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.
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.
Authors: Assaf Anyamba; Jean-Paul Chretien; Jennifer Small; Compton J Tucker; Pierre B Formenty; Jason H Richardson; Seth C Britch; David C Schnabel; Ralph L Erickson; Kenneth J Linthicum Journal: Proc Natl Acad Sci U S A Date: 2009-01-14 Impact factor: 11.205
Authors: Shilu Tong; Pat Dale; Neville Nicholls; John S Mackenzie; Rodney Wolff; Anthony J McMichael Journal: Environ Health Perspect Date: 2008-07-24 Impact factor: 9.031