Literature DB >> 33633493

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

A Alexiadis1, A Albano1, A Rahmat1, M Yildiz2, A Kefal2, M Ozbulut3, N Bakirci4, D A Garzón-Alvarado5, C A Duque-Daza1,5, J H Eslava-Schmalbach6.   

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.
© 2021 The Authors.

Entities:  

Keywords:  COVID-19; discrete epidemiology; epidemiology; numerical modelling; particle-based methods

Year:  2021        PMID: 33633493      PMCID: PMC7897638          DOI: 10.1098/rspa.2020.0653

Source DB:  PubMed          Journal:  Proc Math Phys Eng Sci        ISSN: 1364-5021            Impact factor:   2.704


  9 in total

1.  Creating a surrogate commuter network from Australian Bureau of Statistics census data.

Authors:  Kristopher M Fair; Cameron Zachreson; Mikhail Prokopenko
Journal:  Sci Data       Date:  2019-08-16       Impact factor: 6.444

2.  Spatial extent of an outbreak in animal epidemics.

Authors:  Eric Dumonteil; Satya N Majumdar; Alberto Rosso; Andrea Zoia
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-25       Impact factor: 11.205

3.  Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling.

Authors:  Rebecca J Rockett; Alicia Arnott; Connie Lam; Rosemarie Sadsad; Verlaine Timms; Karen-Ann Gray; John-Sebastian Eden; Sheryl Chang; Mailie Gall; Jenny Draper; Eby M Sim; Nathan L Bachmann; Ian Carter; Kerri Basile; Roy Byun; Matthew V O'Sullivan; Sharon C-A Chen; Susan Maddocks; Tania C Sorrell; Dominic E Dwyer; Edward C Holmes; Jen Kok; Mikhail Prokopenko; Vitali Sintchenko
Journal:  Nat Med       Date:  2020-07-09       Impact factor: 53.440

4.  Tracking random walks.

Authors:  Riccardo Gallotti; Rémi Louf; Jean-Marc Luck; Marc Barthelemy
Journal:  J R Soc Interface       Date:  2018-02       Impact factor: 4.118

5.  Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

Authors:  Marco Ajelli; Bruno Gonçalves; Duygu Balcan; Vittoria Colizza; Hao Hu; José J Ramasco; Stefano Merler; Alessandro Vespignani
Journal:  BMC Infect Dis       Date:  2010-06-29       Impact factor: 3.090

6.  The discrete multi-hybrid system for the simulation of solid-liquid flows.

Authors:  Alessio Alexiadis
Journal:  PLoS One       Date:  2015-05-11       Impact factor: 3.240

7.  Large-scale physical activity data reveal worldwide activity inequality.

Authors:  Tim Althoff; Rok Sosič; Jennifer L Hicks; Abby C King; Scott L Delp; Jure Leskovec
Journal:  Nature       Date:  2017-07-10       Impact factor: 49.962

8.  Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model.

Authors:  Cameron Zachreson; Kristopher M Fair; Oliver M Cliff; Nathan Harding; Mahendra Piraveenan; Mikhail Prokopenko
Journal:  Sci Adv       Date:  2018-12-12       Impact factor: 14.136

9.  The effect of mask use on the spread of influenza during a pandemic.

Authors:  Nicole C J Brienen; Aura Timen; Jacco Wallinga; Jim E van Steenbergen; Peter F M Teunis
Journal:  Risk Anal       Date:  2010-05-20       Impact factor: 4.000

  9 in total
  1 in total

1.  A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities.

Authors:  Ling Yin; Hao Zhang; Yuan Li; Kang Liu; Tianmu Chen; Wei Luo; Shengjie Lai; Ye Li; Xiujuan Tang; Li Ning; Shengzhong Feng; Yanjie Wei; Zhiyuan Zhao; Ying Wen; Liang Mao; Shujiang Mei
Journal:  J R Soc Interface       Date:  2021-08-25       Impact factor: 4.118

  1 in total

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