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Introduction Leptospirosis is a zoonotic disease responsible for over 1 million severe cases and 60,000 deaths annually. The wide range of animal hosts and complex environmental drivers of transmission make targeted interventions challenging, particularly when restricted to regression-based analyses which have limited ability to deal with complexity. In Fiji, important environmental and socio-demographic factors include living in rural areas, poverty, and livestock exposure. This study aims to examine drivers of transmission under different scenarios of environmental and livestock exposures. Methods Spatial Bayesian networks (SBN) were used to analyse the influence of livestock and poverty on the risk of leptospirosis infection in urban compared to rural areas. The SBN models used a combination of spatially-explicit field data from previous work and publically available census information. Predictive risk maps were produced for overall risk, and for scenarios related to poverty, livestock, and urban/rural setting. Results While high, rather than low, commercial dairy farm density similarly increased the risk of infection in both urban (12% to 18%) and rural areas (70% to 79%), the presence of pigs in a village had different impact in rural (43% to 84%) compared with urban areas (4% to 24%). Areas with high poverty rates were predicted to have 26.6% and 18.0% higher probability of above average seroprevalence in rural and urban areas, respectively. In urban areas, this represents >300% difference between areas of low and high poverty, compared to 43% difference in rural areas. Conclusions Our study demonstrates the use of SBN to provide valuable insights into the drivers of leptospirosis transmission under complex scenarios. By estimating the risk of leptospirosis infection under different scenarios, such as urban versus rural areas, these subgroups or areas can be targeted with more precise interventions that focus on the most relevant key drivers of infection.

Leptospirosis is an important zoonotic disease in the Pacific Islands. In Fiji, two successive cyclones and severe flooding in 2012 resulted in outbreaks with 576 reported cases and 7% case-fatality. We conducted a cross-sectional seroprevalence study and used an eco-epidemiological approach to characterize risk factors and drivers for human leptospirosis infection in Fiji, and aimed to provide an evidence base for improving the effectiveness of public health mitigation and intervention strategies. Antibodies indicative of previous or recent infection were found in 19.4% of 2152 participants (81 communities on the 3 main islands). Questionnaires and geographic information systems data were used to assess variables related to demographics, individual behaviour, contact with animals, socioeconomics, living conditions, land use, and the natural environment. On multivariable logistic regression analysis, variables associated with the presence of Leptospira antibodies included male gender (OR 1.55), iTaukei ethnicity (OR 3.51), living in villages (OR 1.64), lack of treated water at home (OR 1.52), working outdoors (1.64), living in rural areas (OR 1.43), high poverty rate (OR 1.74), living <100m from a major river (OR 1.41), pigs in the community (OR 1.54), high cattle density in the district (OR 1.04 per head/sqkm), and high maximum rainfall in the wettest month (OR 1.003 per mm). Risk factors and drivers for human leptospirosis infection in Fiji are complex and multifactorial, with environmental factors playing crucial roles. With global climate change, severe weather events and flooding are expected to intensify in the South Pacific. Population growth could also lead to more intensive livestock farming; and urbanization in developing countries is often associated with urban and peri-urban slums where diseases of poverty proliferate. Climate change, flooding, population growth, urbanization, poverty and agricultural intensification are important drivers of zoonotic dis