Aging Risk for Childhood Cancer Survivors
Headshot of Jennifer Yeh (top left), Zachary Ward (bottom right). Abstract art images are pictured as well (top right and bottom left).

The COMPASS model was developed to predict long-term outcomes based on treatment exposures and age-related risks in 5-year survivors of childhood cancer diagnosed and treated between 1970 and 1999. This model provides insight into survivor health risks compared to the general population with a goal of informing coordinated care.

Impact of HPV Vaccine Strategies
Image of Tom Gaziano and Natasha Stout in Conversation in Meeting.

Researchers used mathematical models to compare switching from a 2-dose to a 1-dose HPV vaccine. Results show countries can prevent nearly as many cervical cancer cases with 1 dose while awaiting long-term data.

Early HPV Natural History Transitions
Nicole Gastineau Campos standing with glass of water in hand

Microsimulation models used to evaluate the cost-effectiveness of novel cervical cancer screening technologies rely on accurate human papillomavirus (HPV) transition risks. To inform the refinement of such models, authors compared the early natural history of HPV types using three large prospective studies of immunocompetent women.

Elevated Body Weight in US

Is elevated body weight associated with excess mortality in the United States? Using an empirically calibrated microsimulation model, this analysis finds that excess weight not only has substantial impacts on mortality, but that there are large disparities by state and subgroup.

Reducing Cardiovascular Disease Inequities

This paper uses a microsimulation modeling approach and individual-level data from nationally representative surveys to model the distributional impacts of improving hypertension diagnosis and treatment on cardiovascular disease risk and cases across socioeconomic groups. 

New Models for Cervical Cancer Control

Authors propose a new health decision modeling framework to evaluate novel cervical screening technologies. The framework de-emphasizes previously used cytologic-colposcopic-histologic diagnoses, relying instead on HPV type and duration of infection as the major determinants of model transition probabilities.