Viennet Elvina, Frentiu Francesca D, McKenna Emilie, Torres Vasconcelos Flavia, Flower Robert L P, Faddy Helen M
Research and Development, Strategy and Growth, Australian Red Cross Lifeblood, Kelvin Grove, QLD 4059, Australia.
School of Biomedical Sciences, Centre for Immunology and Infection Control, Queensland University of Technology, Brisbane, QLD 4001, Australia.
Biology (Basel). 2024 Jul 15;13(7):524. doi: 10.3390/biology13070524.
Arboviruses pose a significant global public health threat, with Ross River virus (RRV), Barmah Forest virus (BFV), and dengue virus (DENV) being among the most common and clinically significant in Australia. Some arboviruses, including those prevalent in Australia, have been reported to cause transfusion-transmitted infections. This study examined the spatiotemporal variation of these arboviruses and their potential impact on blood donation numbers across Australia. Using data from the Australian Department of Health on eight arboviruses from 2002 to 2017, we retrospectively assessed the distribution and clustering of incidence rates in space and time using Geographic Information System mapping and space-time scan statistics. Regression models were used to investigate how weather variables, their lag months, space, and time affect case and blood donation counts. The predictors' importance varied with the spatial scale of analysis. Key predictors were average rainfall, minimum temperature, daily temperature variation, and relative humidity. Blood donation number was significantly associated with the incidence rate of all viruses and its interaction with local transmission of DENV, overall. This study, the first to cover eight clinically relevant arboviruses at a fine geographical level in Australia, identifies regions at risk for transmission and provides valuable insights for public health intervention.
虫媒病毒对全球公共卫生构成重大威胁,其中罗斯河病毒(RRV)、巴马森林病毒(BFV)和登革病毒(DENV)是澳大利亚最常见且具有临床意义的病毒。据报道,包括在澳大利亚流行的一些虫媒病毒可导致输血传播感染。本研究调查了这些虫媒病毒的时空变化及其对澳大利亚各地献血人数的潜在影响。利用澳大利亚卫生部2002年至2017年关于八种虫媒病毒的数据,我们使用地理信息系统绘图和时空扫描统计方法,回顾性评估了发病率在空间和时间上的分布及聚集情况。采用回归模型研究天气变量、其滞后月份、空间和时间如何影响病例数和献血次数。预测因素的重要性随分析的空间尺度而变化。关键预测因素包括平均降雨量、最低温度、日温度变化和相对湿度。总体而言,献血次数与所有病毒的发病率及其与登革病毒局部传播的相互作用显著相关。本研究首次在澳大利亚精细地理层面涵盖了八种具有临床相关性的虫媒病毒,确定了有传播风险的地区,并为公共卫生干预提供了有价值的见解。