| Autor: |
Alexiadis, Alessio, Albano, Andrea, Rahmat, Amin, Yildiz, Mehmet, Kefal, Adnan, Özbulut, Murat, Bakirci, Nadi, Garzon Alvarado, Diego Alexander, Duque-Daza, Carlos Alberto, Eslava-Schmalbach, Javier Hernando |
| Přispěvatelé: |
Alexiadis, Alessio, School of Chemical Engineering University of Birmingham, University of Birmingham [Birmingham], Faculty of Engineering and Natural Sciences (Sabanci University), Sabanci University [Istanbul], Faculty of Engineering, Piri Reis University, Acibadem University, Department of Mechanical and Mechatronic Engineering, Universidad Nacional de Colombia, School of Medicine, Universidad Nacional de Colombia |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Popis: |
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 early stages of the pandemic. Policymakers can use our digital cities as virtual labs for testing, predicting, and comparing the effects of policies aimed at containing epidemics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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