Microsimulation based quantitative analysis of COVID-19 management strategies.

ABSTRACT: Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies

SUBMITTER: Reguly IZ 

PROVIDER: S-EPMC8759654 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature