Scan brief descriptions of methodological work conducted by our center community and our decision science colleagues.

Validating Cardiovascular Disease Model
Image of Ankur Pandya Speaking at Meeting.

This paper describes a cardiovascular disease model used to evaluate prevention and treatment, and a validation process in which simulated results were compared to observed all-cause and CVD-specific mortality data from the National Health and Nutrition Examination Survey using survival curves and ROC curves. 

Modeling the Natural History of HPV
Image of Nicole Campos

This analysis used an empirically calibrated model of cervical cancer to explore the age distribution at which individuals acquired their causal HPV infection, finding 50% acquired it by age 20.6 and 75% by age 30.6. These findings raise concerns about surrogate endpoints for vaccine efficacy studies of mid-adult women. 

Iterative Process of Empiric Calibration
Image of Sue Goldie and Jane Kim in Meeting

These two papers describe the construction and empiric calibration of a cervical cancer microsimulation model at two time points, first leveraging primary data from a large epidemiological study (Kim et al.), and second leveraging data on type-specific HPV persistence and clearance from the control arm of vaccine trials (Campos et al.).

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Featured Resource: Open Source Modeling Platform

Amua, the Swahili word meaning “decide”, is an open-source, freely-available software platform for users to build decision models. Designed to be transparent, flexible, and accessible, it is currently available for beta testing. Amua is being developed by Zach Ward. Learn about Amua.