During the COVID-19 pandemic, lockdowns were introduced in many countries around the world to reduce social interactions. As a result, the spread of the coronavirus was limited. Unfortunately, it also had a negative impact on healthcare: scheduled surgeries were canceled and appointments with doctors and examinations were rescheduled. Access to health care was difficult, and contacts with doctors were discouraged without serious symptoms. Consequently, diseases, that normally would have been detected faster, were silently progressing and impacting people’s lives. Finally, when the disease was manifesting itself, it was often too late to apply the benign treatment. Patients were suffering from serious complications or even died.

The aim of the project is to investigate the impact of lockdowns on breast cancer costs. During pandemics, the screening programs were halted and their overall yearly costs decreased. However, we hypothesize that the delayed detection of breast cancer among many patients resulted in a larger costs increase, whether due to more intensive treatment or patients death.

The scope of tasks in this project will include, inter alia, preparing and developing a model of the disease based on the available data and publications. Based on available literature and knowledge the types of cost (direct/indirect) will need to be specified. This model will be used to simulate the population under lockdown conditions and in the absence of a pandemic. The modeling can be conducted with differential equations, Markov Model, or other chosen methods. After conducting the simulations the analysis of costs, delayed diagnoses and deaths will be undertaken. For the model’s development, the Python programming language will be used.