Joint Multilevel Discrete Competing Risk with Continuous Outcome via Bivariate Copula Model - Application to a Dengue Epidemiology Study, Sri Lanka

The competing risk is a special branch of medical research where several multiple events can happen. It can encompass the joint modelling approach for dengue epidemiology to model the relation of different destinations of the length of stay and platelet count. Also, the district effect is an inherent feature of dengue highly associated with climate change. Therefore, this leads to the joint multilevel approaches for analyzing the different destinations of the length of stay of a dengue patient and platelet count. Here, length of stay is a discrete form and platelet count is in a continuous form. The joint modelling is done through a copula model with the formation of multilevel utility models for discrete competing risk response (different destination of the length of stay) and a multilevel linear regression model for platelet count. The within and between-study variability models are joined through random effects. The fitted model indicated that the white blood cell (WBC) count, year, and sex are the only associated factors for the platelet count and time indicators, age, classification, temperature, and rainfall have a significant impact on the rate of a discharging patient and only time indicators and classification were significant for a death rate in the joint model. Moreover, the joint model yielded more precise results than the univariate model.