Bayesian Epidemic Compartmental Model for an Infectious Disease with Multiple Transition Paths: Analyzing Visceral Leishmaniasis in Brazil

• Activity Number: 341 - Statistical Applications in Infectious Disease Epidemiology
• Type: Contributed
• Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Marie Ozanne* and Jacob Oleson and Grant Brown
• Companies: University of Iowa and University of Iowa and University of Iowa
• Keywords: compartmental model ; infectious disease

Abstract

Visceral leishmaniasis (VL) is a vector-borne infectious disease endemic to many parts of the world, including Brazil. VL exhibits complex epidemic behavior; it can be carried by multiple species and has multiple modes of transmission. A species of sand fly transmits a parasite; it is responsible for horizontal transmission. Canine hosts also are known to experience vertical transmission. These complexities complicate both modeling and intervention efforts. This work is part of a larger study to model the pathogen transmission dynamics of VL. Compartmental models lend themselves to this end, but few have focused on the interplay between mammalian horizontal and vertical transmission. Using historical data, researchers have fit multinomial logistic regression models to estimate the proportions of individuals in various epidemic states. We investigate to what degree compartmental epidemic modeling techniques can improve epidemic state estimates for small surveillance studies. We fit several compartmental models, along with a Bayesian multinomial logistic regression. The DIC is used to compare model fit, and the population implications of each model are compared.