title: El Niño and arboviral disease prediction.
abstract: 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.
authors.affiliation: Department of Entomology, University of Queensland, St. Lucia, Queensland, Australia.
authors.forename: D
authors.initials: D
authors.lastname: Maelzer
authors.forename: S
authors.initials: S
authors.lastname: Hales
authors.forename: P
authors.initials: P
authors.lastname: Weinstein
authors.forename: M
authors.initials: M
authors.lastname: Zalucki
authors.forename: A
authors.initials: A
authors.lastname: Woodward
mesh_terms: D001102:Arbovirus Infections / Q000453:epidemiology*; D002980:Climate; D006801:Humans; D011891:Rain; D013696:Temperature