A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic

  title={A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic},
  author={Joe Hilton and Heather Riley and Lorenzo Pellis and Rabia Aziza and Samuel P. C. Brand and Ivy K Kombe and John Ojal and Andrea Parisi and Matt. J. Keeling and D. James Nokes and R Manson-Sawko and Thomas A. House},
  journal={PLoS Computational Biology},
The widespread, and in many countries unprecedented, use of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic has highlighted the need for mathematical models which can estimate the impact of these measures while accounting for the highly heterogeneous risk profile of COVID-19. Models accounting either for age structure or the household structure necessary to explicitly model many NPIs are commonly used in infectious disease modelling, but models incorporating both levels of… 

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