Predicting Ross River virus epidemics from regional weather data.
BACKGROUND
Diseases caused by arboviruses cause extensive mortality and morbidity throughout the world. Weather directly affects the breeding, abundance, and survival of mosquitoes, the principal vector of many arboviruses. The goal of this study was to test whether climate variables could predict with high levels of accuracy (more than 70%) epidemics of one arbovirus, Ross River virus disease.


METHODS
Weather data from two regions in southeastern Australia were matched with Ross River virus disease data for the period 1991 to 1999. Our aim was to develop simple models for the probability of the occurrence of an epidemic in an area in a given year.


RESULTS
Two predictable epidemic patterns emerged, after either high summer rainfalls or high winter rainfalls. A prerequisite relating to host-virus dynamics was lower than average spring rainfall in the preepidemic year. The sensitivity of the model was 96% for Region 1 and 73% for Region 2.


CONCLUSIONS
Early warning of weather conditions conducive to outbreaks of Ross River virus disease is possible at the regional level with a high degree of accuracy. Our models may have application as a decision tool for health authorities to use in risk-management planning.
Woodruff
Rosalie E
RE
National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia. rosalie.woodruff@anu.edu.au
Guest
Charles S
CS
Garner
Michael G
MG
Becker
Niels
N
Lindesay
Janette
J
Carvan
Terence
T
Ebi
Kristie
K
D018354:Alphavirus Infections / Q000453:epidemiology*; D000818:Animals; D001315:Australia / Q000453:epidemiology; D002980:Climate; D009033:Culicidae / Q000821:virology; D004196:Disease Outbreaks; D006801:Humans; D007303:Insect Vectors; D016012:Poisson Distribution; D011159:Population Surveillance; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012398:Ross River virus; D012680:Sensitivity and Specificity; D014887:Weather