Elementary effects analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of social distancing and mask usage

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@article{c999eabb99c04128bcb4f849725a75e3,
title = "Elementary effects analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of social distancing and mask usage",
abstract = "COVID-19 was declared a pandemic by the World Health Organisation (WHO) on March 11th, 2020. With half of the world's countries in lockdown as of April due to this pandemic, monitoring and understanding the spread of the virus and infection rates and how these factors relate to behavioural and societal parameters is crucial for developing control strategies. This paper aims to investigate the effectiveness of masks, social distancing, lockdown and self-isolation for reducing the spread of SARS-CoV-2 infections. Our findings from an agent-based simulation modelling showed that whilst requiring a lockdown is widely believed to be the most efficient method to quickly reduce infection numbers, the practice of social distancing and the usage of surgical masks can potentially be more effective than requiring a lockdown. Our multivariate analysis of simulation results using the Morris Elementary Effects Method suggests that if a sufficient proportion of the population uses surgical masks and follows social distancing regulations, then SARS-CoV-2 infections can be controlled without requiring a lockdown.",
keywords = "Agent-based modelling, Coronavirus, COVID-19, Epidemiology, Infectious diseases, Isolation, Lockdown, Masks, netlogo, Python, SARS-COV-2, Simulation, Social distancing, Stochastic processes, Stochasticity, Survival, VIRUS",
author = "Li, {Kelvin K.F.} and Jarvis, {Stephen A.} and Fayyaz Minhas",
note = "Funding Information: FM is supported by the PathLAKE digital pathology consortium which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government's Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). Funding Information: This study was based on the findings of the lead author's dissertation project which was completed during his time at the University of Warwick, although he is now working as a Data Scientist for the Chinese University of Hong Kong. FM is supported by the PathLAKE digital pathology consortium which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government's Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",
year = "2021",
month = jul,
doi = "10.1016/j.compbiomed.2021.104369",
language = "English",
volume = "134",
journal = "Computers in biology and medicine",
issn = "0010-4825",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Elementary effects analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of social distancing and mask usage

AU - Li, Kelvin K.F.

AU - Jarvis, Stephen A.

AU - Minhas, Fayyaz

N1 - Funding Information: FM is supported by the PathLAKE digital pathology consortium which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government's Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). Funding Information: This study was based on the findings of the lead author's dissertation project which was completed during his time at the University of Warwick, although he is now working as a Data Scientist for the Chinese University of Hong Kong. FM is supported by the PathLAKE digital pathology consortium which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government's Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). Publisher Copyright: © 2021 Elsevier Ltd

PY - 2021/7

Y1 - 2021/7

N2 - COVID-19 was declared a pandemic by the World Health Organisation (WHO) on March 11th, 2020. With half of the world's countries in lockdown as of April due to this pandemic, monitoring and understanding the spread of the virus and infection rates and how these factors relate to behavioural and societal parameters is crucial for developing control strategies. This paper aims to investigate the effectiveness of masks, social distancing, lockdown and self-isolation for reducing the spread of SARS-CoV-2 infections. Our findings from an agent-based simulation modelling showed that whilst requiring a lockdown is widely believed to be the most efficient method to quickly reduce infection numbers, the practice of social distancing and the usage of surgical masks can potentially be more effective than requiring a lockdown. Our multivariate analysis of simulation results using the Morris Elementary Effects Method suggests that if a sufficient proportion of the population uses surgical masks and follows social distancing regulations, then SARS-CoV-2 infections can be controlled without requiring a lockdown.

AB - COVID-19 was declared a pandemic by the World Health Organisation (WHO) on March 11th, 2020. With half of the world's countries in lockdown as of April due to this pandemic, monitoring and understanding the spread of the virus and infection rates and how these factors relate to behavioural and societal parameters is crucial for developing control strategies. This paper aims to investigate the effectiveness of masks, social distancing, lockdown and self-isolation for reducing the spread of SARS-CoV-2 infections. Our findings from an agent-based simulation modelling showed that whilst requiring a lockdown is widely believed to be the most efficient method to quickly reduce infection numbers, the practice of social distancing and the usage of surgical masks can potentially be more effective than requiring a lockdown. Our multivariate analysis of simulation results using the Morris Elementary Effects Method suggests that if a sufficient proportion of the population uses surgical masks and follows social distancing regulations, then SARS-CoV-2 infections can be controlled without requiring a lockdown.

KW - Agent-based modelling

KW - Coronavirus

KW - COVID-19

KW - Epidemiology

KW - Infectious diseases

KW - Isolation

KW - Lockdown

KW - Masks

KW - netlogo

KW - Python

KW - SARS-COV-2

KW - Simulation

KW - Social distancing

KW - Stochastic processes

KW - Stochasticity

KW - Survival

KW - VIRUS

UR - http://www.scopus.com/inward/record.url?scp=85105691746&partnerID=8YFLogxK

U2 - 10.1016/j.compbiomed.2021.104369

DO - 10.1016/j.compbiomed.2021.104369

M3 - Article

C2 - 33915478

AN - SCOPUS:85105691746

VL - 134

JO - Computers in biology and medicine

JF - Computers in biology and medicine

SN - 0010-4825

M1 - 104369

ER -