Background Subsequent epidemic waves have already emerged in some countries and in the absence of highly effective preventive and curative options, there is a need for detailed epidemiological examination of the role of patient characteristics on the development of outcomes. The objective of this study is to describe the probabilities of admission to the Intensive Care Unit (ICU) and the probabilities of hospital discharge among positive COVID-19 patients according to demographics and comorbidities recorded at hospital admission. Methods A prospective cohort study of all patients with COVID-19 found in the Electronic Medical Records of Jaber Al-Ahmad Al-Sabah Hospital in Kuwait was conducted. The study included 3995 individuals (symptomatic and asymptomatic) of all ages who tested positive from February 24th to May 27th, 2020, out of which 315 were treated in the ICU and 3619 were discharged including those who were transferred to a different healthcare unit without previously entering the ICU. A competing risk analysis considering two events, namely, ICU admission and hospital discharge using flexible hazard models was performed to describe the association between event-specific probabilities and patient characteristics.Results Results showed that being male, increasing age and comorbidities such as chronic kidney disease (CKD), asthma or chronic obstructive pulmonary disease and weakened immune system increased the risk of ICU admission within 10 days of entering the hospital. CKD and weakened immune system decreased the probabilities of discharge in both females and males however, the age-related pattern differed by gender. Diabetes, which was the most prevalent comorbid condition, had only a moderate impact on both probabilities whilst CKD which had the largest effect, was only present in 2% of the study cohort.Conclusion This study provides useful insight in describing the probability of ICU admission and hospital discharge according to age, gender, and comorbidities among confirmed COVID-19 cases in Kuwait. A web-tool is also provided for free to allow the user to estimate these probabilities for any combination of these covariates. These probabilities enable the deeper understanding of the hospital demand according to patient characteristics which is essential to hospital management and useful for developing a vaccination strategy.