collaborators

5 papers

stat.ME2026

Heterogeneous behavioral mechanisms in epidemiological models

Jessica Pavani, Rob Deardon, Alexandra M. Schmidt

Traditional epidemic models frequently assume behavioral homogeneity. The susceptible-infected-recovered model provides a robust foundation for characterizing disease transmission,…

stat.ME2026

Multivariable Behavioral Change Modeling of Epidemics in the Presence of Undetected Infections

Caitlin Ward, Rob Deardon, Alexandra M. Schmidt

Epidemic models are invaluable tools to understand and implement strategies to control the spread of infectious diseases, as well as to inform public health policies and resource a…

stat.AP2026

Hidden Markov Individual-level Models of Infectious Disease Transmission

Dirk Douwes-Schultz, Rob Deardon, Alexandra M. Schmidt

Individual-level epidemic models are increasingly being used to help understand the transmission dynamics of various infectious diseases. However, fitting such models to individual…

stat.AP2025

Markov switching zero-inflated space-time multinomial models for comparing multiple infectious diseases

Dirk Douwes-Schultz, Alexandra M. Schmidt, Laís Picinini Freitas +1

Univariate zero-inflated models are increasingly being used to account for excess zeros in spatio-temporal infectious disease counts. However, the multivariate case is challenging…

stat.AP2025

A Comparison between Markov Switching Zero-inflated and Hurdle Models for Spatio-temporal Infectious Disease Counts

Mingchi Xu, Dirk Douwes-Schultz, Alexandra M. Schmidt

In epidemiological studies, zero-inflated and hurdle models are commonly used to handle excess zeros in reported infectious disease cases. However, they can not model the persisten…