Background: Depression is a treatable disease, and untreated depression can lead to serious health complications and decrease the quality of life. Therefore, prevention, early identification, and treatment efforts are essential. Screening has an essential role in preventive medicine in the general population. Ideally, screening tools detect patients early enough to manage the disease and reduce symptoms. We aimed to determine the cost-effectiveness of routine screening schedules. Methods: We used a discrete-time nonstationary Markov model to simulate the progression of depression. We used Monte Carlo techniques to simulate the stochastic model for 20 years or during the lifetime of individuals. Baseline and screening scenario models with screening frequencies of annual, 2-year, and 5-year strategies were compared based on incremental cost-effectiveness ratios (ICER). Monte Carlo (MC) simulation and one-way sensitivity analysis were conducted to manage uncertainties. Results: In the general population, all screening strategies were cost-effective compared to the baseline. However, male and female populations differed based on cost over quality-adjusted life years (QALY). Females had lower ICERs, and annual screening had the highest ICER for females, with 11,134/QALYgained.Incontrast,maleshadaroundthreetimeshigherICER,withannualscreeningcostsof34,065/QALY gained. Limitations: We assumed that the screening frequency was not changing at any time during the screening scenario. In our calculations, false-positive cases were not taking into account. Conclusions: Considering the high lifetime prevalence and recurrence rates of depression, detection and prevention efforts can be one critical cornerstone to support required care. Our analysis combined the expected benefits and costs of screening and assessed the effectiveness of screening scenarios. We conclude that routine screening is cost-effective for all age groups of females and young, middle-aged males
