This thesis is an investigation into measures of disease frequency for Porcine Epidemic Diarrhea Virus (PEDV) and Porcine Deltacoronavirus (PDCoV) in Ontario, as well as outbreak forecasts for Porcine Epidemic Diarrhea Virus (PEDV) in Ontario. Surveillance data from an industry-administered voluntary disease control program (DCP) were analysed to obtain estimates of incidence risk, incidence rate, and prevalence for Porcine Epidemic Diarrhea Virus (PEDV) and Porcine Deltacoronavirus (PDCoV) between 2014 and 2016. The results indicate an overall decline in disease frequency measures, from a prevalence of 4.36% to 1.35% and 0.48% to 0.16% from 2014 to 2016, for PEDV and PDCoV respectively. For PEDV outbreak forecasts, incidence as well as prevalence and weather data were trained on Classification and Regression Trees (CART), Random Forest, and Artificial Neural Network models. The Random Forest model provided the best prediction for long-term PEDV trends, with the variable importance measure pointing to prevalence and low temperature as strong determinants for future PEDV outbreaks.