Japanese encephalitis (JE) is a vector-borne zoonosis and the leading cause of human viral encephalitis in Asia. Its transmission cycle is usually described as involving wild birds as reservoirs and pigs as amplifying hosts. JE is endemic in Cambodia, where it circulates in areas with low pig densities (<70 pigs per km2), and could be maintained in a multi-host system composed of pigs, but also poultry as competent hosts, and dogs, cattle and humans as non-competent hosts. We used a mathematical model representing Japanese encephalitis virus (JEV) transmission in a traditional Cambodian village that we calibrated with field data collected in 3 districts of Kandal province, Cambodia. First, R0 calculations allowed us to assess the capacity of the epidemiological system to be invaded by JEV and sustain virus transmission in villages in the 3 districts, and we predicted human exposure at the epidemiological equilibrium, based on simulations. Changes in spatial density of livestock, in agricultural practices, and epizootics (e.g., African swine fever), can profoundly alter the composition of host communities, which could affect JEV transmission and its impact on human health. In a second step, we then used the model to analyse how host community composition affected R0 and the predicted human exposure. Lastly, we evaluated the potential use of dog JE seroprevalence as an indicator of human exposure to JEV. In the modeled villages, the calculated R0 ranged from 1.07 to 1.38. Once the equilibrium reached, predicted annual probability of human exposure ranged from 9% to 47%, and predicted average age at infection was low, between 2 and 11 years old, highlighting the risk of severe forms of JEV infection and the need to intensify child immunization. According to the model, increasing the proportion of competent hosts induced a decrease in age at infection. The simulations also showed that JEV could invade a multi-host system with no pigs, reinforcing the assumption of poultry acting as reservoirs. Finally, the annual human exposure probability appeared linearly correlated with dog seroprevalence, suggesting that in our specific study area, dog seroprevalence would be a good proxy for human exposure.