Despite knowledge of vertical transmission for multiple infectious diseases for at least three-quarters of a century, we do not know how vertical transmission impacts the basic reproductive number (R0) of classically vector-borne infections. In addition, multi-species diseases are likely to persist through both vertical and horizontal transmission, and not enough is known about their collective impact on R0. It has been demonstrated that vertical transmission maintains endemic canine VL within US hunting hounds. We use this unique cohort to measure the infective capacity of vertical transmission in VL. With understanding gained from this study, we will be able to interpret how vertical transmission and horizontal transmission impact R0 separately, and we will quantify their interactive effect on R0. The proposed research introduces new statistical and computational methods for improved estimation of R0. Specifically, we propose to develop flexible spatio-temporal statistical models within the Bayesian hierarchical framework to evaluate the interactions between disease-causing organisms, their vectors, and their hosts. This work is proposed to be developed in the VL setting, and is designed to specifically motivate improved intervention efforts in Brazil, but to have wider applicability for a more general understanding of how complex transmission processes impact the estimation of R0. Previous models of VL transmission dynamics have not accounted for canine vertical transmission or a human reservoir. Coinfection with two or more pathogens modifies host immunity to each. This has been presumed true for multiple infections, but disease transmissibility has not been modeled based on the observation of comorbidity and transmissibility. Our goal is to find ways to decrease VL R0 to <1.0. We hypothesize that an integrative statistical model allowing hierarchical consideration of transmission in canine and human hosts, and vertical plus vector transmission, is a transformative tool to understand the interplay of vertical and vector borne disease. Finally, we will determine how disease transmission is influenced by different environments and comorbidities and compare roles of key transmission dynamics on pathogen maintenance, e.g. alter R0.