Improving Infectious Disease Models through social contact data: An endemic epidemic framework for disease prediction

Eishita Yadav, University of Limerick

Co-authors: James Sweeney, University of Limerick

Abstract: This research aims to improve infectious disease models by incorporating transmission matrices in their framework that account for heterogeneity in interactions across age groups and social settings. A simulation study is conducted where age specific disease counts are generated for Ireland. An endemic-epidemic model is applied to the generated over-dispersed disease count data. The model accounts for both baseline (endemic) disease levels as well as short term fluctuations (epidemic) caused by outbreaks. Predictions are validated against the simulated data. The results of the simulation study illustrate the potential of the approach to accurately model the impact of age specific interaction factors and public health interventions on disease spread.