Naish Suchithra, Mengersen Kerrie, Tong Shi-Lu
Geospat Health. 2013 Nov;8(1):289-99. doi: 10.4081/gh.2013.74.
Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia but few data are available on the risk factors. We assessed the impact of spatial climatic, socioeconomic and ecological factors on the transmission of BFV disease in Queensland, Australia, using spatial regression. All our analyses indicate that spatial lag models provide a superior fit to the data compared to spatial error and ordinary least square models. The residuals of the spatial lag models were found to be uncorrelated, indicating that the models adequately account for spatial and temporal autocorrelation. Our results revealed that minimum temperature, distance from coast and low tide were negatively and rainfall was positively associated with BFV disease in coastal areas, whereas minimum temperature and high tide were negatively and rainfall was positively associated with BFV disease (all P-value.
巴马森林病毒(BFV)病是澳大利亚第二常见的蚊媒疾病,但关于其风险因素的数据很少。我们利用空间回归分析评估了空间气候、社会经济和生态因素对澳大利亚昆士兰州BFV疾病传播的影响。我们所有的分析表明,与空间误差模型和普通最小二乘模型相比,空间滞后模型对数据的拟合效果更好。发现空间滞后模型的残差不相关,这表明这些模型充分考虑了空间和时间自相关性。我们的结果显示,在沿海地区,最低温度、与海岸的距离和低潮与BFV疾病呈负相关,而降雨量与BFV疾病呈正相关;而最低温度和高潮与BFV疾病呈负相关,降雨量与BFV疾病呈正相关(所有P值……) (注:原文最后“all P-value”表述不完整)