Abstract
BACKGROUND: Dengue viruses have spread rapidly across tropical regions of the world in recent decades. Today, dengue transmission is observed in the Americas, Southeast Asia, Western Pacific, Africa and in non-endemic areas of the USA and Europe. Dengue is responsible for 16% of travel-related febrile illnesses. Although most prevalent in tropical areas, risk maps indicate that subtropical regions are suitable for transmission. Dengue-control programs in these regions should focus on minimizing virus importation, community engagement, improved vector surveillance and control. RESULTS: We developed a conceptual model for the probability of local introduction and propagation of dengue, comprising disease vulnerability and receptivity, in a temperate area, considering risk factors and social media indicators. Using a rich data set from a temperate area in the south of Brazil (where there is active surveillance of mosquitoes, viruses and human cases), we used a conceptual model as a framework to build two probabilistic models to estimate the probability of initiation and propagation of local dengue transmission. The final models estimated with good accuracy the probabilities of local transmission and propagation, with three and four weeks in advance, respectively. Vulnerability indicators (number of imported cases and dengue virus circulation in mosquitoes) and a receptivity indicator (vector abundance) could be optimally integrated with tweets and temperature data to estimate probability of early local dengue transmission. CONCLUSIONS: We demonstrated how vulnerability and receptivity indicators can be integrated into probabilistic models to estimate initiation and propagation of dengue transmission. The models successfully estimate disease risk in different scenarios and periods of the year. We propose a decision model with three different risk levels to assist in the planning of prevention and control measures in temperate regions at risk of dengue introduction.