Maelzer D, Hales S, Weinstein P, Zalucki M, Woodward A
Department of Entomology, University of Queensland, St. Lucia, Queensland, Australia.
Environ Health Perspect. 1999 Oct;107(10):817-8. doi: 10.1289/ehp.99107817.
Recent El Niño events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to El Niño. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.
近期的厄尔尼诺事件激发了人们对开发预测极端气候及相关健康事件的建模技术的兴趣。此前的研究记录了特定气候变量（尤其是温度和降雨）与虫媒病毒病暴发之间的关联。在一些国家，此类疾病对厄尔尼诺现象敏感。在此，我们描述一种基于气候的模型，用于预测澳大利亚罗斯河病毒的流行情况。通过文献检索和病例通报数据，我们确定了1928年至1998年间澳大利亚南部哪些年份出现了罗斯河病毒疫情。预测变量为疫情当年或滞后1年的每月南方涛动指数值。我们发现，在东南部各州，前一年1月和9月的每月南方涛动指数值能很好地预测疫情年份。该模型预测1999年澳大利亚南部各州很有可能出现罗斯河病毒疫情。我们得出结论，至少在理论上，虫媒病毒病的流行可基于气候关系进行预测。
