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

ABSTRACT: 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 due to the need to account for correlations across space, time and disease in both the count and zero-inflated components of the model. We are interested in comparing the transmission dynamics of several co-circulating infectious diseases across space and time, where some of the diseases can be absent for long periods. We first assume there is a baseline disease that is well-established and always present in the region. The other diseases switch between periods of presence and absence in each area through a series of coupled Markov chains, which account for long periods of disease absence, disease interactions an

SUBMITTER: Douwes-Schultz D 

PROVIDER: S-EPMC12596980 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature