Fine-grained modeling and cost-effectiveness evaluation of public health policies for cervical cancer, with application to a Colombian case study

Background: Cervical cancer (CC) is globally ranked fourth in terms of incidence and mortality among women. Vaccination against Human Papilloma Virus (HPV) and screening programs can significantly reduce CC mortality rates. Hence, executing cost-effective public health policies for prevention and surveillance is crucial. However, defining policies that make the best use of the available resources is not easy, as it requires predicting the long-term costs and results of interventions on a changing population. Since the simpler task of predicting the results of public health policies is difficult, devising those that make the best usage of available resources is an arduous challenge for decision-makers. Methods: : We propose a fine-grained epidemiological simulation model based on differential equations, which predicts costs and effectiveness of CC public health policies that include vaccination and screening. The model represents population dynamics, HPV transmission within the population, likelihood of infection/clearance, virus-induced appearance of precancerous lesions and eventually of CC, as well as immunity gained with vaccination and early detection with screening. The model is implemented in an open-source software tool that allows defining and evaluating multiple policies. We validate the modeling approach against real population data and apply it to a case study based on Colombian data. Results: : For the Colombian case, our modeling approach showed minimal deviations with respect to reference population estimates over a 30-year horizon, and an accurate estimation of the age-standardized mortality rate. We analyzed 54 policies and identied 8 with appropriate costs/effectiveness results. We explored the sensitivity of our results to changes in parameters, including the discount rate and the performance of screening tests. Conclusions: : Our modeling approach can provide valuable support for healthcare decision-makers. The implementation into an automated tool allows customizing the analysis with country specific data, flexibly defining public health policies to be evaluated, and conducting disaggregated analysis of their cost and effectiveness.