School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China.
Trop Med Int Health. 2023 Jul;28(7):551-561. doi: 10.1111/tmi.13896. Epub 2023 May 25.
Scrub typhus is an increasingly serious public health problem, which is becoming the most common vector-borne disease in Guangzhou. This study aimed to analyse the correlation between scrub typhus incidence and potential factors and rank the importance of influential factors.
We collected monthly scrub typhus cases, meteorological variables, rodent density (RD), Normalised Difference Vegetation Index (NDVI), and land use type in Guangzhou from 2006 to 2019. Correlation analysis and a random forest model were used to identify the risk factors for scrub typhus and predict the importance rank of influencing factors related to scrub typhus incidence.
The epidemiological results of the scrub typhus cases in Guangzhou between 2006 and 2019 showed that the incidence rate was on the rise. The results of correlation analysis revealed that a positive relationship between scrub typhus incidence and meteorological factors of mean temperature (T ), accumulative rainfall (RF), relative humidity (RH), sunshine hours (SH), and NDVI, RD, population density, and green land coverage area (all p < 0.001). Additionally, we tested the relationship between the incidence of scrub typhus and the lagging meteorological factors through cross-correlation function, and found that incidence was positively correlated with 1-month lag T , 2-month lag RF, 2-month lag RH, and 6-month lag SH (all p < 0.001). Based on the random forest model, we found that the T was the most important predictor among the influential factors, followed by NDVI.
Meteorological factors, NDVI, RD, and land use type jointly affect the incidence of scrub typhus in Guangzhou. Our results provide a better understanding of the influential factors correlated with scrub typus, which can improve our capacity for biological monitoring and help public health authorities to formulate disease control strategies.
恙虫病是一个日益严重的公共卫生问题，在广州已成为最常见的虫媒传染病。本研究旨在分析恙虫病发病率与潜在因素的相关性，并对影响因素的重要性进行排序。
我们收集了 2006 年至 2019 年广州每月的恙虫病病例、气象变量、鼠密度（RD）、归一化植被指数（NDVI）和土地利用类型的数据。采用相关分析和随机森林模型来识别恙虫病的风险因素，并预测与恙虫病发病率相关的影响因素的重要性排名。
2006 年至 2019 年广州恙虫病病例的流行病学结果表明，发病率呈上升趋势。相关性分析结果表明，恙虫病发病率与气象因素平均温度（T）、累积降雨量（RF）、相对湿度（RH）、日照时数（SH）和 NDVI、RD、人口密度和绿地覆盖率呈正相关（均 P<0.001）。此外，我们通过交叉相关函数测试了恙虫病发病率与滞后气象因素之间的关系，发现发病率与 1 个月滞后 T、2 个月滞后 RF、2 个月滞后 RH 和 6 个月滞后 SH 呈正相关（均 P<0.001）。基于随机森林模型，我们发现 T 是影响因素中最重要的预测因子，其次是 NDVI。
气象因素、NDVI、RD 和土地利用类型共同影响广州恙虫病的发病率。我们的研究结果更好地理解了与恙虫病相关的影响因素，这有助于提高生物监测能力，并为公共卫生部门制定疾病控制策略提供参考。
