种具有全球重要意义的动物源性传染病。该疾病在热带和亚热带国家尤为重要。人类感染可能是由于接触受感染的动物或受污染的土壤或水，这些环境适合钩端螺旋体生长。为了探索聚集区域，我们使用每月和每年的数据，计算了 2012-2018 年省级每 10 万人发病率的全局 Moran's I 指数。使用局部空间关联指标（LISA）确定高风险和低风险省份。使用具有零膨胀的广义线性混合模型（GLMM）评估钩端螺旋体病的危险因素。我们还添加了空间和时间相关项，以考虑空间和时间结构。全局 Moran's I 指数显示出显著的正值。在整个研究期间，它没有显示出随机分布。高风险省份几乎都在泰国的东北部和南部。对于每年报告的病例，最终最佳拟合模型的显著危险因素是人口密度、海拔和主要水稻作物耕地面积。有趣的是，我们的研究表明，钩端螺旋体病病例与大面积水稻生产有关，但在水稻高产区的发病率较低。对于每月报告的病例，使用温度范围的模型比使用淹没面积百分比的模型拟合得更好。使用温度范围的模型的显著危险因素是时间相关、平均土壤湿度、归一化差异植被指数和温度范围。与淹没面积百分比呈强负相关的温度范围是每月数据的一个重要危险因素。应使用洪水暴露控制措施来降低感染钩端螺旋体病的风险。这些结果可用于开发钩端螺旋体病预警系统，以支持泰国的公共卫生组织。
