Costs of dengue prevention and incremental cost of dengue outbreak control in Guantanamo, Cuba

Objective To assess the economic cost of routine Aedes aegypti control in an at‐risk environment without dengue endemicity and the incremental costs incurred during a sporadic outbreak. Methods The study was conducted in 2006 in the city of Guantanamo, Cuba. We took a societal perspective to calculate costs in months without dengue transmission (January–July) and during an outbreak (August–December). Data sources were bookkeeping records, direct observations and interviews. Results The total economic cost per inhabitant (p.i.) per month. (p.m.) increased from 2.76 USD in months without dengue transmission to 6.05 USD during an outbreak. In months without transmission, the routine Aedes control programme cost 1.67 USD p.i. p.m. Incremental costs during the outbreak were mainly incurred by the population and the primary/secondary level of the healthcare system, hardly by the vector control programme (1.64, 1.44 and 0.21 UDS increment p.i. p.m., respectively). The total cost for managing a hospitalized suspected dengue case was 296.60 USD (62.0% direct medical, 9.0% direct non‐medical and 29.0% indirect costs). In both periods, the main cost drivers for the Aedes control programme, the healthcare system and the community were the value of personnel and volunteer time or productivity losses. Conclusions Intensive efforts to keep A. aegypti infestation low entail important economic costs for society. When a dengue outbreak does occur eventually, costs increase sharply. In‐depth studies should assess which mix of activities and actors could maximize the effectiveness and cost‐effectiveness of routine Aedes control and dengue prevention.     

The development of predictive tools for pre‐emptive dengue vector control: a study of Aedes aegypti abundance and meteorological variables in North Queensland,Australia

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 (R² = 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 week 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.