SUMMARY OBJECTIVES: To describe the meteorological influences on adult dengue vector abundance in Australia for the development of predictive models to trigger pre-emptive control operation. METHODS: Multiple linear regression analyses were performed using meteorological data and female Aedes aegypti collection data from BG-Sentinel Mosquito traps placed at 11 monitoring sites in Cairns, north Queensland. RESULTS: Considerable regression coefficients (R(2) = 0.64 and 0.61) for longer- and shorter-term factor models respectively were derived. Longer-term factors significantly associated with abundance of adult vectors were mean minimum temperature (lagged 6 month) and mean daily temperature (lagged 4 month), explaining the predictable increase in abundance during the wet season. Factors explaining fluctuation in abundance in the shorter term were mean relative humidity over the previous 2 weeks and current daily average temperature. Rainfall variables were not found to be strong predictors of A. aegypti abundance in either longer- or shorter-term models. CONCLUSIONS: The implications of these findings for the development of useful predictive models for vector abundance risks are discussed. Such models can be used to guide the application of pre-emptive dengue vector control, and thereby enhance disease management.
SUMMARY OBJECTIVES: To describe the meteorological influences on adult dengue vector abundance in Australia for the development of predictive models to trigger pre-emptive control operation. METHODS: Multiple linear regression analyses were performed using meteorological data and female Aedes aegypti collection data from BG-Sentinel Mosquito traps placed at 11 monitoring sites in Cairns, north Queensland. RESULTS: Considerable regression coefficients (R(2) = 0.64 and 0.61) for longer- and shorter-term factor models respectively were derived. Longer-term factors significantly associated with abundance of adult vectors were mean minimum temperature (lagged 6 month) and mean daily temperature (lagged 4 month), explaining the predictable increase in abundance during the wet season. Factors explaining fluctuation in abundance in the shorter term were mean relative humidity over the previous 2 weeks and current daily average temperature. Rainfall variables were not found to be strong predictors of A. aegypti abundance in either longer- or shorter-term models. CONCLUSIONS: The implications of these findings for the development of useful predictive models for vector abundance risks are discussed. Such models can be used to guide the application of pre-emptive dengue vector control, and thereby enhance disease management.
Authors: Susan P Jacups; Luke P Rapley; Petrina H Johnson; Seleena Benjamin; Scott A Ritchie Journal: Am J Trop Med Hyg Date: 2013-01-28 Impact factor: 2.345
Authors: Saul Lozano-Fuentes; Mary H Hayden; Carlos Welsh-Rodriguez; Carolina Ochoa-Martinez; Berenice Tapia-Santos; Kevin C Kobylinski; Christopher K Uejio; Emily Zielinski-Gutierrez; Luca Delle Monache; Andrew J Monaghan; Daniel F Steinhoff; Lars Eisen Journal: Am J Trop Med Hyg Date: 2012-09-17 Impact factor: 2.345
Authors: Elizabet L Estallo; Francisco F Ludueña-Almeida; María V Introini; Mario Zaidenberg; Walter R Almirón Journal: PLoS One Date: 2015-05-20 Impact factor: 3.240