Tong S, Hu W
Centre for Public Health Research, Queensland University of Technology, Kelvin Grove, Queensland, Australia.
Environ Health Perspect. 2001 Dec;109(12):1271-3. doi: 10.1289/ehp.011091271.
In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values.
在本研究中,我们评估了气候变异性对罗斯河病毒(RRv)传播的影响,并在澳大利亚凯恩斯验证了一种流行病预测模型。1985年至1996年期间记录的RRv病例数据来自昆士兰州卫生部。气候和人口数据分别由澳大利亚气象局和澳大利亚统计局提供。互相关函数(CCF)表明,当月最高温度以及滞后2个月的降雨量和相对湿度与RRv的月发病率呈正相关且显著相关,而滞后5个月的相对湿度与RRv传播呈负相关。我们根据1985年至1994年收集的数据建立了自回归积分滑动平均(ARIMA)模型,然后使用1995年至1996年收集的数据对模型进行了验证。结果表明,滞后5个月的相对湿度(p < 0.001)和滞后2个月的降雨量(p < 0.05)似乎在凯恩斯RRv疾病传播中发挥了重要作用。此外,回归预测曲线与实际值模式一致。