Different responses of Ross River virus to climate variability between coastline and inland cities in Queensland, Australia
- Centre for Public Health Research, Queensland University of Technology, Kelvin Grove, Queensland 4059, Australia
- Correspondence to: Dr S Tong, Centre for Public Health Research, Queensland University of Technology, Kelvin Grove, Queensland 4059, Australia; s.tong{at}qut.edu.au
- Accepted 10 April 2002
Abstract
Aims: To examine the potential impact of climate variability on the transmission of Ross River virus (RRv) infection, and to assess the difference in the potential predictors of RRv incidence in coastline and inland regions, Queensland, Australia.
Methods: Information on the RRv cases notified between 1985 to 1996 was obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australia Bureau of Statistics, respectively. The function of cross correlations was used to compute a series of correlations between climate variables (rainfall, maximum temperature, minimum temperature, relative humidity, and high tide) and the monthly incidence of RRv disease over a range of time lags. Time series Poisson regression models were performed to adjust for the autocorrelations of the monthly incidences of RRv disease and the confounding effects of seasonality, the case notification time, and population sizes.
Results: The cross correlation function shows rainfall, maximum temperature, minimum temperature, and relative humidity at a lag of 1–2 months and high tide in the current month were significantly associated with the monthly incidence of RRv in the coastline region. Relative humidity and rainfall at a lag of two months was also significantly associated with the monthly incidence of RRv in the inland region. The results of Poisson regressive models show that the incidence of RRv disease was significantly associated with rainfall, maximum temperature, minimum temperature, relative humidity, and high tide in the coastline region, and with rainfall and relative humidity in the inland region. There was a significant interaction between climate variables and locality in RRv transmission.
Conclusions: Climate variability may have played a significant role in the transmission of RRv. There appeared to be different responses of RRv to climate variability between coastline and inland cities in Queensland, Australia. Maximum temperature appeared to exhibit a greater impact on the RRv transmission in coastline than in inland cities. Minimum temperature and relative humidity at 3 pm inland seemed to affect the RRv transmission more than at the coastline. However, the relation between climate variables and RRv needs to be viewed within a wider context of other social and environmental factors, and further research is needed.
