Cacao (Theobroma cacao L.), is one of the most important tropical perennial cash crops worldwide. However, cacao production is severely impacted by diseases and account for losses estimated at around 30% of total yield worldwide. Cacao black pod rot, due to several Phytophthora spp., is the most important disease globally and the main cacao disease in Africa, responsible for yield losses up to 50-80% in the absence of control measures. In Cameroon, cacao black pod rot due to Phytophthora megakarya can even be responsible for losses up to 80-90%. Understanding diseases epidemics allows slowing or even stopping disease outbreaks by means of identification of adequate management strategies. This will ultimately help ensure sustainable cacao production. One way to improve the understanding of plant disease epidemics and the factors governing their spatio-temporal dynamics is mathematical modelling. It is well known that mathematical modelling allows better understanding of the mechanisms behind epidemics as well as help in identifying gaps in our knowledge. Although black pod rot of cacao is of major concern and much attention has been dedicated to it, there are still many questions regarding the factors that govern the disease dynamics. For instance the relative importance of the two different sources of inoculum (primary and secondary) and spore dispersal dynamics are not well understood. In an attempt to provide answers to these questions, a temporal mathematical model has been developed based on empirical data from and expert knowledge on cacao black pod epidemics. The model allows simulating and predicting disease outbreaks in a cacao plot and will enable us to identify control levers and sustainable management strategies. The general aim of this modelling study is to investigate different scenarios of epidemic evolution in order to highlight determinant factors on which management strategies could be build. To achieve this, we analyze the epidemiological model and