Systems Dynamics Modelling of Oral Cancer Care Pathways in Nigeria: Identifying Leverage Points for Reducing Diagnostic Delay

Oral cancer in Nigeria is characterized by persistently late-stage diagnosis, with the majority of patients presenting at stage III or IV disease, dramatically reducing five-year survival rates compared to high-income country benchmarks. The causal complexity of diagnostic delay involves interconnected individual, community, provider, and system-level factors that static analytical models fail to adequately capture. This PhD study develops a systems dynamics model of the oral cancer care pathway in Nigeria to identify high-leverage intervention points for reducing diagnostic delay. Using a participatory group model-building approach, causal loop diagrams were constructed through structured workshops involving 62 stakeholders from the South West, North Central, and South East geopolitical zones, including patients, community health workers, general practitioners, oral surgeons, oncologists, and health policy actors. The causal loop diagrams were translated into a quantitative system dynamics simulation model parameterized with data from 280 oral cancer patient interviews and institutional records from six tertiary hospitals. Scenario simulations tested the impact of ten candidate interventions on time from first symptom to definitive treatment over a 10-year horizon. Community awareness campaigns combined with CHW-led OCSE programs demonstrated the greatest reduction in diagnostic delay in simulation outputs, reducing median diagnosis delay from 8.4 months to 3.1 months when combined with priority referral fast-track pathways. Isolated supply-side interventions showed limited impact without demand-side behavior change. The study contributes an original systems science methodology to Nigerian oral oncology and recommends a bundled intervention package informed by the model outputs. Keywords: systems dynamics, oral cancer, diagnostic delay, care pathway, Nigeria.