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20212026
most citedZero-state Coupled Markov Switching Count Models for Spatio-temporal Infectious Disease Spread

15 citations · 17 across the 5 of their papers we have counts for

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5 papers

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.AP2024

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.AP2023★ 1 cited

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…

stat.AP2023★ 1 cited

A three-state coupled Markov switching model for COVID-19 outbreaks across Quebec based on hospital admissions

Dirk Douwes-Schultz, Alexandra M. Schmidt, Yannan Shen +1

Recurrent COVID-19 outbreaks have placed immense strain on the hospital system in Quebec. We develop a Bayesian three-state coupled Markov switching model to analyze COVID-19 outbr…

stat.AP2021★ 15 cited

Zero-state Coupled Markov Switching Count Models for Spatio-temporal Infectious Disease Spread

Dirk Douwes-Schultz, Alexandra M. Schmidt

Spatio-temporal counts of infectious disease cases often contain an excess of zeros. With existing zero inflated count models applied to such data it is difficult to quantify space…