Janette Lindesay

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.

Weather-driven variation in dengue activity in Australia examined using a process-based modeling approach

The impact of weather variation on dengue transmission in Cairns, Australia, was determined by applying a process-based dengue simulation model (DENSiM) that incorporated local meteorologic, entomologic, and demographic data. Analysis showed that inter-annual weather variation is one of the significant determinants of dengue outbreak receptivity. Cross-correlation analyses showed that DENSiM simulated epidemics of similar relative magnitude and timing to those historically recorded in reported dengue cases in Cairns during 1991-2009, (r = 0.372, P < 0.01). The DENSiM model can now be used to study the potential impacts of future climate change on dengue transmission. Understanding the impact of climate variation on the geographic range, seasonality, and magnitude of dengue transmission will enhance development of adaptation strategies to minimize future disease burden in Australia.

The Development of Virtual World Tools to Enhance Learning and Real World Decision Making in the Australian Sugar Farming Industry

In farming, the outcome of critical decisions to enhance productivity and profitability and so ensure the viability of farming enterprises is often influenced by seasonal conditions and weather events over the growing season. This paper reports on a project that uses cutting-edge advances in digital technologies and their application in learning environments to develop and evaluate a web-based virtual ‘discussion-support’ system for improved climate risk management in Australian sugar farming systems. Customized scripted video clips (machinima) are created in the Second Life virtual world environment. The videos use contextualized settings and lifelike avatar actors to model conversations about climate risk and key farm operational decisions relevant to the real-world lives and practices of sugarcane farmers. The tools generate new cognitive schema for farmers to access and provide stimuli for discussions around how to incorporate an understanding of climate risk into operational decision-making. They also have potential to provide cost-effective agricultural extension which simulates real world face-to-face extension services but is accessible anytime anywhere.