Abstract
Ross River Virus (RRV) infection is the most incident arbovirus disease in Australia. Despite the significant human health burden of RRV, the ecological characteristics of putative exposure sites to RRV infected mosquitos are not fully understood. In this study, we aimed to ascertain the most likely sites of RRV exposure and their characteristics for individuals residing in the RRV notification hotpots of the Greater Brisbane Region.
We analysed all reported RRV notifications geolocated to the household level for the period prior, during and after the Queensland COVID19 lockdown (January 2020 to July 2020). We first used geospatial cluster detection methods to identify RRV notification hotspot areas for each study period. We then harvested mobile-phone data for users in the areas of residence of the identified RRV notification hotspots. Using network analysis, we estimated the areas in Greater Brisbane that were more connected and the average time people spent in green areas during the lockdown period. Using a Zero-inflated Poisson model, we estimated associations between RRV notifications and environmental data and population movement.
During the study period, a total of 993 RRV cases were notified with geolocation in Greater Brisbane, resulting in an annual case rate of 66.1 cases per 100,000 people and we identified a total of 22 RRV geospatial clusters. Our analysis of movement data involved 9 million movements from hotspots areas of residence of RRV cases. We found that areas with high degree centrality measures had a significant higher incidence of RRV (p-value <0.05). Additionally, we noticed a slight increase in time spent walking in green areas across the study period, while the time spent in green areas was lower in the pre-lockdown phase, averaging at 11.4 minutes per week. Further, we observed that areas with a higher percentage of vegetation cover had a higher RRV incidence (p-value <0.01).
This study provides strong evidence RRV exposure was likely to occur in urban areas, specifically locations with higher vegetation coverage than the target areas identified in this study (e.g. urban green areas). This information can be used as an evidence-base regarding changes to current surveillance protocols and the deployment of mosquito control and surveillance strategies to areas where the community in high-risk areas tend to spend more time outdoors.