MODELS USING MODELS: USE OF MICROSIMULATION MODEL RESULTS TO IMPROVE ACCURACY OF AN EXCEL-BASED POLICY ANALYSIS TOOL FOR USE IN THE FIELD

Purpose: When choosing between models to inform resource allocation decisions, policymakers are often forced to trade complexity, accuracy, and flexibility for ease of use, computational speed, and transparency of model logic. The ProVac Initiative develops model-based tools and provides technical assistance to Latin American countries to build local capacity for economic evaluation of public health interventions. In developing ProVac's Cervical Cancer Prevention Model (CERVIVAC tool), we implement an innovative approach to leverage results of a highly sophisticated microsimulation model within a user-friendly Excel-based tool that can be used by local country teams without sacrificing quality of model results.

Method: The CERVIVAC model is an Excel-based cohort model used for economic evaluation of HPV vaccination and cervical screening. Reliable estimation of the impact of screening is challenging for several reasons including: necessity of model calibration to uncertain country-specific epidemic patterns, cumulated effects of repeated screening over a woman's lifetime, and complex natural history governing HPV infection, lesion development, regression and progression to cancer.  A cervical cancer microsimulation model developed for academic research handles these complexities. This model was used to generate outcomes for settings matching 4 distinct epidemiological profiles (Argentina, Brazil, Colombia, and Peru). Approximately 4000 screening strategies were defined by varying coverage, age range, technology, and frequency. Reductions in cancer were computed for each by Monte Carlo simulation. The results reside as a large lookup table in the CERVIVAC model, from which 'impact' estimates for user-specified strategies are drawn. Tests were conducted to determine which CERVIVAC model inputs needed to be included in the strategy specification for the microsimulation. Additionally, we compared CERVIVAC and microsimulation results for a common scenario.

Result: Post-hoc adjustment for Loss-to-follow-up (LTFU) at different points in the screening process introduced a small bias, compared to including LTFU variable in the microsimulation runs, but the bias was predictable and could be adjusted for post-hoc. Cost-effectiveness estimates from the CERVIVAC model were similar to analyses performed wholly in the academic microsimulation model.

Conclusion: The CERVIVAC tool produces results for the impact of cervical screening strategies that benefit from the complex calibration algorithms and screening dynamics implemented in the academic research-grade microsimulation, while retaining accessibility to CERVIVAC users seeking to carry out rapid country-specific assessments of the cost and impacts of cervical screening policies.