The SARS-CoV-2 pandemic poses an unprecedented challenge to society and policy-making. The goal of OptimAgent is to develop a standardized model-based framework to support public health decision-making processes that can evaluate a wide range of infection control interventions. The focus is on the design of an agent-based model (ABM) that goes substantially beyond simulation approaches used to date. Through a flexible modular structure and an extensive consultation process with national and international modeling experts, the model will be tailored in particular to inform health policy decision-making during future pandemics. In addition, it will also be adaptable for endemic pathogens. The model will realistically represent the sociodemographic and regional structures of Germany. Agents will have demographic, socio-economic, sociological as well as psychological characteristics that influence individual contact behavior, risk of infection and disease. Based on the results of comprehensive and sophisticated analyses of contact behavior, specific model modules will be developed on selective target-directed contact restraints in different settings, contact tracking and testing strategies. The flexible modular model design will also provide opportunities for easy integration of additional components. The focus of the project is to analyze the impact of different dimensions of heterogeneity in the population as well as their interaction on the incidence of infection. This will provide new insights into the importance of heterogeneity in the spread of severe respiratory infectious diseases in the population and the effectiveness of pandemic control measures.