Climate and Landscape Factors Associated with Buruli Ulcer Incidence in Victoria, Australia

Abstract

Background

Buruli ulcer (BU), caused by Mycobacterium ulcerans (M. ulcerans), is a necrotizing skin disease found in more than 30 countries worldwide. BU incidence is highest in West Africa; however, cases have substantially increased in coastal regions of southern Australia over the past 30 years. Although the mode of transmission remains uncertain, the spatial pattern of BU emergence in recent years seems to suggest that there is an environmental niche for M. ulcerans and BU prevalence. Methodology/Principal Findings

Network analysis was applied to BU cases in Victoria, Australia, from 1981–2008. Results revealed a non-random spatio-temporal pattern at the regional scale as well as a stable and efficient BU disease network, indicating that deterministic factors influence the occurrence of this disease. Monthly BU incidence reported by locality was analyzed with landscape and climate data using a multilevel Poisson regression approach. The results suggest the highest BU risk areas occur at low elevations with forested land cover, similar to previous studies of BU risk in West Africa. Additionally, climate conditions as far as 1.5 years in advance appear to impact disease incidence. Warmer and wetter conditions 18–19 months prior to case emergence, followed by a dry period approximately 5 months prior to case emergence seem to favor the occurrence of BU. Conclusions/Significance

The BU network structure in Victoria, Australia, suggests external environmental factors favor M. ulcerans transmission and, therefore, BU incidence. A unique combination of environmental conditions, including land cover type, temperature and a wet-dry sequence, may produce habitat characteristics that support M. ulcerans transmission and BU prevalence. These findings imply that future BU research efforts on transmission mechanisms should focus on potential vectors/reservoirs found in those environmental niches. Further, this study is the first to quantitatively estimate environmental lag times associated with BU outbreaks, providing insights for future transmission investigations.