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Simulation of pandemics in real cities: enhanced and accurate digital laboratories. | LitMetric

AI Article Synopsis

  • The study creates a modeling framework to simulate how infectious diseases spread in real cities by digitally replicating Birmingham (UK) and Bogotá (Colombia), including their environments and populations.
  • It uses both predictable and random movement patterns of digital inhabitants to replicate real-life interactions, simulating millions of encounters and disease spread over extended periods with high-performance computing.
  • The model effectively mirrors actual COVID-19 data for both cities and serves as a virtual laboratory for policymakers to explore and assess the impact of various epidemic containment strategies.

Article Abstract

This study develops a modelling framework for simulating the spread of infectious diseases within real cities. Digital copies of Birmingham (UK) and Bogotá (Colombia) are generated, reproducing their urban environment, infrastructure and population. The digital inhabitants have the same statistical features of the real population. Their motion is a combination of predictable trips (commute to work, school, etc.) and random walks (shopping, leisure, etc.). Millions of individuals, their encounters and the spread of the disease are simulated by means of high-performance computing and massively parallel algorithms for several months and a time resolution of 1 minute. Simulations accurately reproduce the COVID-19 data for Birmingham and Bogotá both before and during the lockdown. The model has only one adjustable parameter calculable in the early stages of the pandemic. Policymakers can use our digital cities as virtual laboratories for testing, predicting and comparing the effects of policies aimed at containing epidemics.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897638PMC
http://dx.doi.org/10.1098/rspa.2020.0653DOI Listing

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